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Collections/Coding

Best AI Models for Coding

Model rankings updated March 2026 based on real usage data.

Compare the best AI models for coding, ranked by real usage from developers on OpenRouter. Whether you're generating code, debugging, refactoring or building an AI coding assistant, these LLMs deliver strong performance across popular languages and frameworks.

This collection features top coding models from Anthropic, Google, xAI, OpenAI and more, all accessible through a single API. From agentic coding workflows to one-off code generation, find the right model for your engineering needs.

LLM Leaderboard for Programming Models

1.
Minimax M2.5
by minimax
626B
24.5%
2.
Mimo V2 Flash
by xiaomi
238B
9.3%
3.
Kimi K2.5 0127
by moonshotai
199B
7.8%
4.
Claude Opus 4.6
by anthropic
192B
7.5%
5.
Hunter Alpha
by openrouter
190B
7.4%
6.
Claude Sonnet 4.6
by anthropic
162B
6.3%
7.
Gemini 3 Flash Preview
by google
108B
4.2%
8.
Step 3.5 Flash (free)
by stepfun
94.1B
3.7%
9.
GPT-5.3-Codex
by openai
76.3B
3.0%
10.
Others
by unknown
672B
26.3%

Top Coding Models on OpenRouter

Based on top weekly usage data from millions of users accessing AI models for coding through OpenRouter.

Favicon for minimax

MiniMax: MiniMax M2.5

1.6T tokens

MiniMax-M2.5 is a SOTA large language model designed for real-world productivity. Trained in a diverse range of complex real-world digital working environments, M2.5 builds upon the coding expertise of M2.1 to extend into general office work, reaching fluency in generating and operating Word, Excel, and Powerpoint files, context switching between diverse software environments, and working across different agent and human teams. Scoring 80.2% on SWE-Bench Verified, 51.3% on Multi-SWE-Bench, and 76.3% on BrowseComp, M2.5 is also more token efficient than previous generations, having been trained to optimize its actions and output through planning.

by minimax197K context$0.20/M input tokens$1.20/M output tokens
Favicon for stepfun

StepFun: Step 3.5 Flash (free)

1.46T tokens

Step 3.5 Flash is StepFun's most capable open-source foundation model. Built on a sparse Mixture of Experts (MoE) architecture, it selectively activates only 11B of its 196B parameters per token. It is a reasoning model that is incredibly speed efficient even at long contexts.

by stepfun256K context$0/M input tokens$0/M output tokens
Favicon for deepseek

DeepSeek: DeepSeek V3.2

1.16T tokens

DeepSeek-V3.2 is a large language model designed to harmonize high computational efficiency with strong reasoning and agentic tool-use performance. It introduces DeepSeek Sparse Attention (DSA), a fine-grained sparse attention mechanism that reduces training and inference cost while preserving quality in long-context scenarios. A scalable reinforcement learning post-training framework further improves reasoning, with reported performance in the GPT-5 class, and the model has demonstrated gold-medal results on the 2025 IMO and IOI. V3.2 also uses a large-scale agentic task synthesis pipeline to better integrate reasoning into tool-use settings, boosting compliance and generalization in interactive environments.

Users can control the reasoning behaviour with the reasoning enabled boolean. Learn more in our docs

by deepseek164K context$0.26/M input tokens$0.38/M output tokens
Favicon for google

Google: Gemini 3 Flash Preview

1.08T tokens

Gemini 3 Flash Preview is a high speed, high value thinking model designed for agentic workflows, multi turn chat, and coding assistance. It delivers near Pro level reasoning and tool use performance with substantially lower latency than larger Gemini variants, making it well suited for interactive development, long running agent loops, and collaborative coding tasks. Compared to Gemini 2.5 Flash, it provides broad quality improvements across reasoning, multimodal understanding, and reliability.

The model supports a 1M token context window and multimodal inputs including text, images, audio, video, and PDFs, with text output. It includes configurable reasoning via thinking levels (minimal, low, medium, high), structured output, tool use, and automatic context caching. Gemini 3 Flash Preview is optimized for users who want strong reasoning and agentic behavior without the cost or latency of full scale frontier models.

by google1.05M context$0.50/M input tokens$3/M output tokens$1/M audio tokens
Favicon for anthropic

Anthropic: Claude Sonnet 4.6

1.05T tokens

Sonnet 4.6 is Anthropic's most capable Sonnet-class model yet, with frontier performance across coding, agents, and professional work. It excels at iterative development, complex codebase navigation, end-to-end project management with memory, polished document creation, and confident computer use for web QA and workflow automation.

by anthropic1M context$3/M input tokens$15/M output tokens
Favicon for anthropic

Anthropic: Claude Opus 4.6

979B tokens

Opus 4.6 is Anthropic’s strongest model for coding and long-running professional tasks. It is built for agents that operate across entire workflows rather than single prompts, making it especially effective for large codebases, complex refactors, and multi-step debugging that unfolds over time. The model shows deeper contextual understanding, stronger problem decomposition, and greater reliability on hard engineering tasks than prior generations.

Beyond coding, Opus 4.6 excels at sustained knowledge work. It produces near-production-ready documents, plans, and analyses in a single pass, and maintains coherence across very long outputs and extended sessions. This makes it a strong default for tasks that require persistence, judgment, and follow-through, such as technical design, migration planning, and end-to-end project execution.

For users upgrading from earlier Opus versions, see our official migration guide here

by anthropic1M context$5/M input tokens$25/M output tokens
Favicon for google

Google: Gemini 2.5 Flash

637B tokens

Gemini 2.5 Flash is Google's state-of-the-art workhorse model, specifically designed for advanced reasoning, coding, mathematics, and scientific tasks. It includes built-in "thinking" capabilities, enabling it to provide responses with greater accuracy and nuanced context handling.

Additionally, Gemini 2.5 Flash is configurable through the "max tokens for reasoning" parameter, as described in the documentation (https://openrouter.ai/docs/use-cases/reasoning-tokens#max-tokens-for-reasoning).

by google1.05M context$0.30/M input tokens$2.50/M output tokens$1/M audio tokens
Favicon for moonshotai

MoonshotAI: Kimi K2.5

608B tokens

Kimi K2.5 is Moonshot AI's native multimodal model, delivering state-of-the-art visual coding capability and a self-directed agent swarm paradigm. Built on Kimi K2 with continued pretraining over approximately 15T mixed visual and text tokens, it delivers strong performance in general reasoning, visual coding, and agentic tool-calling.

by moonshotai262K context$0.45/M input tokens$2.20/M output tokens
Favicon for x-ai

xAI: Grok 4.1 Fast

522B tokens

Grok 4.1 Fast is xAI's best agentic tool calling model that shines in real-world use cases like customer support and deep research. 2M context window.

Reasoning can be enabled/disabled using the reasoning enabled parameter in the API. Learn more in our docs

by x-ai2M context$0.20/M input tokens$0.50/M output tokens
Favicon for google

Google: Gemini 2.5 Flash Lite

517B tokens

Gemini 2.5 Flash-Lite is a lightweight reasoning model in the Gemini 2.5 family, optimized for ultra-low latency and cost efficiency. It offers improved throughput, faster token generation, and better performance across common benchmarks compared to earlier Flash models. By default, "thinking" (i.e. multi-pass reasoning) is disabled to prioritize speed, but developers can enable it via the Reasoning API parameter to selectively trade off cost for intelligence.

by google1.05M context$0.10/M input tokens$0.40/M output tokens$0.30/M audio tokens