Design your workflow
Start with the task. Build from there.Best AI for coding: choose by your development workflow
28 directory models
Choose between an editor assistant, a coding agent and a chat assistant, with a practical test for your own codebase.
By WAMIB editorial · Sources checked · Based on documentation
Start with your actual task.
Check the fit and limitations.
Evaluate on your own work.
The short answer
Start with GitHub Copilot if you want help inside an existing GitHub development workflow. Consider Claude Code for delegated coding work, or a chat assistant for explanations and small examples. Our recommendation is based on workflow fit; we have not run a comparative coding benchmark.
Compare your options
| Tool | Consider it for | Check before choosing |
|---|---|---|
| GitHub CopilotOfficial source | Inline assistance, code questions and repository tasks in a GitHub workflow. | Available functions depend on your client, plan and organisation settings. |
| Claude CodeOfficial source | A candidate for developers who want to delegate coding tasks; Claude lists it in Pro. | Check usage limits and the tools you need before subscribing. |
| ChatGPTOfficial source | Explain an error, discuss an approach or work through a small code example in chat. | A plausible explanation is not evidence that the resulting code passes your tests. |
These are workflow recommendations, not measured performance rankings. Product features, limits and prices can change; follow the official sources for current terms.
What should you test before paying?
Take one real bug, one small feature and one unfamiliar function from a repository you can share. Give each candidate the same instructions and acceptance criteria. Record whether the tests pass, how much code you must rewrite, and the time spent reviewing. A tool that produces a longer patch is not necessarily saving you time.
Which option is best on a budget?
Begin with a free tier or an existing subscription on small tasks. Only pay when a limit repeatedly interrupts useful work. Include review time and failed attempts in the cost: a cheap generation that needs an hour of repair can be worse value than a more expensive successful one.
When should you choose a model API?
Use an API when you are building AI into your own software and need control over requests and outputs. A coding assistant subscription and an API model are different purchases. The model directory below contains versioned records; confirm current availability with the provider before building around one.
Common questions
Can AI-generated code go straight into production?
Treat it as a proposed change. Review it, run the project’s tests and check dependencies and access to data before deployment.
Versioned directory records, newest known release dates first. Includes historical models; verify availability and pricing with the provider.
Model directory for Code Generation
Claude Haiku 4.5
by AnthropicClaude Haiku 4.5 is Anthropic's latest small AI model, launched on October 15, 2025. It offers similar coding performance to the previous state-of-the-art model, Claude Sonnet 4, but at one-third the cost and more than twice the speed. This model excels in real-time, low-latency tasks, making it particularly beneficial for applications like chat assistants and customer service agents. Claude Haiku 4.5 also enhances the coding experience, providing a responsive environment for multiple-agent projects and rapid prototyping, while maintaining high intelligence and speed.
Claude Opus 4.5
by AnthropicClaude Opus 4.5 is Anthropic's latest AI model, launched on November 24, 2025. It is designed to be intelligent and efficient, excelling in coding, agents, and computer use. The model significantly improves performance in everyday tasks such as deep research and working with slides and spreadsheets. It is state-of-the-art in real-world software engineering tests and is available on various platforms, including apps, API, and major cloud services.
GPT-5.2
by OpenAIGPT-5.2 is OpenAI's flagship model series for 2025, achieving unprecedented performance in reasoning, coding, and mathematics. Available in three variants—Instant (optimized for speed), Thinking (step-by-step reasoning), and Pro (maximum capability)—it sets new industry benchmarks including a perfect 100% on AIME 2025 and 55.6% on SWE-Bench Pro. The model excels at professional knowledge work including complex spreadsheets, presentations, and business documents. It demonstrates 30% fewer hallucinations than GPT-5.1 and introduces improved agentic capabilities for executing multi-step tasks with high reliability. Key improvements include enhanced tool calling, superior front-end code generation, and better long-context reasoning.
Claude Opus 4
by AnthropicAnthropic's most capable model, excelling at complex analysis, nuanced content creation, and advanced coding tasks. Features superior reasoning and the ability to work autonomously on extended tasks.
Claude Sonnet 4
by AnthropicThe best combination of performance and speed for efficient, high-throughput tasks. Excellent balance of intelligence and cost-effectiveness.
DeepSeek-R1
by DeepSeekReasoning-focused model achieving strong performance on math and coding benchmarks through reinforcement learning.
o3-mini
by OpenAIFast, cost-efficient reasoning model excelling at STEM tasks. Offers adjustable reasoning effort levels.
DeepSeek-V3
by DeepSeekHighly efficient 671B MoE model trained on 14.8T tokens. Achieves top benchmark scores at fraction of typical training cost.
Gemini 2.0 Flash
by GoogleGoogle's latest multimodal model with native tool use, code execution, and agentic capabilities. Fast and efficient.
Llama 3.3 70B
by MetaMeta's latest open-source model offering performance comparable to Llama 3.1 405B at a fraction of the cost. Excellent for self-hosting.
o1
by OpenAIOpenAI's reasoning model designed to solve hard problems across science, coding, and math using chain-of-thought reasoning.
Qwen2.5-Coder
by Alibaba CloudSpecialized coding model available in sizes from 0.5B to 32B. State-of-the-art for open-source code models.
Qwen 2.5 72B
by Alibaba CloudAlibaba's flagship open-source model with strong coding and math capabilities. Supports 29 languages.
Grok-2
by xAIxAI's flagship model with strong reasoning and coding capabilities. Known for witty responses and real-time knowledge.
Llama 3.1 405B
by MetaMeta's largest open-source model with 405 billion parameters. Competitive with leading closed models on benchmarks.
Mistral Nemo
by Mistral AIEfficient 12B model developed with NVIDIA. Drop-in replacement for Mistral 7B with improved performance.
Codestral
by Mistral AISpecialized coding model trained on 80+ programming languages. Optimized for code completion and generation.
GPT-4o
by OpenAIOpenAI's flagship multimodal model with advanced reasoning, vision, and audio capabilities. Fast and versatile for most tasks.
Mistral Large
by Mistral AIMistral's flagship model with top-tier reasoning, coding, and multilingual capabilities. Strong at complex tasks.
GPT-4
by OpenAIOpenAI's original GPT-4 model. A highly capable large language model for complex tasks requiring advanced reasoning and broad knowledge.
GPT-4 Turbo
by OpenAIAn optimized version of GPT-4 with vision capabilities and improved performance. Supports both text and image inputs with a 128K context window.
GPT-4.1
by OpenAIOpenAI's latest flagship model with improved coding, instruction following, and long-context understanding. Excels at complex multi-step tasks with a 1M token context window.
GPT-4.1 mini
by OpenAIA smaller, faster, and more affordable version of GPT-4.1. Ideal for tasks requiring quick responses while maintaining strong performance.
GPT-5
by OpenAIOpenAI's most advanced language model to date. Features unprecedented reasoning, creativity, and multimodal understanding. Represents a major leap in AI capabilities across all domains.
GPT-5.1
by OpenAIThe latest iteration of GPT-5 with improved instruction following, reduced hallucinations, and enhanced safety. Offers the best balance of capability and reliability for production use.
o1-mini
by OpenAIA smaller, faster reasoning model optimized for coding and STEM tasks. Offers strong logical capabilities at a lower cost than o1.
o3
by OpenAIOpenAI's most powerful reasoning model. Uses extended thinking time to solve complex problems in math, science, and coding. Achieves expert-level performance on technical benchmarks.
o4-mini
by OpenAIA cost-effective reasoning model that balances strong logical capabilities with faster response times. Great for everyday reasoning tasks.