7 models for code
Best AI models for coding
Agentic coding is the workload providers now optimise hardest for, which means the general frontier models are also the best code models. What separates them is token efficiency: how much thinking a model burns to land the same diff.
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Coding Agent Index leaders
Artificial Analysis Coding Agent Index, higher is better. Independent but fast-moving — verify before you standardise on one model.
All coding-capable models
7 of 7 models
| Model | Provider | Input / 1M | Output / 1M | Context | Best for | Status |
|---|---|---|---|---|---|---|
| DeepSeek V4-Pro reasoning open | DeepSeek | $0.66 | $1.98 | 1M | Frontier-adjacent reasoning at open-weight prices | stable |
| GLM-5.2 reasoning open | Z.ai | $1.40 | $4.40 | 1M | MIT-licensed coding agents | stable |
| Gemini 3.5 Flash reasoning | $1.50 | $9.00 | 1.05M | Agentic loops and sub-agent fleets | stable | |
| Kimi K3 reasoning open | Moonshot AI | $3.00 | $15.00 | 1.05M | Natively multimodal long-horizon agents | stable |
| GPT-5.6 Sol reasoning | OpenAI | $4.00 | $20.00 | 1.05M | Frontier coding and long-horizon agents | stable |
| Claude Opus 5 reasoning | Anthropic | $5.00 | $25.00 | 1M | Most teams' best Claude starting point | stable |
| Claude Fable 5 reasoning | Anthropic | $10.00 | $50.00 | 1M | Long-horizon agentic engineering | stable |
No models match those filters.
Context window is not the constraint
A million tokens sounds like "fit the whole repo," but long prompts get expensive and recall degrades. Retrieval and compaction still beat brute-force context stuffing.
Caching is the biggest saving
Coding agents resend the same system prompt and file context repeatedly. Cached input runs at roughly a tenth of the base rate, so cache design outweighs model choice on the bill.
Open weights have closed the gap
Open coding models now run usefully on consumer hardware. Compare open options
Frequently asked
Which AI model is best for coding in 2026?
GPT-5.6 Sol currently leads the Artificial Analysis Coding Agent Index at 80. That said, index position changes every few weeks, and token efficiency often matters more than a two-point score gap for real agent work.
What is the cheapest usable model for code?
DeepSeek V4-Pro at $0.66/$1.98 per million tokens. Budget tiers have improved enough that they now handle routine edits, test generation, and refactors that needed a flagship a year ago.
Do I need a coding-specific model?
Generally no. The strongest general frontier models are also the strongest coding models, because agentic coding is what providers optimise for. Dedicated code models mainly matter when you want open weights you can run locally.
Why does token efficiency matter for coding agents?
A coding agent may make hundreds of calls to finish one task. A model that reaches the same result using half the output tokens and half the wall-clock time costs far less overall, even at a higher per-token price.