DeepSeek R1 vs Qwen 3: Coding Task Showdown

Software development is changing fast these days, with AI assistants now an integral part of many developers' workflows. According to Stack Overflow's 2024 survey, 63% of professional developers report using AI tools in their development process. This surge is fueled by advanced models that can write, review, and even explain code. Industry leaders have declared that "English is emerging as the universal coding language" thanks to AI, reflecting the idea that natural language prompts can replace traditional syntax. Concepts like "vibe coding" – where one "fully gives in to the vibes, embraces exponentials, and forgets that the code even exists" – have entered the lexicon, illustrating the new, fluid relationship between human intent and code. Alongside code generation, AI-assisted code review is an emerging trend: We @entelligence.ai use LLMs to automate pull-request reviews and catch bugs early. Today, we are comparing two powerful LLMs – DeepSeek R1 and Qwen 3 – on a suite of coding problems to see how they stack up in real-world coding tasks, and discuss the broader implications for AI-driven development.

Overview of the Models

DeepSeek R1 is a massive mixture-of-experts model (≈671B total parameters, 37B activated per token) from Chinese AI-Lab DeepSeek, developed with a focus on reasoning. It was trained with multi-stage reinforcement learning (RL) to explore chain-of-thought strategies. DeepSeek-R1's designers report that it "achieves performance comparable to OpenAI-o1 across math, code, and reasoning tasks", highlighting its strength in logic and problem-solving. The model is open-source, and distilled smaller versions (e.g. based on Qwen or Llama) have been released. In practice, DeepSeek R1 excels at generating detailed reasoning chains and handling complex logic, and Entelligence's benchmarks suggest it has strong code-understanding capabilities (see below).

Qwen 3 is Alibaba's latest family of LLMs, ranging from tiny (0.6B) to very large (235B parameters) models, including both dense and Mixture-of-Experts variants. Like DeepSeek, Qwen 3 uses MoE techniques (the 235B "A22B" model activates ~22B parameters per forward pass) and is open-weight and multilingual. Crucially, Qwen 3 includes specialized coding models: for example, Alibaba reports that its flagship Qwen3-235B model "achieves competitive results in benchmark evaluations of coding, math [and] general [tasks]". Independent reports note that even the mid-sized 32B Qwen 3 coding model "matches GPT-4o's coding prowess" with high accuracy. In fact, some analyses (e.g. from Entelligence) claim Qwen 3 variants outperform models like DeepSeek R1 and GPT-4 on standard benchmarks. In summary, Qwen 3 is a versatile, high-performance LLM suite with strong credentials in code generation and reasoning.

Both models are state-of-the-art and open-source, but they have different strengths: DeepSeek R1 emphasizes RL-trained reasoning patterns, while Qwen 3 emphasizes scalable performance and coding fluency. In the sections below we compare how each model tackles five practical coding problems.

Benchmark Coding Tasks

We evaluated both models on five coding challenges of increasing complexity:

Asynchronous Web Scraper: Build a web scraper using asyncio and aiohttp to fetch multiple pages concurrently (with rate limiting) and save results to a database.
Topological Sort: Given a list of tasks and dependencies (a directed acyclic graph), produce an order that respects all prerequisites (i.e. topological sort).
SaaS Landing Page: Create a modern-looking SaaS landing page for an AI code review company (HTML/CSS/JS, responsive design).
Rainbow SVG Bird: Draw a stylized flying bird in rainbow colors using SVG.
Animated Weather Card: Build a colorful, animated weather card (HTML/CSS/JS) that displays current conditions (e.g. temperature, sun/rain/cloud icons, wind speed).

For each task we present the model outputs (abridged for clarity), discuss the approaches, and judge which model handled it better.

Task 1: Asynchronous Web Scraper

Q1: Build a web scraper using asyncio and aiohttp that can concurrently scrape multiple pages, respecting rate limits, and saving the results to a database.

Description: Scrape multiple web pages concurrently using asyncio/aiohttp, enforce a rate limit, and store each page's title in a database.

Qwen 3's Solution:

Qwen 3 generated a concise Python scraper. It uses asyncio.Semaphore to limit concurrency, an aiohttp.TCPConnector(limit_per_host=2) for per-domain connection limits, and a simple re regex to extract the <title>. It also uses aiosqlite for async DB writes.

Here's a complete and well-structured implementation of a concurrent web scraper using asyncio, aiohttp, and aiosqlite that respects rate limits and stores the scraped data into a SQLite database.

✅ Features Implemented

Asynchronous scraping with aiohttp.
Concurrency control using asyncio.Semaphore.
Rate limiting per request with a configurable delay.
Per-domain connection limits via TCPConnector.
Async database writes using aiosqlite.

📁 Project Structure

web_scraper/
├── scraper.py
└── scraped_data.db  (auto-created)

🧠 Key Concepts Used

async/await: For non-blocking I/O.
Semaphore: To limit the number of concurrent requests.
TCPConnector(limit_per_host=...): To avoid hammering a single host.
aiosqlite: For asynchronous SQLite database writes.
Regex: For simple title extraction from HTML (can be replaced with BeautifulSoup in a thread pool if needed).

🧾 Full Code (`scraper.py`)

import asyncio
import aiohttp
import aiosqlite
import re
from urllib.parse import urlparse

# Configuration
CONCURRENCY_LIMIT = 10     # Max concurrent requests
RATE_LIMIT_DELAY = 0.2     # Delay between requests (in seconds)
DATABASE_NAME = 'scraped_data.db'

# List of URLs to scrape
URLS = [
    "https://example.com/page1",
    "https://example.com/page2",
    # Add more URLs here
]

# Rate-limiting semaphore
semaphore = asyncio.Semaphore(CONCURRENCY_LIMIT)

async def init_db():
    """Initialize the SQLite database."""
    async with aiosqlite.connect(DATABASE_NAME) as db:
        await db.execute('''
            CREATE TABLE IF NOT EXISTS scraped_pages (
                id INTEGER PRIMARY KEY AUTOINCREMENT,
                url TEXT NOT NULL,
                title TEXT
            )
        ''')
        await db.commit()

async def save_data(url: str, title: str):
    """Save scraped data to the database."""
    async with aiosqlite.connect(DATABASE_NAME) as db:
        await db.execute(
            'INSERT INTO scraped_pages (url, title) VALUES (?, ?)',
            (url, title)
        )
        await db.commit()

async def extract_title(html: str) -> str:
    """Extract the title from HTML content using regex."""
    match = re.search(r'<title>(.*?)</title>', html, re.IGNORECASE | re.DOTALL)
    return match.group(1).strip() if match else "No Title Found"

async def fetch(session, url: str):
    """Fetch and process a single URL."""
    async with semaphore:
        try:
            async with session.get(url) as response:
                response.raise_for_status()
                html = await response.text()
                title = await extract_title(html)
                await save_data(url, title)
                print(f"Scraped {url} - Title: {title[:50]}...")
        except Exception as e:
            print(f"Error scraping {url}: {e}")

        # Respect rate limit
        await asyncio.sleep(RATE_LIMIT_DELAY)

async def main():
    """Main async function to orchestrate scraping."""
    await init_db()

    # Limit concurrent connections per host
    connector = aiohttp.TCPConnector(limit_per_host=2)

    async with aiohttp.ClientSession(connector=connector) as session:
        tasks = [fetch(session, url) for url in URLS]
        await asyncio.gather(*tasks)

if __name__ == "__main__":
    asyncio.run(main())

🛠️ How It Works

Database Initialization: Creates a SQLite table scraped_pages if it doesn't exist.
Concurrency Control: Uses Semaphore to limit the number of simultaneous requests.
Rate Limiting: Adds a small delay (RATE_LIMIT_DELAY) after each request to avoid overwhelming servers.
Per-Host Connection Limits: TCPConnector(limit_per_host=2) ensures no more than 2 concurrent requests per domain.
HTML Parsing: Uses a simple regex to extract the <title> tag from the HTML.
Error Handling: Catches exceptions during scraping and logs errors without crashing the entire process.

📦 Requirements

Install the necessary libraries:

pip install aiohttp aiosqlite

🧪 Example Output

Scraped https://example.com/page1 - Title: Example Page 1
Scraped https://example.com/page2 - Title: Example Page 2

📚 Notes

For real-world use, consider replacing regex with BeautifulSoup inside an asyncio.to_thread() for parsing HTML.
You can extend this to respect robots.txt and respect Crawl-Delay directives.
For production, use a more robust database like PostgreSQL with asyncpg.

📌 Summary

This scraper efficiently scrapes multiple pages concurrently, respects server limits, and stores the results in a SQLite database—all using asynchronous Python. It's modular, scalable, and ready to be extended with advanced features like proxy rotation, retries, or request throttling.

Output:

This code sets up the database table, then in main() it creates an aiohttp.ClientSession with a TCPConnector(limit_per_host=2). It kicks off asynchronous fetch() tasks for all URLs and waits for them with asyncio.gather(). The scraper is modular and covers basic error handling and cleanup.

DeepSeek R1's Solution:

DeepSeek R1's output is more elaborate. It likewise uses asyncio, aiohttp, and aiosqlite, but adds extra robustness. It imports BeautifulSoup (bs4) to parse HTML (instead of regex), includes retry logic with timeouts, and structures the code into helper functions (create_table, save_to_db, etc.). Important excerpts:

Here's a complete implementation of an async web scraper using asyncio, aiohttp, and aiosqlite that handles concurrency, rate limiting, and database storage:

import asyncio
import aiohttp
import aiosqlite
from bs4 import BeautifulSoup

# Configuration
DATABASE_NAME = 'scraped_data.db'
RATE_LIMIT = 5  # Requests per second
WORKERS = 10
TIMEOUT = 10
MAX_RETRIES = 3


async def create_table(db):
    """Create database table if not exists"""
    await db.execute('''
        CREATE TABLE IF NOT EXISTS pages (
            id INTEGER PRIMARY KEY AUTOINCREMENT,
            url TEXT NOT NULL,
            title TEXT,
            content TEXT,
            timestamp DATETIME DEFAULT CURRENT_TIMESTAMP
        )
    ''')
    await db.commit()


async def save_to_db(db, url, data):
    """Save scraped data to database"""
    await db.execute('''
        INSERT INTO pages (url, title, content)
        VALUES (?, ?, ?)
    ''', (url, data['title'], data['content']))
    await db.commit()


def parse_html(html):
    """Parse HTML content using BeautifulSoup"""
    soup = BeautifulSoup(html, 'html.parser')
    title = soup.title.string if soup.title else ''
    paragraphs = [p.get_text() for p in soup.find_all('p')]
    return {
        'title': title,
        'content': '\n'.join(paragraphs)
    }


async def fetch_url(session, url):
    """Fetch URL with retries and timeout"""
    retry_delays = [1, 2, 4]  # Exponential backoff
    for attempt in range(MAX_RETRIES + 1):
        try:
            async with session.get(url, timeout=aiohttp.ClientTimeout(total=TIMEOUT)) as response:
                response.raise_for_status()
                return await response.text()
        except (aiohttp.ClientError, asyncio.TimeoutError) as e:
            if attempt < MAX_RETRIES:
                await asyncio.sleep(retry_delays[attempt])
                print(f"Retrying {url} (attempt {attempt + 1})")
            else:
                print(f"Failed to fetch {url} after {MAX_RETRIES} attempts")
                raise


async def rate_limiter(queue, max_tokens, interval):
    """Token bucket rate limiter implementation"""
    while True:
        await asyncio.sleep(interval)
        for _ in range(max_tokens):
            try:
                queue.put_nowait(1)
            except asyncio.QueueFull:
                break


async def worker(db, url_queue, rate_limit_queue):
    """Worker to process URLs from queue"""
    async with aiohttp.ClientSession() as session:
        while True:
            url = await url_queue.get()
            await rate_limit_queue.get()  # Wait for rate limit token
            
            try:
                html = await fetch_url(session, url)
                data = parse_html(html)
                await save_to_db(db, url, data)
                print(f"Scraped: {url}")
            except Exception as e:
                print(f"Error processing {url}: {str(e)}")
            finally:
                url_queue.task_done()


async def main(urls):
    """Main async function to orchestrate scraping"""
    async with aiosqlite.connect(DATABASE_NAME) as db:
        await create_table(db)
        
        url_queue = asyncio.Queue()
        for url in urls:
            await url_queue.put(url)
        
        rate_limit_queue = asyncio.Queue(maxsize=RATE_LIMIT)
        rate_limiter_task = asyncio.create_task(
            rate_limiter(rate_limit_queue, RATE_LIMIT, 1)
        )
        
        workers = [
            asyncio.create_task(worker(db, url_queue, rate_limit_queue))
            for _ in range(WORKERS)
        ]
        
        await url_queue.join()
        
        rate_limiter_task.cancel()
        for w in workers:
            w.cancel()
        
        await asyncio.gather(rate_limiter_task, *workers, return_exceptions=True)


if __name__ == '__main__':
    # Example URLs - replace with your target URLs
    sample_urls = [
        'https://example.com',
        'https://www.python.org',
        'https://aiohttp.readthedocs.io',
    ]
    
    asyncio.run(main(sample_urls))

Key features of this implementation:

Rate Limiting: Uses a token bucket algorithm to enforce rate limits
Concurrency: Uses multiple workers to process URLs concurrently
Retry Logic: Implements exponential backoff for failed requests
Database Storage: Stores results in SQLite with async operations
Error Handling: Robust error handling with retries and proper cleanup
HTML Parsing: Uses BeautifulSoup for content extraction

To use this scraper:

Install required packages:

pip install aiohttp aiosqlite beautifulsoup4

Modify the sample_urls list with your target URLs
Run the script:

python scraper.py

The scraper will:

Process URLs concurrently while respecting rate limits
Store results in an SQLite database (scraped_data.db)
Retry failed requests with exponential backoff
Handle network errors and timeouts gracefully

Note: Always check website's robots.txt and terms of service before scraping, and consider adding proper user-agent headers and request delays to be respectful of target servers.

Output:

DeepSeek's version includes a robust fetch_url() with retry/backoff, uses BeautifulSoup for parsing (which handles HTML more reliably than regex), and explicitly saves both title and content into the database. It also uses a floating rate-limit (RATE_LIMIT = 5 rps) and clean separation of concerns (table creation, saving, etc.).

Analysis:

The Qwen's code gave incomplete response. DeepSeek R1's scraper is more sophisticated: it handles retries on failure, parses HTML fully, and organizes the code into smaller functions. In terms of completeness, DeepSeek R1's answer is more production-ready. However, Qwen 3's code is leaner and easier to read. For large-scale scraping, DeepSeek R1's retry logic and parsing give it an edge in reliability.

Verdict:

DeepSeek R1 performed better overall. Its scraper is more robust and comprehensive (BeautifulSoup parsing, retry logic, structured code), whereas Qwen 3's solution is incomplete. DeepSeek R1's output scores higher on reliability and clarity, which we judge more important for this task.

Task 2: Topological Sort (Task Ordering)

Q2: "You have a list of tasks and the order they need to be done in. Your job is to arrange these tasks so that each task is done before the ones that depend on it. Understanding Topological Sort. It's like making a to-do list for a project.

Important points:

You have tasks (nodes) and dependencies (edges).
Start with tasks that don't depend on anything else.
Keep going until all tasks are on your list.
You'll end up with a list that makes sure you do everything in the right order.

Steps:

Use a list to show what tasks depend on each other.
Make an empty list for your final order of tasks.

Create a helper function to visit each task:

Mark it as in process.
Visit all the tasks that need to be done before this one.
Add this task to your final list.

Mark it as done. Start with tasks that don't have any prerequisites."

Description: Given a list of tasks and dependency pairs (A must come before B), produce an ordering of tasks such that all prerequisites are satisfied. Detect and handle cycles.

Qwen 3's Solution:

Qwen 3 provided a DFS-based topological sort with cycle detection. It marks each node as 'visiting' or 'visited' and builds a result list. Key parts:

Here's a well-structured and robust implementation of Topological Sort in Python, based on your detailed description. This function arranges tasks in such a way that every task appears before any task that depends on it, respecting the dependencies between them.

✅ Key Features

Cycle Detection: Detects and handles circular dependencies.
DFS-Based Algorithm: Uses depth-first search to ensure all prerequisites are processed before the task itself.
Flexible Input: Accepts a list of tasks and a dictionary of dependencies.
Efficient and Correct: Produces one valid topological ordering of the tasks.

🧠 Understanding the Approach

Graph Representation: Tasks and their dependencies are modeled as a directed graph.
DFS Traversal: For each task, recursively visit all its prerequisites (dependencies).
Cycle Detection: If during traversal we revisit a node that is currently being processed (visiting), a cycle is detected.
State Tracking: Nodes are marked as unvisited, visiting, or visited to manage traversal and detect cycles.

🧾 Code Implementation

def topological_sort(tasks, dependencies):
    """
    Perform a topological sort on a list of tasks with dependencies.

    Args:
        tasks (list): List of all tasks (nodes) to be sorted.
        dependencies (dict): Dictionary where each key is a task,
                             and the value is a list of tasks that must be completed before it.

    Returns:
        list: A list of tasks in topologically sorted order.
              Returns an empty list if a cycle is detected.
    """
    visited = {}  # Tracks the state of each node: 'unvisited', 'visiting', 'visited'
    result = []
    has_cycle = False

    def dfs(node):
        nonlocal has_cycle
        if visited.get(node) == 'visiting':
            # Cycle detected
            has_cycle = True
            return
        if visited.get(node) == 'visited':
            return  # Already processed

        visited[node] = 'visiting'

        # Visit all prerequisites (dependencies)
        for prereq in dependencies.get(node, []):
            dfs(prereq)
            if has_cycle:
                return

        visited[node] = 'visited'
        result.append(node)

    for task in tasks:
        if visited.get(task) != 'visited':
            dfs(task)
            if has_cycle:
                return []

    return result

📌 Example Usage

# Example 1: Simple dependencies
tasks = ["A", "B", "C"]
dependencies = {
    "A": ["B", "C"],  # A depends on B and C
    "B": [],           # B has no dependencies
    "C": []            # C has no dependencies
}

print(topological_sort(tasks, dependencies))
# Possible outputs: ['B', 'C', 'A'] or ['C', 'B', 'A']

# Example 2: Cycle detection
tasks = ["A", "B"]
dependencies = {
    "A": ["B"],
    "B": ["A"]  # Circular dependency
}

print(topological_sort(tasks, dependencies))
# Output: []

# Example 3: Complex dependencies (diamond structure)
tasks = ["A", "B", "C", "D"]
dependencies = {
    "A": ["B"],
    "C": ["B"],
    "D": ["A", "C"]
}

print(topological_sort(tasks, dependencies))
# Possible outputs: ['B', 'A', 'C', 'D'] or ['B', 'C', 'A', 'D']

🧪 Notes

The order of tasks in the input list can affect the final topological order, especially when multiple valid orderings exist.
This implementation assumes all tasks in dependencies are included in the tasks list.
If a cycle is detected, the function returns an empty list. You can modify this behavior to raise an exception if preferred.

📚 Summary

This implementation provides a correct and efficient way to perform topological sorting using depth-first search. It ensures that each task is scheduled after all its prerequisites, and gracefully handles circular dependencies by detecting and reporting them. This is ideal for applications like build systems, course scheduling, dependency resolution, and more.

This implementation handles cycles by detecting a back-edge (revisiting a "visiting" node) and returns an empty list on cycle. It uses recursion to visit prerequisites first, then appends the node to the result. Qwen's solution is well-documented and even includes example usage in the output.

DeepSeek R1's Solution:

DeepSeek R1 chose Kahn's algorithm (in-degree method). It builds an adjacency list and in-degree counts, then repeatedly pops zero-indegree nodes.

Here's a Python implementation of topological sort using Depth-First Search (DFS) with cycle detection:

def topological_sort(tasks, dependencies):
    """
    Perform topological sorting on tasks with dependencies.
    
    Args:
        tasks: List of task identifiers (can be strings, numbers, etc.)
        dependencies: List of tuples (A, B) where task B depends on task A
        
    Returns:
        Ordered list of tasks that satisfies all dependencies
        
    Raises:
        ValueError: If a cycle is detected in the dependencies
    """
    # Build the adjacency list and track all nodes
    graph = {task: [] for task in tasks}
    in_degree = {task: 0 for task in tasks}
    
    for prerequisite, task in dependencies:
        graph[prerequisite].append(task)
        in_degree[task] += 1

    # Kahn's algorithm for topological sort
    queue = [task for task, degree in in_degree.items() if degree == 0]
    order = []
    
    while queue:
        node = queue.pop(0)
        order.append(node)
        
        for neighbor in graph[node]:
            in_degree[neighbor] -= 1
            if in_degree[neighbor] == 0:
                queue.append(neighbor)
    
    if len(order) != len(tasks):
        # Cycle detected if not all tasks are processed
        cycle = set(tasks) - set(order)
        raise ValueError(f"Cycle detected involving tasks: {cycle}")
    
    return order

# Example usage:
if __name__ == "__main__":
    tasks = ['A', 'B', 'C', 'D', 'E']
    dependencies = [('A', 'B'), ('B', 'C'), ('D', 'E'), ('C', 'E')]

    try:
        ordered_tasks = topological_sort(tasks, dependencies)
        print("Valid execution order:", ordered_tasks)
    except ValueError as e:
        print("Error:", str(e))

Key features of this implementation:

Kahn's Algorithm:
- Uses in-degree tracking for efficient ordering
- Processes nodes with zero dependencies first
- Detects cycles by checking if all nodes were processed
Cycle Detection:
- Automatically checks for circular dependencies
- Provides helpful error message with problematic tasks
Efficiency:
- Time complexity: O(V + E) (vertices + edges)
- Space complexity: O(V + E)
Input Handling:
- Requires explicit list of all tasks
- Processes dependencies as (prerequisite, task) pairs

Example output for the sample input:

Valid execution order: ['A', 'D', 'B', 'C', 'E']

This implementation:

Starts with tasks that have no dependencies (A and D)
Processes dependent tasks in valid order
Ensures all dependencies are respected
Handles multiple independent dependency chains

To use with different tasks/dependencies:

tasks = [1, 2, 3, 4]
dependencies = [(1, 2), (2, 3), (3, 4)]
print(topological_sort(tasks, dependencies))  # Output: [1, 2, 3, 4]

DeepSeek's code expects dependencies as a list of tuples (rather than a dict). It raises an exception if a cycle remains (when not all tasks get processed). This implementation is iterative and efficient, and it clearly distinguishes building the graph from processing it.

Analysis:

Both solutions correctly implement topological sort. Qwen 3's DFS approach is conceptually clear and handles cycles gracefully (returning an empty list). DeepSeek R1's Kahn algorithm is likewise correct and arguably more straightforward for cycle detection (it directly checks if all tasks are ordered). In terms of performance on large graphs, Kahn's algorithm (DeepSeek) avoids recursion and may be slightly faster/better for very large inputs, while the DFS approach (Qwen) is easier to follow but relies on recursion.

Verdict:

DeepSeek R1 slightly outperforms Qwen 3 on this task. Its Kahn's algorithm implementation is concise and efficient, and it explicitly raises an error on cycles. Qwen 3's DFS solution is adequate but somewhat more complex (tracking node states). For reliability and large-input performance, DeepSeek R1 gets the nod.

Task 3: SaaS Landing Page (AI Code Review Company)

Q3: Create a modern looking saas landing page for an AI Code Review Company.

Description: Design a modern, responsive SaaS landing page (HTML/CSS/JavaScript) for an AI code review startup. Include sections like hero, features, testimonials, pricing, etc., with a clean aesthetic.

Qwen 3's Solution:

Qwen 3 produced a full static webpage with custom CSS. It set up a dark theme using CSS variables, a sticky header with nav links, and typical sections (hero, features, how-it-works, testimonials, pricing, FAQ, footer). The key features included glassmorphism and soft gradients. For example, it defined primary/secondary colors and applied them in CSS, created a <header> with a gradient backdrop, and wrote layout styles manually.

Here's a modern SaaS landing page for an AI Code Review company using HTML/CSS/JS with a clean, responsive design and modern aesthetics (soft gradients, glassmorphism, animations, and a tech-forward feel).

✅ Key Features

Hero Section: Bold headline + CTA
Features: Icons & descriptions
How It Works
Testimonials
Pricing
FAQ
Responsive Design
Minimal JS for interactivity (mobile nav & FAQ accordion)

🌐 Full Code (HTML + CSS + JS)

<!DOCTYPE html>
<html lang="en">
<head>
  <meta charset="UTF-8" />
  <meta name="viewport" content="width=device-width, initial-scale=1.0"/>
  <title>CodeWise AI | AI-Powered Code Review</title>
  <link href="https://fonts.googleapis.com/css2?family=Inter:wght@400;600;700&display=swap" rel="stylesheet">
  <style>
    :root {
      --primary: #4F46E5;
      --secondary: #10B981;
      --bg: #0F172A;
      --white: #FFFFFF;
      --gray: #64748b;
    }

    * {
      margin: 0;
      padding: 0;
      box-sizing: border-box;
    }

    body {
      font-family: 'Inter', sans-serif;
      background-color: var(--bg);
      color: var(--white);
      line-height: 1.6;
    }

    header {
      background: rgba(15, 23, 42, 0.95);
      backdrop-filter: blur(10px);
      position: sticky;
      top: 0;
      z-index: 1000;
    }

    nav {
      display: flex;
      justify-content: space-between;
      align-items: center;
      max-width: 1200px;
      margin: auto;
    }

    .logo {
      font-size: 1.5rem;
      font-weight: 700;
      color: var(--secondary);
    }

    .nav-links {
      display: flex;
      gap: 1.5rem;
      align-items: center;
    }

    .nav-links a {
      color: var(--white);
      text-decoration: none;
      transition: color 0.3s ease;
    }

    .nav-links a:hover {
      color: var(--secondary);
    }

    .cta-button {
      background: var(--secondary);
      padding: 0.6rem 1.2rem;
      border-radius: 8px;
      color: var(--bg);
      font-weight: 600;
      cursor: pointer;
      transition: background 0.3s ease;
    }

    .cta-button:hover {
      background: #059669;
    }

    .hero {
      padding: 5rem 2rem;
      text-align: center;
      background: linear-gradient(145deg, var(--bg), #1E293B);
    }

    .hero h1 {
      font-size: 3rem;
      margin-bottom: 1rem;
    }

    .hero p {
      font-size: 1.25rem;
      max-width: 700px;
      margin: 0 auto 2rem;
      color: var(--gray);
    }

    .hero .cta-button {
      font-size: 1rem;
    }

    .features {
      display: grid;
      grid-template-columns: repeat(auto-fit, minmax(250px, 1fr));
      gap: 2rem;
      padding: 4rem 2rem;
      background: #111827;
    }

    .feature {
      background: rgba(255, 255, 255, 0.05);
      padding: 2rem;
      border-radius: 12px;
      backdrop-filter: blur(10px);
      transition: transform 0.3s ease;
    }

    .feature:hover {
      transform: translateY(-5px);
    }

    .feature h3 {
      margin-bottom: 1rem;
      color: var(--secondary);
    }

    .how-it-works {
      padding: 4rem 2rem;
      background: var(--bg);
      text-align: center;
    }

    .steps {
      display: flex;
      flex-wrap: wrap;
      justify-content: center;
      gap: 2rem;
      margin-top: 2rem;
    }

    .step {
      background: rgba(255, 255, 255, 0.05);
      padding: 2rem;
      border-radius: 12px;
      width: 250px;
    }

    .step-number {
      font-size: 2rem;
      color: var(--secondary);
    }

    .testimonials {
      background: #111827;
      padding: 4rem 2rem;
      text-align: center;
    }

    .testimonial {
      max-width: 600px;
      margin: 2rem auto;
      font-style: italic;
      color: var(--gray);
    }

    .pricing {
      padding: 4rem 2rem;
      background: var(--bg);
      text-align: center;
    }

    .pricing-cards {
      display: grid;
      grid-template-columns: repeat(auto-fit, minmax(250px, 1fr));
      gap: 2rem;
    }

    .card {
      background: rgba(255, 255, 255, 0.05);
      padding: 2rem;
      border-radius: 12px;
      transition: transform 0.3s ease;
    }

    .card:hover {
      transform: translateY(-5px);
    }

    .card h3 {
      margin-bottom: 1rem;
      color: var(--secondary);
    }

    .faq {
      padding: 4rem 2rem;
      background: #111827;
      text-align: center;
    }

    .faq-accordion {
      max-width: 800px;
      margin: 2rem auto;
      display: flex;
      flex-direction: column;
      gap: 1rem;
    }

    .faq-item {
      background: rgba(255, 255, 255, 0.05);
      padding: 1rem;
      border-radius: 8px;
      cursor: pointer;
    }

    .faq-item.active .answer {
      display: block;
      margin-top: 0.5rem;
    }

    .answer {
      display: none;
      color: var(--gray);
    }

    footer {
      background: var(--bg);
      padding: 2rem;
      text-align: center;
      color: var(--gray);
    }

    @media (max-width: 768px) {
      .nav-links {
        display: none;
        flex-direction: column;
        background: rgba(15, 23, 42, 0.95);
        position: absolute;
        top: 60px;
        left: 0;
        right: 0;
        padding: 1rem;
      }

      .nav-links.active {
        display: flex;
      }

      .menu-toggle {
        display: block;
        cursor: pointer;
        font-size: 1.5rem;
      }
    }

    .menu-toggle {
      display: none;
    }
  </style>
</head>
<body>

  <!-- Header -->
  <header>
    <nav>
      <div class="logo">CodeWise AI</div>
      <div class="menu-toggle" id="menu-toggle">&#9776;</div>
      <div class="nav-links" id="nav-links">
        <a href="#features">Features</a>
        <a href="#how-it-works">How It Works</a>
        <a href="#testimonials">Testimonials</a>
        <a href="#pricing">Pricing</a>
        <a href="#faq">FAQ</a>
        <a href="#">Login</a>
        <button class="cta-button">Start Free Trial</button>
      </div>
    </nav>
  </header>

  <!-- Hero Section -->
  <section class="hero">
    <h1>Elevate Your Code Quality with AI</h1>
    <p>Automated code review powered by machine learning. Detect bugs, improve readability, and enforce best practices — all in real time.</p>
    <button class="cta-button">Get Started</button>
  </section>

  <!-- Features -->
  <section class="features" id="features">
    <div class="feature">
      <h3>🤖 Instant Feedback</h3>
      <p>Get real-time suggestions and fixes as you code.</p>
    </div>
    <div class="feature">
      <h3>🔒 Secure & Private</h3>
      <p>All code reviews are encrypted and never stored.</p>
    </div>
    <div class="feature">
      <h3>🚀 Seamless Integration</h3>
      <p>Works with GitHub, GitLab, VS Code, and more.</p>
    </div>
    <div class="feature">
      <h3>📈 Scalable for Teams</h3>
      <p>From solo devs to enterprise teams, we scale with you.</p>
    </div>
  </section>

  <!-- How It Works -->
  <section class="how-it-works" id="how-it-works">
    <h2>How It Works</h2>
    <div class="steps">
      <div class="step">
        <div class="step-number">1</div>
        <h3>Connect</h3>
        <p>Link your repositories or IDE in seconds.</p>
      </div>
      <div class="step">
        <div class="step-number">2</div>
        <h3>Analyze</h3>
        <p>AI scans your codebase for issues and improvements.</p>
      </div>
      <div class="step">
        <div class="step-number">3</div>
        <h3>Improve</h3>
        <p>Receive actionable feedback to fix bugs and optimize code.</p>
      </div>
    </div>
  </section>

  <!-- Testimonials -->
  <section class="testimonials" id="testimonials">
    <h2>Trusted by Developers Worldwide</h2>
    <div class="testimonial">
      "CodeWise AI caught a critical bug in our production code before we even deployed. Game-changer!" — Jane Doe, Lead Developer
    </div>
    <div class="testimonial">
      "Our team's code quality improved by 40% in just 3 months." — Alex Smith, Engineering Manager
    </div>
  </section>

  <!-- Pricing -->
  <section class="pricing" id="pricing">
    <h2>Simple, Transparent Pricing</h2>
    <div class="pricing-cards">
      <div class="card">
        <h3>Free</h3>
        <p>$0/mo</p>
        <ul>
          <li>1 project</li>
          <li>Basic code analysis</li>
          <li>Email support</li>
        </ul>
        <button class="cta-button">Start Free</button>
      </div>
      <div class="card">
        <h3>Pro</h3>
        <p>$29/mo</p>
        <ul>
          <li>Unlimited projects</li>
          <li>Premium checks</li>
          <li>Priority support</li>
        </ul>
        <button class="cta-button">Go Pro</button>
      </div>
      <div class="card">
        <h3>Enterprise</h3>
        <p>Custom</p>
        <ul>
          <li>On-premise hosting</li>
          <li>Dedicated account manager</li>
          <li>Custom AI models</li>
        </ul>
        <button class="cta-button">Contact Us</button>
      </div>
    </div>
  </section>

  <!-- FAQ -->
  <section class="faq" id="faq">
    <h2>Frequently Asked Questions</h2>
    <div class="faq-accordion">
      <div class="faq-item" onclick="toggleFaq(this)">
        <strong>What languages do you support?</strong>
        <div class="answer">Currently supports JavaScript, Python, Java, TypeScript, and Go.</div>
      </div>
      <div class="faq-item" onclick="toggleFaq(this)">
        <strong>Can I cancel anytime?</strong>
        <div class="answer">Yes, no strings attached.</div>
      </div>
      <div class="faq-item" onclick="toggleFaq(this)">
        <strong>Is my code private?</strong>
        <div class="answer">Yes! We never store or share your code.</div>
      </div>
    </div>
  </section>

  <!-- Footer -->
  <footer>
    <p>&copy; 2025 CodeWise AI. All rights reserved.</p>
    <p><a href="#">Privacy Policy</a> | <a href="#">Terms of Service</a></p>
  </footer>

  <script>
    // Toggle mobile menu
    document.getElementById('menu-toggle').addEventListener('click', () => {
      document.getElementById('nav-links').classList.toggle('active');
    });

    // FAQ Accordion
    function toggleFaq(item) {
      item.classList.toggle('active');
    }
  </script>
</body>
</html>

🎨 Design Highlights

Glassmorphism Effect: Faint translucent backgrounds with backdrop-filter.
Soft Gradients: For hero and alternating sections.
Hover Effects: Subtle animations on cards and buttons.
Responsive Layout: Mobile menu toggle and grid layouts that adapt to screen size.
Modern Fonts: Uses Inter for a clean UI look.

📱 Mobile Preview

Collapsible Menu: Click the hamburger icon to reveal nav links.
Stacked Cards: Features and pricing cards stack vertically.
Accordion FAQ: Users can expand/collapse questions.

🧩 Extendability

You can easily extend this template by:

Adding animations via libraries like AOS.js or GSAP.
Integrating Stripe or PayPal for payments.
Hooking into backend APIs for live demo or user sign-in.
Replacing testimonials with Swiper.js carousel for dynamic UX.

✅ Final Notes

This landing page is ready to deploy on platforms like Vercel, Netlify, or GitHub Pages. You can plug in backend logic or connect it to your SaaS app with minimal effort.

Let me know if you'd like a React version, TailwindCSS variant, or a dark/light mode toggle!

This page is self-contained (all CSS is in <style> tags, using Google Fonts) and follows modern design patterns. It includes a nav bar, hero section, and placeholders for other sections. The design uses gradients and minimal JavaScript (possibly toggling mobile nav, accordion FAQ). Qwen 3's output is detailed and implements most of the requested sections with clean HTML structure.

DeepSeek R1's Solution:

DeepSeek's answer also delivers a polished landing page, but uses Tailwind CSS for styling. Key points: it links to the Tailwind CDN and FontAwesome, and uses Tailwind utility classes for layout. An excerpt:

Here's a modern SaaS landing page design for an AI Code Review company using HTML and Tailwind CSS:

<!DOCTYPE html>
<html lang="en">
<head>
    <meta charset="UTF-8">
    <meta name="viewport" content="width=device-width, initial-scale=1.0">
    <title>CodeAI - Intelligent Code Review</title>
    <script src="https://cdn.tailwindcss.com"></script>
    <link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/6.0.0/css/all.min.css">
</head>
<body class="font-sans">
    <!-- Navigation -->
    <nav class="bg-white shadow-sm sticky top-0 z-50">
        <div class="max-w-7xl mx-auto px-4 sm:px-6 lg:px-8">
            <div class="flex justify-between h-16">
                <div class="flex items-center">
                    <div class="flex-shrink-0 font-bold text-2xl bg-gradient-to-r from-purple-600 to-blue-500 bg-clip-text text-transparent">
                        CodeAI
                    </div>
                    <div class="hidden md:flex space-x-8 ml-10">
                        <a href="#" class="text-gray-600 hover:text-purple-600">Features</a>
                        <a href="#" class="text-gray-600 hover:text-purple-600">Testimonials</a>
                        <a href="#" class="text-gray-600 hover:text-purple-600">Pricing</a>
                    </div>
                </div>
                <div class="flex items-center">
                    <a href="#" class="bg-gradient-to-r from-purple-600 to-blue-500 text-white px-6 py-2 rounded-full hover:shadow-lg transition-shadow">
                        Get Started
                    </a>
                </div>
            </div>
        </div>
    </nav>

    <!-- Hero Section -->
    <section class="bg-gradient-to-b from-white to-purple-50">
        <div class="max-w-7xl mx-auto px-4 sm:px-6 lg:px-8 py-20">
            <div class="text-center">
                <h1 class="text-4xl md:text-6xl font-bold text-gray-900 mb-6">
                    Revolutionize Your Code Reviews with AI
                </h1>
                <p class="text-xl text-gray-600 mb-8 max-w-3xl mx-auto">
                    Automate your code review process with intelligent AI analysis that finds bugs, suggests improvements, and enforces best practices in real-time.
                </p>
                <div class="flex justify-center space-x-4">
                    <a href="#" class="bg-gradient-to-r from-purple-600 to-blue-500 text-white px-8 py-4 rounded-full text-lg hover:shadow-lg transition-shadow">
                        Start Free Trial
                    </a>
                    <a href="#" class="border-2 border-gray-300 text-gray-700 px-8 py-4 rounded-full text-lg hover:border-purple-500 transition-colors">
                        See Demo
                    </a>
                </div>
            </div>
            <div class="mt-16 bg-white rounded-xl shadow-xl p-2 max-w-4xl mx-auto">
                <!-- Placeholder for code review animation -->
                <div class="bg-gray-100 h-96 rounded-lg flex items-center justify-center">
                    <div class="text-center text-gray-500">
                        <i class="fas fa-code text-4xl mb-4"></i>
                        <p>AI Code Review in Action</p>
                    </div>
                </div>
            </div>
        </div>
    </section>

    <!-- Features Section -->
    <section class="py-20">
        <div class="max-w-7xl mx-auto px-4 sm:px-6 lg:px-8">
            <div class="text-center mb-16">
                <h2 class="text-3xl font-bold text-gray-900 mb-4">
                    Smart Code Analysis Features
                </h2>
                <p class="text-gray-600 max-w-2xl mx-auto">
                    Harness the power of machine learning to improve code quality and developer productivity
                </p>
            </div>
            <div class="grid md:grid-cols-3 gap-8">
                <div class="p-6 bg-white rounded-xl shadow-lg hover:shadow-xl transition-shadow">
                    <div class="w-12 h-12 bg-purple-100 rounded-lg flex items-center justify-center mb-4">
                        <i class="fas fa-robot text-purple-600 text-xl"></i>
                    </div>
                    <h3 class="text-xl font-semibold mb-2">AI-Powered Reviews</h3>
                    <p class="text-gray-600">Instant automated code reviews with intelligent suggestions and best practice recommendations</p>
                </div>
                <!-- Add more feature cards here -->
            </div>
        </div>
    </section>

    <!-- CTA Section -->
    <section class="bg-gradient-to-r from-purple-600 to-blue-500 text-white py-20">
        <div class="max-w-7xl mx-auto px-4 sm:px-6 lg:px-8 text-center">
            <h2 class="text-3xl font-bold mb-6">Ready to Transform Your Workflow?</h2>
            <p class="text-xl mb-8 max-w-2xl mx-auto">Join thousands of developers already improving their code quality with CodeAI</p>
            <a href="#" class="bg-white text-purple-600 px-8 py-3 rounded-full text-lg font-semibold hover:bg-opacity-90 transition-all">
                Start Your Free Trial Today
            </a>
        </div>
    </section>

    <!-- Footer -->
    <footer class="bg-gray-50">
        <div class="max-w-7xl mx-auto px-4 sm:px-6 lg:px-8 py-12">
            <!-- Footer content -->
        </div>
    </footer>
</body>
</html>

This landing page includes:

Modern gradient color scheme with purple and blue accents
Clean, minimal design with ample white space
Sticky navigation with gradient logo
Hero section with compelling headline and CTA buttons
Animated code review demonstration placeholder
Feature highlights with icons
Gradient CTA section
Responsive design for all screen sizes

Key features:

Built with Tailwind CSS for modern styling
Mobile-responsive layout
Gradient accents for visual interest
Clear value proposition
Multiple call-to-action sections
Feature highlights with icons
Smooth hover effects and transitions

To enhance this further, you could:

Add actual product screenshots or demo videos
Include real customer testimonials
Add loading animations
Implement interactive elements like a live code editor demo
Add more sections like pricing tables, team members, or integration partners
Include trust indicators like client logos or statistics

Remember to replace the placeholder content with actual product information and add proper meta tags for SEO optimization.

DeepSeek's design also has all the required sections (nav, hero, features, etc.). Using Tailwind made the HTML concise (many classes instead of writing custom CSS). The visual style is bright and gradient-heavy (e.g. gradient text, and a white-to-purple hero background). Note that DeepSeek's code assumes Internet access to fetch Tailwind and FontAwesome, whereas Qwen's solution had all CSS inline.

Analysis:

Both pages meet the requirements with modern aesthetics. Qwen 3's version uses plain CSS (no external frameworks), which means it works in any environment without CDN dependencies. It has more detailed custom styling defined in <style>. DeepSeek R1's version uses Tailwind, which makes the HTML shorter but relies on the Tailwind CDN. In terms of visual appeal, both designs are clean and professional. Qwen 3's output featured a dark mode with glassy headers, whereas DeepSeek's used lighter gradients. Functionality (menus, responsiveness) appears similar.

Verdict:

Tie, with a slight edge to Qwen 3 for self-containment. Both models produced high-quality landing pages. Qwen 3's answer is remarkable for being pure HTML/CSS without external deps, which is practical. DeepSeek R1's Tailwind solution is also excellent and arguably more maintainable (less custom CSS). Overall, Qwen 3 wins by a hair due to its fully standalone implementation.

Task 4: Rainbow SVG Bird

Q4: Create a Representation for a Flying Bird in rainbow colour with SVG Code

Description: Generate an SVG graphic of a flying bird using rainbow colors and gradients. The design should be stylized and scalable.

Qwen 3's Solution:

Qwen 3 produced a detailed SVG with multiple gradient definitions. It defined separate linear gradients for the left wing, right wing, body, and tail, each sweeping through the red→orange→yellow→green→blue→indigo→violet spectrum. The bird shape was constructed with <path> elements for wings, body, and tail. For example:

Here's a rainbow-colored flying bird SVG with a stylized, abstract design using linear gradients to create vibrant color transitions across its wings, body, and tail feathers. This SVG is scalable, responsive, and visually dynamic, perfect for web use or embedding in modern UIs.

🌈 Key Features

Rainbow gradients across wings, body, and tail.
Abstract, stylized bird in a flying pose.
Modular and editable: You can tweak colors, shapes, and gradients easily.
Responsive viewBox for scaling.

✅ SVG Code

<svg width="100%" height="100%" viewBox="0 0 200 100" xmlns="http://www.w3.org/2000/svg" aria-label="A rainbow-colored flying bird">
  <defs>
    <!-- Rainbow Gradient for Left Wing -->
    <linearGradient id="rainbow-wing-left" x1="0%" y1="0%" x2="100%" y2="0%">
      <stop offset="0%" stop-color="#FF0000"/>
      <stop offset="20%" stop-color="#FFA500"/>
      <stop offset="40%" stop-color="#FFD700"/>
      <stop offset="60%" stop-color="#00FF00"/>
      <stop offset="80%" stop-color="#0000FF"/>
      <stop offset="100%" stop-color="#8A2BE2"/>
    </linearGradient>

    <!-- Rainbow Gradient for Right Wing -->
    <linearGradient id="rainbow-wing-right" x1="100%" y1="0%" x2="0%" y2="0%">
      <stop offset="0%" stop-color="#FF0000"/>
      <stop offset="20%" stop-color="#FFA500"/>
      <stop offset="40%" stop-color="#FFD700"/>
      <stop offset="60%" stop-color="#00FF00"/>
      <stop offset="80%" stop-color="#0000FF"/>
      <stop offset="100%" stop-color="#8A2BE2"/>
    </linearGradient>

    <!-- Rainbow Gradient for Body -->
    <linearGradient id="rainbow-body" x1="0%" y1="0%" x2="0%" y2="100%">
      <stop offset="0%" stop-color="#FF0000"/>
      <stop offset="20%" stop-color="#FFA500"/>
      <stop offset="40%" stop-color="#FFD700"/>
      <stop offset="60%" stop-color="#00FF00"/>
      <stop offset="80%" stop-color="#0000FF"/>
      <stop offset="100%" stop-color="#8A2BE2"/>
    </linearGradient>

    <!-- Rainbow Gradient for Tail Feathers -->
    <linearGradient id="rainbow-tail" x1="0%" y1="0%" x2="100%" y2="100%">
      <stop offset="0%" stop-color="#FF0000"/>
      <stop offset="20%" stop-color="#FFA500"/>
      <stop offset="40%" stop-color="#FFD700"/>
      <stop offset="60%" stop-color="#00FF00"/>
      <stop offset="80%" stop-color="#0000FF"/>
      <stop offset="100%" stop-color="#8A2BE2"/>
    </linearGradient>
  </defs>

  <!-- Left Wing -->
  <path d="M30,50 C20,30 50,20 60,40 C70,60 40,70 30,50 Z"
        fill="url(#rainbow-wing-left)" />

  <!-- Right Wing -->
  <path d="M170,50 C180,30 150,20 140,40 C130,60 160,70 170,50 Z"
        fill="url(#rainbow-wing-right)" />

  <!-- Body -->
  <path d="M60,40 C70,60 130,60 140,40 C130,30 70,30 60,40 Z"
        fill="url(#rainbow-body)" />

  <!-- Head -->
  <circle cx="100" cy="30" r="10" fill="url(#rainbow-body)" />

  <!-- Beak -->
  <path d="M110,28 L118,30 L110,32 Z" fill="#000" />

  <!-- Eye -->
  <circle cx="95" cy="27" r="2" fill="#000" />

  <!-- Tail Feathers -->
  <path d="M60,40 L40,60 L50,65 L60,55 Z"
        fill="url(#rainbow-tail)" />
  <path d="M60,40 L40,60 L45,70 L60,60 Z"
        fill="url(#rainbow-tail)" />
</svg>

🧠 How It Works

Gradients: Six linear gradients (rainbow-wing-left, rainbow-wing-right, rainbow-body, rainbow-tail) define the rainbow color flow.
Paths: Each body part (wings, body, tail) is drawn with a path element, filled with the appropriate gradient.
Symmetry & Flow: The wings are mirrored, and the tail uses overlapping paths for a feathered appearance.
Head & Details: A circle for the head, a triangular path for the beak, and a small circle for the eye add character.

🛠️ How to Customize

Change Colors: Modify the stop colors in the gradients to match your brand or theme.
Adjust Shape: Tweak the path d values to change wing shape, tail length, etc.
Add Animation: Use CSS or JavaScript to animate the wings or make the bird "fly."

📦 Embedding in HTML

<div style="width: 100%; height: 200px;">
  <!-- Paste SVG code here -->
</div>

🧪 Preview

You can view the rendered SVG using:

CodePen
JSFiddle
Any browser by saving as .html or .svg

✅ Summary

This rainbow-colored flying bird SVG uses gradient fills to simulate a vibrant, colorful effect across wings, body, and tail feathers. It's a great visual asset for landing pages, loading animations, or design systems. Easily customizable, scalable, and visually striking! 🎨

Let me know if you'd like:

Animated version (e.g., flapping wings)
Different bird species
Tailwind CSS integration
React component version

(This is a simplified excerpt.) Qwen's output included comments and clearly labeled gradients. The result is a very colorful, cartoon-like bird: each wing and the body uses a horizontal or vertical rainbow gradient, giving a bright, vivid look. It also set viewBox="0 0 200 100" to make the SVG scalable.

DeepSeek R1's Solution:

DeepSeek R1 also generated an SVG bird (i don't think it is a bird xD), but took a different artistic approach. It defined a single rainbow gradient sweeping horizontally (id="rainbow") for the whole bird, plus a drop-shadow filter. The bird's body and wings were drawn with Bézier curves and then filled with fill="url(#rainbow)". For example:

Here's an SVG representation of a stylized flying bird with rainbow colors, incorporating smooth curves and gradient effects:

<svg width="400" height="400" viewBox="0 0 200 200" xmlns="http://www.w3.org/2000/svg">
  <defs>
    <linearGradient id="rainbow" x1="0%" y1="50%" x2="100%" y2="50%">
      <stop offset="0%" stop-color="#FF0000"/>
      <stop offset="16.6%" stop-color="#FF7F00"/>
      <stop offset="33.3%" stop-color="#FFFF00"/>
      <stop offset="50%" stop-color="#00FF00"/>
      <stop offset="66.6%" stop-color="#0000FF"/>
      <stop offset="83.3%" stop-color="#4B0082"/>
      <stop offset="100%" stop-color="#8F00FF"/>
    </linearGradient>
    
    <filter id="shadow" x="-20%" y="-20%" width="140%" height="140%">
      <feDropShadow dx="2" dy="2" stdDeviation="2" flood-color="rgba(0,0,0,0.3)"/>
    </filter>
  </defs>

  <!-- Motion trails -->
  <path d="M70 110 Q90 90 110 110" stroke="#ffffff30" fill="none" stroke-width="3"/>
  <path d="M65 115 Q85 95 105 115" stroke="#ffffff30" fill="none" stroke-width="3"/>

  <!-- Main bird body -->
  <path d="M100 100 C80 80 120 60 140 80 S160 120 140 140 120 160 100 140 80 120 100 100" 
        fill="url(#rainbow)" 
        filter="url(#shadow)"
        stroke="#00000030" 
        stroke-width="1.5"/>

  <!-- Wing details -->
  <path d="M110 95 Q115 85 125 90" stroke="#00000030" fill="none" stroke-width="1"/>
  <path d="M90 95 Q85 85 75 90" stroke="#00000030" fill="none" stroke-width="1"/>
</svg>

This SVG features:

A rainbow gradient using all 7 spectral colors
A stylized bird shape created with Bézier curves
Subtle motion trails behind the bird
Soft shadow effects
Wing detail lines
Semi-transparent black strokes for definition
Smooth color transitions across the bird's body

You can adjust the colors in the <linearGradient> section or modify the path coordinates in the <path> elements to change the bird's shape and size.

DeepSeek generated incomplete output.

Analysis:

Only Qwen 3 SVG fulfill the "rainbow bird" requirement. Qwen 3's approach paints each part of the bird in full rainbow, yielding a very bright, segmented look. DeepSeek R1's uses one gradient across the whole body, giving a cohesive rainbow color sweep. Qwen's output is more colorful in that multiple gradients are stacked, while DeepSeek's design is not up to the mark. For vividness, Qwen 3 nails the "rainbow" theme explicitly.

Verdict:

Qwen 3 wins for colorfulness. Its multi-gradient wings and tail create a truly rainbow-colored bird as requested. DeepSeek R1's illustration is incomplete but Qwen's SVG has vibrant approach. Because the task emphasized rainbow colors, Qwen 3's solution is a better match to the brief.

Task 5: Animated Weather Card

Q5: Create a Colourful and animated weather card that shows current weather conditions including temperature, rainy/cloudy/sunny, wind speed, and other stuff.

Description: Create an interactive weather widget (HTML/CSS/JavaScript) that shows current weather (temperature, condition like sun/rain/cloud, wind speed, etc.) with animated icons and colorful themes.

Qwen 3's Solution:

Qwen 3 output an HTML file with inline CSS and JS. It defined CSS variables for different weather themes and implemented animations (clouds floating, raindrops falling, a glowing sun). For example, its CSS starts with:

Here's a colorful animated weather card using HTML, CSS, and JavaScript. It displays temperature, weather condition, wind speed, and humidity, with animated visual effects for sun, rain, and clouds.

🌤️ Features

Dynamic color themes based on weather (sunny, cloudy, rainy).
Animated weather effects: floating clouds, falling rain, glowing sun.
Responsive design for all screen sizes.
Lightweight and easy to integrate with any weather API.

🧾 Code Example

<!DOCTYPE html>
<html lang="en">
<head>
  <meta charset="UTF-8" />
  <meta name="viewport" content="width=device-width, initial-scale=1.0"/>
  <title>Animated Weather Card</title>
  <link href="https://fonts.googleapis.com/css2?family=Inter:wght@400;600;700&display=swap" rel="stylesheet">
  <style>
    :root {
      --sun-color: #FFD700;
      --cloud-color: #E0E0E0;
      --rain-color: #A0C4FF;
      --bg-gradient-sunny: linear-gradient(135deg, #FFE082, #FFA726);
      --bg-gradient-rainy: linear-gradient(135deg, #A5D8FF, #7AA9E5);
      --bg-gradient-cloudy: linear-gradient(135deg, #B0BEC5, #90A4AE);
    }

    * {
      margin: 0;
      padding: 0;
      box-sizing: border-box;
    }

    body {
      font-family: 'Inter', sans-serif;
      background: #f0f2f5;
      display: flex;
      justify-content: center;
      align-items: center;
      height: 100vh;
    }

    .weather-card {
      background: var(--bg-gradient-sunny);
      border-radius: 20px;
      padding: 2rem;
      width: 300px;
      box-shadow: 0 10px 30px rgba(0,0,0,0.1);
      position: relative;
      overflow: hidden;
      transition: background 0.5s ease;
    }

    .weather-card.sunny {
      background: var(--bg-gradient-sunny);
    }

    .weather-card.rainy {
      background: var(--bg-gradient-rainy);
    }

    .weather-card.cloudy {
      background: var(--bg-gradient-cloudy);
    }

    .location {
      font-size: 1.5rem;
      font-weight: 700;
      text-align: center;
      color: #fff;
    }

    .temperature {
      font-size: 3rem;
      font-weight: 700;
      text-align: center;
      color: #fff;
      margin: 0.5rem 0;
    }

    .condition {
      font-size: 1.25rem;
      text-align: center;
      color: #fff;
      margin-bottom: 1rem;
    }

    .weather-icon {
      display: flex;
      justify-content: center;
      align-items: center;
      margin: 1rem 0;
    }

    .sun {
      width: 60px;
      height: 60px;
      background: var(--sun-color);
      border-radius: 50%;
      position: relative;
      animation: spin 10s linear infinite;
    }

    .sun::before {
      content: '';
      position: absolute;
      top: -10px;
      left: 50%;
      transform: translateX(-50%);
      width: 4px;
      height: 20px;
      background: var(--sun-color);
      animation: glow 1.5s ease-in-out infinite alternate;
    }

    @keyframes spin {
      0% { transform: rotate(0deg); }
      100% { transform: rotate(360deg); }
    }

    @keyframes glow {
      from { opacity: 0.8; }
      to { opacity: 1; }
    }

    .cloud {
      position: relative;
      width: 80px;
      height: 40px;
      background: var(--cloud-color);
      border-radius: 50%;
      margin: 10px 0;
      animation: floatCloud 10s ease-in-out infinite;
    }

    .cloud::after {
      content: '';
      position: absolute;
      top: -10px;
      left: 20px;
      width: 50px;
      height: 30px;
      background: var(--cloud-color);
      border-radius: 50%;
    }

    @keyframes floatCloud {
      0%, 100% { transform: translateX(0); }
      50% { transform: translateX(10px); }
    }

    .rain {
      position: relative;
      width: 80px;
      height: 60px;
      margin: 10px 0;
    }

    .rain::before {
      content: '';
      position: absolute;
      width: 4px;
      height: 20px;
      background: var(--rain-color);
      top: 0;
      left: 20px;
      animation: fall 1s linear infinite;
    }

    .rain::after {
      content: '';
      position: absolute;
      width: 4px;
      height: 20px;
      background: var(--rain-color);
      top: 0;
      left: 50px;
      animation: fall 1.2s linear infinite;
    }

    @keyframes fall {
      0% { transform: translateY(0) rotate(20deg); }
      100% { transform: translateY(60px) rotate(20deg); }
    }

    .details {
      background: rgba(255,255,255,0.1);
      backdrop-filter: blur(5px);
      border-radius: 12px;
      padding: 1rem;
      margin-top: 1rem;
    }

    .detail-row {
      display: flex;
      justify-content: space-between;
      padding: 0.5rem 0;
      border-bottom: 1px solid rgba(255,255,255,0.2);
    }

    .detail-row:last-child {
      border-bottom: none;
    }

    .label, .value {
      color: #fff;
    }

    .refresh-btn {
      margin-top: 1rem;
      display: block;
      width: 100%;
      text-align: center;
      color: #fff;
      cursor: pointer;
      font-weight: 600;
      animation: pulse 2s infinite;
    }

    @keyframes pulse {
      0%, 100% { opacity: 1; }
      50% { opacity: 0.6; }
    }
  </style>
</head>
<body>

  <div class="weather-card sunny" id="weatherCard">
    <div class="location">New York</div>
    <div class="temperature" id="temp">25°C</div>
    <div class="condition" id="condition">Sunny</div>
    
    <div class="weather-icon" id="iconContainer">
      <div class="sun"></div>
    </div>

    <div class="details">
      <div class="detail-row">
        <span class="label">Wind</span>
        <span class="value" id="wind">15 km/h</span>
      </div>
      <div class="detail-row">
        <span class="label">Humidity</span>
        <span class="value" id="humidity">60%</span>
      </div>
      <div class="detail-row">
        <span class="label">UV Index</span>
        <span class="value" id="uv">5</span>
      </div>
    </div>

    <div class="refresh-btn" onclick="updateWeather()">🔄 Refresh</div>
  </div>

  <script>
    const weatherData = {
      sunny: {
        temp: "25°C",
        condition: "Sunny",
        wind: "15 km/h",
        humidity: "60%",
        uv: "5",
        icon: "sun"
      },
      rainy: {
        temp: "18°C",
        condition: "Rainy",
        wind: "20 km/h",
        humidity: "85%",
        uv: "2",
        icon: "rain"
      },
      cloudy: {
        temp: "20°C",
        condition: "Cloudy",
        wind: "10 km/h",
        humidity: "70%",
        uv: "3",
        icon: "cloud"
      }
    };

    function setIcon(iconType) {
      const container = document.getElementById("iconContainer");
      container.innerHTML = "";
      if (iconType === "sun") {
        container.innerHTML = '<div class="sun"></div>';
      } else if (iconType === "rain") {
        container.innerHTML = '<div class="rain"></div>';
      } else if (iconType === "cloud") {
        container.innerHTML = '<div class="cloud"></div>';
      }
    }

    function updateWeather() {
      const keys = Object.keys(weatherData);
      const randomKey = keys[Math.floor(Math.random() * keys.length)];
      const data = weatherData[randomKey];

      document.getElementById("temp").textContent = data.temp;
      document.getElementById("condition").textContent = data.condition;
      document.getElementById("wind").textContent = data.wind;
      document.getElementById("humidity").textContent = data.humidity;
      document.getElementById("uv").textContent = data.uv;

      setIcon(data.icon);

      const card = document.getElementById("weatherCard");
      card.className = 'weather-card ' + randomKey;
    }
  </script>

</body>
</html>

🧪 How It Works

Dynamic Weather Types:
- Sunny (uses glowing spinning sun).
- Rainy (animated falling raindrops).
- Cloudy (floating cloud).
Animations:
- Sun spins slowly.
- Clouds float side to side.
- Raindrops fall with staggered timing.
Theming:
- Background gradient changes based on weather type.
- Color variables make it easy to customize.
JavaScript:
- Simulates weather data updates.
- Randomly selects a weather type and updates the UI.
- Can be extended to fetch real data from an API like OpenWeatherMap.

🌐 Integration with OpenWeatherMap API (Optional)

To get real-time data:

async function fetchWeather() {
  const API_KEY = "YOUR_API_KEY";
  const CITY = "London";
  const URL = `https://api.openweathermap.org/data/2.5/weather?q=${CITY}&appid=${API_KEY}&units=metric`;

  try {
    const res = await fetch(URL);
    const data = await res.json();

    const weather = data.weather[0].main.toLowerCase();
    const temp = `${Math.round(data.main.temp)}°C`;
    const wind = `${Math.round(data.wind.speed * 3.6)} km/h`; // m/s to km/h
    const humidity = `${data.main.humidity}%`;
    const uv = "N/A"; // You can fetch UV index from another endpoint if needed

    document.getElementById("temp").textContent = temp;
    document.getElementById("condition").textContent = data.weather[0].description;
    document.getElementById("wind").textContent = wind;
    document.getElementById("humidity").textContent = humidity;

    // Set icon and theme based on condition
    let iconType = "cloud";
    if (weather.includes("rain")) iconType = "rain";
    else if (weather.includes("clear")) iconType = "sun";

    setIcon(iconType);
    document.getElementById("weatherCard").className = 'weather-card ' + iconType;
  } catch (error) {
    console.error("Error fetching weather data", error);
  }
}

✅ Summary

This animated weather card is a vibrant, interactive way to display weather conditions. It's styled with modern CSS, includes dynamic theming, and uses simple animations for visual appeal. It's ready for integration with real-time data or can be used as a static UI component.

Let me know if you'd like:

A React version
Integration with TailwindCSS
Support for dark/light mode
More weather types like snow, thunderstorm, etc.

This design features dynamic themes: for "sunny" it uses a yellow sun icon and a warm gradient; for rain it would switch to a blue gradient with falling drops (via CSS keyframes); for cloudy, a gray palette. It even specified animated raindrops and a pulsing sun. The card shows temperature prominently with FontAwesome icons and uses subtle shadows. The HTML structure is straightforward with header and info sections.

DeepSeek R1's Solution:

DeepSeek R1 also output a single HTML page with CSS and some JS. Its style is a neon-like gradient background with soft "neumorphic" shadows. For brevity, key parts:

Here's a colorful animated weather card using HTML, CSS, and JavaScript with dummy weather data:

<!DOCTYPE html>
<html lang="en">
<head>
    <meta charset="UTF-8">
    <meta name="viewport" content="width=device-width, initial-scale=1.0">
    <title>Animated Weather Card</title>
    <link href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/6.0.0/css/all.min.css" rel="stylesheet">
    <style>
        body {
            display: flex;
            justify-content: center;
            align-items: center;
            min-height: 100vh;
            background: #e0e5ec;
            margin: 0;
            font-family: 'Arial', sans-serif;
        }

        .weather-card {
            background: linear-gradient(135deg, #ff6b6b, #4ecdc4);
            border-radius: 20px;
            padding: 2rem;
            color: white;
            width: 300px;
            position: relative;
            overflow: hidden;
            box-shadow: 20px 20px 60px #bebebe,
                       -20px -20px 60px #ffffff;
            animation: float 3s ease-in-out infinite;
        }

        .weather-header {
            display: flex;
            justify-content: space-between;
            align-items: center;
            margin-bottom: 1.5rem;
        }

        .temperature {
            font-size: 3.5rem;
            font-weight: bold;
        }

        .weather-icon {
            font-size: 3rem;
            animation: pulse 2s infinite;
        }

        .weather-info {
            display: flex;
            justify-content: space-between;
            margin-bottom: 1rem;
        }

        .weather-details div {
            margin: 0.5rem 0;
            display: flex;
            align-items: center;
        }

        .weather-details i {
            margin-right: 0.8rem;
            font-size: 1.2rem;
        }

        @keyframes float {
            0%, 100% { transform: translateY(0); }
            50% { transform: translateY(-10px); }
        }

        @keyframes pulse {
            0%, 100% { transform: scale(1); }
            50% { transform: scale(1.1); }
        }

        .breeze {
            position: absolute;
            top: -50%;
            left: -50%;
            width: 200%;
            height: 200%;
            background: linear-gradient(45deg, transparent 30%, rgba(255,255,255,0.1) 50%, transparent 70%);
            animation: breeze 8s infinite linear;
        }

        @keyframes breeze {
            0% { transform: translateX(-50%) translateY(-50%) rotate(45deg); }
            100% { transform: translateX(50%) translateY(50%) rotate(45deg); }
        }
    </style>
</head>
<body>
    <div class="weather-card">
        <div class="breeze"></div>
        <div class="weather-header">
            <div>
                <h2>New York</h2>
                <p>Partly Cloudy</p>
            </div>
            <i class="fas fa-sun weather-icon"></i>
        </div>
        
        <div class="temperature">24°C</div>
        
        <div class="weather-details">
            <div>
                <i class="fas fa-wind"></i>
                Wind: 12 km/h
            </div>
            <div>
                <i class="fas fa-tint"></i>
                Humidity: 65%
            </div>
            <div>
                <i class="fas fa-thermometer-half"></i>
                Feels like: 26°C
            </div>
        </div>
    </div>

    <script>
        // Dummy weather data - replace with real API data
        const weatherData = {
            temp: 24,
            condition: 'Sunny',
            wind: 12,
            humidity: 65,
            feelsLike: 26,
            icon: 'fa-sun'
        };

        // Update weather card with data
        document.querySelector('.temperature').textContent = `${weatherData.temp}°C`;
        document.querySelector('.weather-icon').className = `fas ${weatherData.icon} weather-icon`;
        document.querySelector('p').textContent = weatherData.condition;
        document.querySelectorAll('.weather-details div')[0].textContent = `Wind: ${weatherData.wind} km/h`;
        document.querySelectorAll('.weather-details div')[1].textContent = `Humidity: ${weatherData.humidity}%`;
        document.querySelectorAll('.weather-details div')[2].textContent = `Feels like: ${weatherData.feelsLike}°C`;
    </script>
</body>
</html>

This code creates an animated weather card with:

A gradient background with floating animation
Smooth hover effects
Animated weather icon
Moving breeze effect in the background
Clean layout with temperature display
Detailed weather information including wind speed and humidity
Responsive design
Font Awesome icons for visual elements

Key features:

Floating animation on the card
Pulsing animation on the weather icon
Continuous breeze effect using gradient animation
Glass-morphism effect using subtle shadows
Responsive layout that works on different screen sizes
Easy-to-read typography with clear hierarchy

To make it functional with real data, you would need to:

Replace the dummy weatherData object with real API data from services like:
- OpenWeatherMap
- WeatherAPI
- AccuWeather
Add error handling
Implement auto-refresh functionality
Add geolocation detection

The card can be customized by:

Changing the gradient colors
Adjusting animations timing
Adding more weather parameters
Modifying the layout
Changing the font
Adjusting the sizing and spacing

DeepSeek's card has a purple-pink gradient background and white text/icons. The layout is similar: big temperature, an icon (cloud/sun), and details. It uses subtle animations (floating card, pulsing icon). Unlike Qwen's, it doesn't define multiple weather themes; it seems to hard-code one theme. The style is modern and "smooth."

Analysis:

Both weather cards look professional. Qwen 3's version is more complete in dynamic theming (different gradients for sunny/rainy/cloudy and animated effects for each). DeepSeek R1's is visually polished with a pleasing gradient and nice shadows. From a features standpoint, Qwen 3's answer is richer (it described multiple weather conditions and had CSS for rain animation), whereas DeepSeek's is simpler and more stylized.

Verdict:

DeepSeek R1 takes the slight edge. Its design is visually striking and the code is clean. Qwen 3's card is comprehensive and functional, but we felt DeepSeek R1's animation and style (gradient, neumorphism) gave it a more professional flair. That said, this was a close call – both models delivered strong weather widgets.

Comparison Table

Task	Qwen 3 Approach	DeepSeek R1 Approach	Verdict
Web Scraper	Asyncio/aiohttp with Semaphore for concurrency, regex title parsing, simple error logging.	Asyncio/aiohttp with retries, BeautifulSoup parsing, robust DB functions.	DeepSeek R1 wins (more robust).
Topological Sort	DFS-based algorithm with visited/visiting states, returns empty on cycle.	Kahn's algorithm (queue of zero-indegree nodes), raises exception on cycle.	DeepSeek R1 wins (efficient and clear).
SaaS Landing Page	Static HTML/CSS design (dark theme), manual styling for hero/nav/pricing.	HTML with Tailwind CSS (responsive layout via utility classes).	Qwen 3 wins (self-contained design).
Rainbow SVG Bird	Multiple linear gradients (left/right wing, body, tail) in distinct rainbow bands.	Single continuous rainbow gradient.	Qwen 3 wins (brighter rainbow effect).
Weather Card	HTML/CSS with theme variables and icon animations (sun, rain, etc.).	HTML/CSS with gradient and soft shadows, plus minor animations.	DeepSeek R1 wins (sleek style).

AI Code Review: The New Vibe in Coding

AI is not only writing code but also reviewing it. The notion of "vibe coding" – of flying by the seat of your pants with AI – underscores a shift in developer culture. Andrej Karpathy famously coined the term to mean treating the AI-generated code as a black box ("I don't read the diffs anymore"), primarily useful for quick prototypes. While fun for throwaway projects, this carefree style can introduce subtle bugs if unchecked. In contrast, many developers advocate a balanced approach: use AI to propose code, but always verify and integrate carefully (Simon Willison argues that responsible AI-assisted coding still requires human review).

At the same time, luminaries have proclaimed that "the hottest new programming language is English". NVIDIA's CEO Jensen Huang envisions a future where "the programming language is human," meaning we simply tell the computer what we want in English and it does it. This reflects a broader trend: LLM-powered tools like GitHub Copilot already let developers describe a function in natural language and receive working code. The implication is that even non-programmers might soon automate tasks by speaking, lowering the barrier to software creation.

Enter the AI-assisted code reviews, where LLMs scan real code repositories. Entelligence.ai is innovating here: we use intelligent agents to analyze pull requests and comment on code quality. In their own tests, Entelligence.ai reported that DeepSeek R1 "caught 3.7× as many bugs" as Anthropic's Claude 3.5 Sonnet when reviewing code (DeepSeek R1 found ~13.7% more critical bugs). This suggests that these new LLMs can enhance engineering productivity by surfacing hidden issues early.

You can also read: How to Build Code Review Agent Using Qwen 3?

These developments – from vibe coding to English-as-code – point to a reimagining of software engineering. We're entering an era where AI can pair-program, auto-generate documentation, and review pull requests. For startups and developers, this means tools must focus on alignment and safety: an AI that writes vast amounts of code quickly is only useful if the code is correct and maintainable. The innovation shown by Entelligence.ai and the models evaluated above is a harbinger of a new workflow: one where human intent expressed in plain language is refined and checked by AI.

Conclusion

Both DeepSeek R1 and Qwen 3 demonstrate how far open-source LLMs have come in coding tasks. DeepSeek R1's strength lies in its reasoning-focused training – it gave us robust, well-structured solutions for the scraper, topological sort, and an elegant weather widget. Qwen 3's strength is in raw coding fluency – it produced a stunning landing page and the brightest rainbow SVG. Overall, neither model is uniformly better; each excels in different domains. Our small test suggests DeepSeek R1 has an edge on logic-intensive or back-end tasks, while Qwen 3 shines on front-end and stylized outputs.

Looking ahead, we expect Qwen 3's future iterations (and similar models) to continue raising the bar on code generation, as hinted by reports of it "outperforming top players". DeepSeek's RL-driven approach may yield more powerful reasoning and self-correction over time. For developers and AI startups, the practical takeaway is that using these models can accelerate development – but success will require careful human oversight (as Huang remarked, "no one has to learn to program" in the AI era, but the responsibility shifts to specifying and validating requirements).

There is no single "best" model yet; DeepSeek R1 and Qwen 3 are complementary tools in the AI coder's toolbox. The real win for developers is having a rich ecosystem of AI models that can suggest code, review it for bugs, and even translate English specs into programs. As AI continues to improve, the practical implication is that software teams will increasingly become prompt engineers: defining problems in human language and curating AI outputs – essentially coding by conversation. This "vibe" of English-language programming is the new frontier, and these models show both the promise and pitfalls of that future.

Entelligence

DeepSeek R1 vs Qwen 3: Coding Task Showdown

Overview of the Models

Benchmark Coding Tasks

Task 1: Asynchronous Web Scraper

Qwen 3's Solution:

✅ Features Implemented

📁 Project Structure

🧠 Key Concepts Used

🧾 Full Code (scraper.py)

🛠️ How It Works

📦 Requirements

🧪 Example Output

📚 Notes

📌 Summary

DeepSeek R1's Solution:

Key features of this implementation:

To use this scraper:

Analysis:

Verdict:

Task 2: Topological Sort (Task Ordering)

Qwen 3's Solution:

✅ Key Features

🧠 Understanding the Approach

🧾 Code Implementation

📌 Example Usage

🧪 Notes

📚 Summary

DeepSeek R1's Solution:

Key features of this implementation:

Analysis:

Verdict:

Task 3: SaaS Landing Page (AI Code Review Company)

Qwen 3's Solution:

✅ Key Features

🌐 Full Code (HTML + CSS + JS)

🎨 Design Highlights

📱 Mobile Preview

🧩 Extendability

✅ Final Notes

DeepSeek R1's Solution:

Analysis:

Verdict:

Task 4: Rainbow SVG Bird

Qwen 3's Solution:

🌈 Key Features

✅ SVG Code

🧠 How It Works

🛠️ How to Customize

📦 Embedding in HTML

🧪 Preview

✅ Summary

DeepSeek R1's Solution:

Analysis:

Verdict:

Task 5: Animated Weather Card

Qwen 3's Solution:

🌤️ Features

🧾 Code Example

🧪 How It Works

🌐 Integration with OpenWeatherMap API (Optional)

✅ Summary

DeepSeek R1's Solution:

Analysis:

Verdict:

Comparison Table

AI Code Review: The New Vibe in Coding

Conclusion

🧾 Full Code (`scraper.py`)