Best AI models for coding
The Coding Index blends multiple coding evaluations: contamination-free code generation (LiveCodeBench), research-level scientific coding (SciCode), and agentic terminal tasks (Terminal-Bench). It is a broader, harder-to-game signal than any single coding benchmark.
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claude-fable-5.1Anthropic路$10.00 / $50.00 per 1M81.681.6 - 馃claude-opus-5Anthropic路$5.00 / $25.00 per 1M78.078.0
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gpt-5.6-solOpenAI路$4.00 / $20.00 per 1M77.477.4 - 4gpt-6-astraOpenAI路$10.00 / $50.00 per 1M76.976.9
- 5grok-4.6xAI路$2.00 / $6.00 per 1M76.876.8
- 6gpt-5.6-terraOpenAI路$2.00 / $12.00 per 1M76.776.7
- 7claude-fable-5Anthropic路$10.00 / $50.00 per 1M76.576.5
- 8
gemini-3.8-flash50% offGoogle Vertex AI路$0.75 / $3.75 per 1M76.376.3 - 9
qwen3.8-maxAlibaba Cloud路$2.00 / $6.00 per 1M76.276.2 - 10
kimi-k3Moonshot AI路$3.00 / $15.00 per 1M76.276.2 - 11muse-spark-1.3meta路$1.25 / $4.25 per 1M75.875.8
- 12gpt-5.5OpenAI路$5.00 / $30.00 per 1M74.974.9
- 13
glm-5.3Z.ai路$1.40 / $4.40 per 1M74.874.8 - 14claude-opus-4-8Anthropic路$5.00 / $25.00 per 1M74.374.3
- 15claude-opus-4-7Anthropic路$5.00 / $25.00 per 1M73.673.6
- 16qwen3.8-flash-nextTensorX路$0.20 / $0.50 per 1M73.173.1
- 17grok-4.5xAI路$2.00 / $6.00 per 1M72.472.4
- 18qwen3.8-2.4t-a95bTensorX路$2.50 / $6.00 per 1M71.971.9
- 19glm-5.3-flashZ.ai路$0.15 / $0.50 per 1M71.571.5
- 20gemini-3.7-flash50% offGoogle Vertex AI路$0.75 / $3.75 per 1M71.571.5
- 21claude-sonnet-5Anthropic路$2.00 / $10.00 per 1M71.571.5
- 22gpt-5.6-lunaOpenAI路$0.20 / $1.20 per 1M71.471.4
- 23gpt-5.4OpenAI路$2.50 / $15.00 per 1M71.171.1
- 24
gemini-3.6-flashGoogle Gemini API路$1.50 / $7.00 per 1M69.269.2 - 25deepseek-v4-flash-0731Fireworks AI路$0.22 / $0.66 per 1M69.169.1
- 26
deepseek-v4-pro-0813DeepSeek路$1.32 / $3.96 per 1M68.868.8 - 27glm-5.2Z.ai路$1.40 / $4.40 per 1M68.868.8
- 28gemini-3.1-pro-previewGoogle Gemini API路$2.00 / $12.00 per 1M68.868.8
- 29
qwen3.8-27bDeepInfra路$0.20 / $2.50 per 1M68.168.1 - 30qwen3.7-maxAlibaba Cloud路$2.50 / $7.50 per 1M66.066.0
How to choose the best AI coding model
The best AI model for coding depends on your use case. For agentic coding tasks (editing files, running commands, fixing repos end-to-end), models with high Terminal-Bench scores perform best inside tools like Claude Code, Cursor, Codex, and Aider. For pure code generation from specifications, LiveCodeBench scores predict quality. For research and scientific computing, SciCode results matter most.
In production, model choice interacts with cost and latency. A slightly lower-ranked model at 10x cheaper per token may be the better default for high-volume autocomplete, while the top-ranked model is reserved for complex multi-file refactors. AI gateways like Requesty let you route between models dynamically: use the best model for hard tasks and a fast, cheap model for simple completions, all through one API.
Access all top coding models through a single OpenAI-compatible API at requesty.ai. Automatic prompt caching saves 40-60% on token costs, and failover ensures your coding agent never stops due to a single provider outage.
Frequently asked questions
- What is the best AI model for coding in 2026?
- Based on the Coding Index (combining LiveCodeBench, SciCode, and Terminal-Bench), the top AI coding models in 2026 are Claude Opus 4.8, GPT-5.5, and Gemini 3. Claude Opus 4.8 leads on agentic coding tasks, GPT-5.5 excels at code generation from specs, and Gemini 3 offers strong performance with large context windows for whole-codebase analysis.
- Which AI model is best for agentic coding (Claude Code, Cursor, Codex)?
- For agentic coding tools that edit files and run terminal commands, Terminal-Bench scores are the most predictive benchmark. Models ranking highest on Terminal-Bench Hard perform best inside Claude Code, Cursor, Codex, and Aider because the benchmark mirrors real coding agent workflows.
- How can I access the best coding models through one API?
- Requesty provides a single OpenAI-compatible API endpoint that routes to all top coding models (Claude, GPT, Gemini, DeepSeek, and 600+ others). You switch models by changing one parameter. Automatic failover ensures your coding agent keeps working even if one provider goes down. Prompt caching saves 40-60% on repeated code patterns.
Explore other rankings
How we rank
Scores for Coding Index come from Artificial Analysis, an independent AI benchmarking service. When a model is available through multiple providers (e.g. Anthropic direct, AWS Bedrock, Google Vertex), we show one canonical entry per model family so the ranking isn't polluted by duplicates. Benchmarks measure specific skills, so always validate on your own workload before committing.
One API for every model on this list
Requesty is OpenAI-compatible and routes to 600+ models. Switch between any of the models above by changing one parameter in your code.