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Read the full article: Full write-up with tables and code: https://binaryverseai.com/minimax-m2-... MiniMax M2 is the 10B-active MoE that makes agentic coding feel fast, affordable, and practical. In this 16:04 review, I test MiniMax M2 as an agentic AI model, walk through setup, compare benchmarks, and show how to deploy it with SGLang, vLLM, and MLX. If you want the best AI coding agent for day-to-day dev work without frontier costs, start here. What you will learn: What MiniMax M2 is and how its Mixture-of-Experts design keeps latency and costs low MiniMax M2 benchmarks for real engineering, including SWE-bench, Terminal-Bench, and BrowseComp Pricing for API usage and where it fits in your stack Exact setup using an Anthropic-compatible endpoint, plus local options with open weights Practical tips for reliable tool use, retries, and long-horizon tasks Key details: Pricing: $0.30 per 1M input tokens, $1.20 per 1M output tokens Promo: Free API usage until November 7, 2025 Use cases: repo repair loops, terminal automation, browse-retrieve-cite pipelines, CI agents Useful links: Try the web agent: https://agent.minimax.io/ API docs: https://platform.minimax.io/docs/guid... Open weights: https://huggingface.co/MiniMaxAI/Mini... Chapters: 00:00 – Welcome to the deep dive 01:03 – laser focus on deployment strategy 02:02 – the mixture of experts layout 03:39 – keeps those activations small 04:18 – focused on endtoend workflows 05:19 – terminal bench score is 46.3 05:53 – browse comp is 44.0 06:32 – sticking to the plan 07:10 – We’ve gathered feedback 08:51 – give it guardrails 09:24 – input tokens 3 per million 09:55 – a few cents per loop 10:32 – there’s local deployment 11:09 – anthropic compatible 12:10 – internal scratch pad 13:17 – temperature 1.0 13:44 – reliable AI coding assistant 14:43 – keep making progress 15:10 – a real sandbox 15:39 – a practical trial If this helped, subscribe for weekly deep dives on open source LLMs, agent frameworks, and real engineering workflows. #MiniMaxM2 #AgenticAI #OpenSourceLLM #CodingAgent #LLMBenchmarks