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Best AI for Coding & Software Development

Find the top AI models for writing, debugging, and reviewing code. We rank models by coding benchmarks like HumanEval and SWE-bench so you can pick the best copilot for your stack.

20 Models RankedUpdated 20263 Open Source

What to Look For

  • High scores on coding benchmarks (HumanEval, SWE-bench)
  • Large context window for working with full files and repos
  • Multi-language support (Python, TypeScript, Rust, Go, etc.)
  • Low latency for real-time code completions
  • Strong instruction following for precise edits

Top Recommended Models

#ModelAvg Score
1Google logo

Gemini 3.1 Pro

Google

93.5
2OpenAI logo

o3-pro

OpenAI

93.3
3OpenAI logo

GPT-5.2

OpenAI

92.9
4Anthropic logo

Claude Opus 4.6

Anthropic

92.7
5Moonshot AI logo

Kimi K2.5

Moonshot AI

92.3
6OpenAI logo

o3

OpenAI

91.5
7Google logo

Gemini 3 Pro

Google

91.3
8OpenAI logo

GPT-5

OpenAI

91.0
9Google logo

Gemini 3 Flash

Google

91.0
10Anthropic logo

Claude Sonnet 4.6

Anthropic

91.0
11Google logo

Gemini 3 Deep Think

Google

89.9
12Anthropic logo

Claude Opus 4.5

Anthropic

89.9
13OpenAI logo

GPT-5.3-Codex

OpenAI

88.9
14DeepSeek logo

DeepSeek V4

DeepSeek

88.6
15Anthropic logo

Claude Opus 4

Anthropic

88.5
16Google logo

Gemini 2.5 Pro

Google

88.4
17OpenAI logo

o1

OpenAI

88.0
18DeepSeek logo

DeepSeek-R1

DeepSeek

87.0
19OpenAI logo

o4-mini

OpenAI

86.5
20DeepSeek logo

DeepSeek-V3.2

DeepSeek

86.4

How We Ranked These

Models are ranked by their average benchmark score across all available benchmarks in the relevant categories. For “Coding”, we filter models that match specific criteria (such as modality, tier, or benchmark category) and then sort by aggregate performance.

Benchmark data comes from official sources and is updated regularly. Pricing reflects the latest published API rates. We do not accept payment for rankings — placement is determined entirely by benchmark performance.

Why It Matters

Choosing the right AI model for software development can dramatically accelerate your workflow. The best coding models excel at understanding complex codebases, generating idiomatic code across multiple languages, and catching subtle bugs before they reach production. They need strong reasoning abilities to understand architectural decisions and large context windows to work with real-world file sizes.

When evaluating AI models for coding, pay close attention to benchmark scores on HumanEval, MBPP, and SWE-bench. These tests measure a model's ability to produce correct, functional code and fix real-world GitHub issues. Models that score well on coding benchmarks also tend to perform better at related tasks like writing tests, generating documentation, and explaining legacy code.

Price matters too, especially for development teams that send hundreds of requests per day. Some frontier models deliver top-tier code quality but at a premium price, while mid-tier and open-source alternatives can handle most everyday coding tasks at a fraction of the cost. Consider whether you need the absolute best performance for complex architecture work or a fast, affordable model for routine completions.

Compare the top coding models side by side

See how Gemini 3.1 Pro, o3-pro, GPT-5.2 stack up against each other across benchmarks, pricing, and capabilities.

Related Use Cases

Frequently Asked Questions

What is the best AI for coding?

Based on our benchmark analysis, Gemini 3.1 Pro by Google is currently the top-ranked AI model for coding, with an average benchmark score of 93.5. o3-pro and GPT-5.2 are also strong contenders.

How do you rank AI models for coding?

We rank models using a combination of benchmark scores, pricing data, and capability analysis. For coding, we prioritize high scores on coding benchmarks (humaneval, swe-bench) and large context window for working with full files and repos. Models are sorted by their average benchmark score across relevant categories.

Are open-source models good for coding?

Open-source models have improved significantly and can be excellent for coding, especially when budget or data privacy are concerns. Among our ranked models, DeepSeek V4 and DeepSeek-R1 are strong open-source options.