Best Coding Agents
Models optimized for coding, agentic tool use, and multi-step workflows. Ideal for writing, debugging, and refactoring code, executing tool calls, and orchestrating complex long-running automated pipelines.
Best rated
MiniMax-M2.5 is MiniMax’s latest frontier model, optimized for fast, low-cost agentic workflows across coding, search/tool use, and high-value office tasks. Trained with large-scale reinforcement learning in complex real-world environments, it delivers strong reasoning, efficient task decomposition, and high-quality outputs for production assistants and enterprise workflows.
Featured Models
Top-performing models in this category, recommended by our community and performance benchmarks.
MiniMax M2.7-Highspeed is the performance-tuned variant of M2.7, built for lower latency and higher throughput while keeping output behavior consistent with the standard model. It’s a strong fit for interactive coding agents, tool-calling pipelines, and office automation flows where responsiveness matters.
Gemini 3.1 Flash Lite is Google’s flagship multimodal language model that processes text alongside images, audio, video, code, and documents. It offers high-performance reasoning, complex instruction following, and deep contextual understanding for a wide range of tasks across language, analysis, and problem solving
Gemini 3 Flash is Google’s flagship multimodal language model that processes text alongside images, audio, video, code, and documents. It offers high-performance reasoning, complex instruction following, and deep contextual understanding for a wide range of tasks across language, analysis, and problem solving.
MiniMax M2.7 is a long-context LLM designed for agentic workflows across software engineering, search and tool use, and high-value office productivity tasks. It’s built for multi-step execution, with strong instruction following and dependable task decomposition, making it a solid default for production assistants that write code, call tools, and handle complex document workflows.
Gemini 3.1 Pro is Google’s flagship multimodal language model that processes text alongside images, audio, video, code, and documents. It offers high-performance reasoning, complex instruction following, and deep contextual understanding for a wide range of tasks across language, analysis, and problem solving.
GPT-5.4 Pro is the high-performance variant of GPT-5.4, optimized for enterprise-grade professional tasks. It offers deeper reasoning, enhanced accuracy, and extended compute for complex multi-step workflows including document creation, spreadsheet analysis, and autonomous agent orchestration. It shares the 1 million token context window and native computer use capabilities of the standard GPT-5.4.
GPT-5.4 is OpenAI's flagship large language model, featuring a 1 million token context window, native computer use, and a 33% reduction in factual errors over GPT-5.2. It integrates coding capabilities from GPT-5.3-Codex, is 47% more token-efficient, and supports configurable reasoning effort for complex professional tasks.
GPT-5.4 Mini is a compact, efficient variant of GPT-5.4 designed for coding assistants, subagent orchestration, and multimodal applications requiring faster responsiveness. It supports a 400K token context window and retains native computer use and configurable reasoning effort at a lower cost than the flagship model.
GPT-5.4 Nano is the smallest and fastest variant of GPT-5.4, designed for high-throughput, low-latency tasks such as classification, data extraction, ranking, and lightweight automation. It prioritizes speed and cost efficiency for simple, high-volume workloads and is available exclusively via the API.