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VSCode AI Showdown: Which Coding Assistant Will Supercharge Your Development?

Tired of switching between AI coding assistants? I put Gemini 2.5 Pro, GPT-4.1, and Claude 3.7 Sonnet to the test in VSCode. Discover which AI agent will transform your coding workflow and why developers are raving about these game-changing tools.

Posted Apr 24, 2025
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By Sergii Grytsaienko
12 min read

Choosing Your VSCode AI Agent: Which One Fits Your Development Style?

The world of artificial intelligence is constantly evolving, with large language models (LLMs) at the forefront of this transformation. These powerful tools are reshaping industries and revolutionizing how we interact with technology. Among the most advanced and widely discussed LLMs are Google’s Gemini 2.5 Pro, OpenAI’s GPT-4.1, and Anthropic’s Claude 3.7 Sonnet. Choosing the right model for your specific needs can be challenging, which is why I’ve compiled this comprehensive comparison to help you understand their strengths, weaknesses, and unique capabilities. 1

VSCode Integration and Developer Experience

These models represent the latest generation of AI coding assistants available in Visual Studio Code, each bringing unique capabilities to the development workflow:

  • Gemini 2.5 Pro in VSCode:

    • Deep integration with Google’s development ecosystem
    • Advanced code completion and generation
    • Real-time code analysis and optimization suggestions
    • Seamless debugging assistance
    • Native support for multiple programming languages and frameworks

  • GPT-4.1 in VSCode:

    • Enhanced code understanding and generation
    • Improved context awareness for large codebases
    • Advanced refactoring suggestions
    • Better handling of complex code patterns
    • Optimized for API development and integration

  • Claude 3.7 Sonnet in VSCode:

    • Superior code explanation and documentation
    • Advanced debugging capabilities with “Thinking Mode”
    • Enhanced code review and quality assurance
    • Better handling of legacy code and technical debt
    • Strong focus on code maintainability and best practices

These AI agents are designed to work seamlessly within VSCode, providing real-time assistance, code suggestions, and intelligent debugging capabilities. They can understand your codebase context, suggest improvements, and help maintain code quality while you work.

Performance Analysis

Coding Capabilities

For developers, coding performance is a critical factor in choosing an LLM. Our analysis reveals:

  • Gemini 2.5 Pro: Consistently scores high on coding benchmarks like SWE-bench Verified, typically achieving 63-64% accuracy. Demonstrates exceptional ability to generate complex, functional code in a single attempt, including sophisticated applications like flight simulators and Rubik’s Cube solvers. 2 Beyond benchmarks, practical tests further highlight these differences. Gemini 2.5 Pro has shown impressive results in generating functional code for complex tasks like a flight simulator and a Rubik’s Cube solver in a single attempt. 2

  • Claude 3.7 Sonnet: Performs strongly with scores between 62-70% on SWE-bench, with potential for even better results through specific optimizations. Features a unique “Thinking Mode” that enhances debugging capabilities. 2 While Claude 3.7 Sonnet performed well in some creative coding tasks, it struggled with these specific tests. 2

  • GPT-4.1: While slightly trailing in raw benchmark scores (52-55%), excels in frontend development and code review tasks. Known for reliable adherence to specific formats and clean code generation. 2 GPT-4.1 is known for its focus on frontend coding and reliable adherence to specific formats, making it a strong choice for web development. 2

Reasoning and Knowledge

Reasoning and general knowledge are crucial for a wide range of applications:

  • Gemini 2.5 Pro: Leads in general reasoning benchmarks, with particularly strong performance in mathematical and scientific domains (GPQA and AIME benchmarks). 1 Consistently demonstrates top-tier performance in reasoning benchmarks, often leading by a significant margin. 1

  • Claude 3.7 Sonnet: Excels in extended reasoning scenarios, with its “extended thinking” mode enabling in-depth analysis of complex problems. 1 Recognized for its robust reasoning capabilities, especially in extended reasoning scenarios where its “extended thinking” mode allows for in-depth analysis. 1

  • GPT-4.1: Focuses on improved instruction following, though accuracy may decrease with extremely large inputs. 1 OpenAI emphasizes GPT-4.1’s improved ability to follow instructions, although its accuracy might decrease with extremely large inputs. 1

Benchmarks like LMArena, which reflect human preferences, often favor Gemini 2.5 Pro for its output quality and style. High scores on benchmarks like GPQA and AIME indicate advanced proficiency in mathematical and scientific domains for Gemini. Claude’s “extended thinking” mode likely contributes to its strength in complex reasoning, while GPT-4.1’s improved instruction following makes it suitable for tasks requiring precise adherence to guidelines.

Multimodal Understanding

In today’s data-rich environment, the ability to process various types of information is increasingly important:

  • Gemini 2.5 Pro: Takes the lead with native multimodality, seamlessly processing text, images, audio, and video. Top performance on MMMU benchmark. 1, 4 Its top performance on the MMMU benchmark underscores this strength. 4

  • GPT-4.1: Supports text and image processing. 1 Also offers multimodal input capabilities, likely supporting text and image processing. 1

  • Claude 3.7 Sonnet: Currently limited to text and image inputs. 1 Claude 3.7 Sonnet’s multimodal support is currently limited to text and image inputs. 1

Technical Specifications

Training Data and Architecture

Understanding the technical aspects of these models provides valuable context:

  • Gemini 2.5 Pro:

    • Training Data: Vast dataset including text, audio, images, video, and code 5
    • Architecture: “Thinking model” with 1M token context window (2M in testing) 5
    • Is a “thinking model” with a 1 million token context window (expanding to 2 million). 5

  • GPT-4.1:

    • Training Data: Knowledge cutoff June 2024 6
    • Architecture: API-focused series with up to 1M token context windows 1
    • Is part of a new API-focused series with up to 1 million token context windows. 1

  • Claude 3.7 Sonnet:

    • Training Data: Knowledge cutoff April 2024 6
    • Architecture: First hybrid reasoning model with 200K token context window (500K testing) 1
    • Is the first hybrid reasoning model with a 200,000 token context window (testing 500,000). 1

The larger context windows of Gemini 2.5 Pro and GPT-4.1 offer an advantage for processing extensive data. Claude’s hybrid reasoning architecture provides a unique approach to problem-solving.

Speed and Efficiency

Efficiency is crucial for practical applications:

  • Gemini 2.5 Pro: While powerful, generalist models are faster for everyday tasks. Game generation noted to be particularly rapid. 4 While powerful, generalist Gemini models are faster for everyday tasks. Game generation was noted to be rapid. 4

  • GPT-4.1: Family includes models optimized for speed and cost, with GPT-4.1 nano being the fastest and most cost-effective. 11 The GPT-4.1 family includes models optimized for speed and cost, with GPT-4.1 nano being the fastest and cheapest. 11

  • Claude 3.7 Sonnet: Slower output speed but faster initial response time. 19 Has a slower output speed but a faster initial response time. 19

The GPT-4.1 family offers the most diverse options for speed and cost optimization.

Pricing and Availability

Accessibility and cost are key considerations:

  • Gemini 2.5 Pro: Currently free in experimental phase through Google AI Studio and Gemini Advanced subscription. 2 Currently free in its experimental phase through Google AI Studio and the Gemini Advanced subscription. 2

  • GPT-4.1: API-only with tiered pricing (nano, mini, standard). Reported to be more cost-effective than previous models. 1, 12 Available exclusively through the API, with different pricing tiers for nano, mini, and the standard model. 1 GPT-4.1 is reported to be more cost-effective than previous models. 12

  • Claude 3.7 Sonnet: Available through Claude.ai and APIs, with higher pricing structure compared to GPT-4.1. 6 Accessible through various platforms, including Claude.ai and APIs, with a higher pricing structure compared to GPT-4.1. 6

GPT-4.1 offers the most varied pricing options, while Gemini 2.5 Pro is currently free for experimentation.

Unique Features

Each model brings unique functionalities:

  • Gemini 2.5 Pro: Native multimodality and deep integration with the Google ecosystem. 1 Native multimodality and deep integration with the Google ecosystem. 1

  • GPT-4.1: Strong focus on coding reliability and different API model sizes. 1 Strong focus on coding reliability and different API model sizes. 1

  • Claude 3.7 Sonnet: “Thinking Mode” for transparent reasoning and a strong focus on safety and natural writing. 1 “Thinking Mode” for transparent reasoning and a strong focus on safety and natural writing. 1

Real-World Applications

User reviews and expert opinions offer practical perspectives:

  • Gemini 2.5 Pro: Praised for coding, reasoning, and handling complex ML models. Users note its contextual awareness and human-like reasoning but also potential verbosity and hallucinations. 4 Praised for coding, reasoning, and handling complex ML models. Users note its contextual awareness and human-like reasoning but also potential verbosity and hallucinations. 4

  • GPT-4.1: Generally positive for development tasks and long datasets, with cleaner code generation and improved instruction following. The mini version is valued for its cost-effectiveness. API-only availability is a limitation for some. 9 Generally positive for development tasks and long datasets, with cleaner code generation and improved instruction following. The mini version is valued for its cost-effectiveness. API-only availability is a limitation for some. 9

  • Claude 3.7 Sonnet: Highly regarded for coding, especially frontend development, and for producing nuanced answers requiring less editing. Users appreciate its ability to grasp abstract concepts and the “Thinking Mode.” Some note potential verbosity and higher pricing. 2 Highly regarded for coding, especially frontend development, and for producing nuanced answers requiring less editing. Users appreciate its ability to grasp abstract concepts and the “Thinking Mode.” Some note potential verbosity and higher pricing. 2

Handling Long Content and Complex Instructions

The ability to manage large amounts of information is critical:

  • Gemini 2.5 Pro: Boasts a 1 million token context window (2 million in testing) and can effectively process lengthy documents. 1 Boasts a 1 million token context window (2 million in testing) and can effectively process lengthy documents. 1

  • GPT-4.1: Features a 1 million token context window and is trained to reliably attend to information throughout. 1 Features a 1 million token context window and is trained to reliably attend to information throughout. 1

  • Claude 3.7 Sonnet: Has a 200,000 token context window (500,000 in testing) and is praised for handling complex codebases. 1 Has a 200,000 token context window (500,000 in testing) and is praised for handling complex codebases. 1

Gemini 2.5 Pro and GPT-4.1 offer a significant advantage for processing very long content due to their larger context windows.

Key Takeaways

  • Gemini 2.5 Pro leads in multimodal capabilities and coding performance
  • GPT-4.1 offers the most cost-effective options with its nano and mini variants
  • Claude 3.7 Sonnet excels in extended reasoning and natural language generation
  • Each model has unique strengths for different use cases
  • Context window sizes vary significantly between models
  • Pricing structures differ based on usage patterns and requirements

Works Cited

  1. AI Showdown 2025: GPT-4.1 vs. Claude 3.7 Sonnet vs. Gemini 2.5 Pro - MindPal, accessed April 24, 2025
  2. GPT-4.1 Comparison with Claude 3.7 Sonnet and Gemini 2.5 Pro - Bind AI, accessed April 24, 2025
  3. Gemini 2.5 Pro vs. Claude 3.7 Sonnet: Coding Comparison - Composio, accessed April 24, 2025
  4. Gemini 2.5 Pro: Features, Tests, Access, Benchmarks & More - DataCamp, accessed April 24, 2025
  5. Gemini 2.5: Our newest Gemini model with thinking - Google Blog, accessed April 24, 2025
  6. GPT-4.1 vs Claude 3.7 Sonnet - Detailed Performance & Feature Comparison - DocsBot, accessed April 24, 2025
  7. Claude 3.7 Sonnet vs Gemini 2.5 Pro - Detailed Performance & Feature Comparison - DocsBot, accessed April 24, 2025
  8. Claude 3.7 Sonnet and Claude Code - Anthropic, accessed April 24, 2025
  9. Introducing GPT-4.1 in the API - OpenAI, accessed April 24, 2025
  10. Evaluating the new Gemini 2.5 Pro Experimental model - Weights & Biases, accessed April 24, 2025
  11. GPT-4.1: How AI is Changing the Way Programmers Work - Dirox, accessed April 24, 2025
  12. All About OpenAI’s GPT‑4.1 Models: How to Access, Uses & More - Analytics Vidhya, accessed April 24, 2025
  13. Gemini Pro 2.5 is a stunningly capable coding assistant - ZDNet, accessed April 24, 2025
  14. We benchmarked GPT-4.1: it’s better at code reviews than Claude Sonnet 3.7 - Reddit, accessed April 24, 2025
  15. We benchmarked GPT-4.1: it’s better at code reviews than Claude Sonnet 3.7 - Reddit, accessed April 24, 2025
  16. Gemini 2.5 vs Sonnet 3.7 vs Grok 3 vs GPT-4.1 vs GPT-o3 - Cursor Community Forum, accessed April 24, 2025
  17. Claude Sonnet 3.7 is INSANELY GOOD - Reddit, accessed April 24, 2025
  18. GPT-4.1 is GREAT at Coding… (and long context!) - YouTube, accessed April 24, 2025
  19. Claude 3.7 Sonnet - Intelligence, Performance & Price Analysis - Artificial Analysis, accessed April 24, 2025
  20. GPT-4.1 is here, but not for everyone - ZDNet, accessed April 24, 2025
  21. Gemini 2.5 Pro is another game changing moment - Reddit, accessed April 24, 2025
  22. I tried using the Deep Research feature with Google’s Gemini 2.5 Pro model - TechRadar, accessed April 24, 2025
  23. Gemini 2.5 Pro reasons about task feasibility - Hacker News, accessed April 24, 2025
  24. Man, the new Gemini 2.5 Pro 03-25 is a breakthrough - Reddit, accessed April 24, 2025
  25. Google Gemini 2.5 Pro is Insane… - YouTube, accessed April 24, 2025
  26. I just spent a week testing GPT-4.1 (all versions) - Reddit, accessed April 24, 2025
  27. Just started using GPT-4.1 — curious what you think - Cursor Forum, accessed April 24, 2025
  28. GPT-4.1 in the API - Hacker News, accessed April 24, 2025
  29. OpenAI’s GPT 4.1 - Absolutely Amazing! - YouTube, accessed April 24, 2025
  30. Just tried Claude 3.7 Sonnet, WHAT THE ACTUAL FUCK IS THIS BEAST? - Reddit, accessed April 24, 2025
  31. Claude 3.7 Sonnet: The BEST Coding LLM Ever! (Fully Tested) - YouTube, accessed April 24, 2025
  32. Actually coding with Claude 3.7 is actually insane, actually. - YouTube, accessed April 24, 2025
  33. Claude Sonnet 3.7 is.. kinda bad? - YouTube, accessed April 24, 2025
Artificial Intelligence, AI Models, Technology, Development Tools
Gemini 2.5 Pro GPT-4.1 Claude 3.7 Sonnet AI Comparison VSCode Extensions Code Assistants Developer Tools
This post is licensed under CC BY 4.0 by the author.
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