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Explore Minimax M2 (Fully Tested): I am switching to this. Better than Claude & GLM-4.6 on Long Running Task with 26,954 views, 503 likes, and 32 comments. Experience the impact of this video content that has captured audience attention.

Visit PhotoGenius AI: https://www.photogenius.ai/ Test Minimax M2 now: https://www.minimax.io/ API: https://platform.minimax.io/docs/guides/text-generation In this video, I’ll review MiniMax M2, cover its specs, pricing, availability on OpenRouter and HuggingFace, compare benchmarks, and show real agentic tests in tools like Kilo to see how it stacks up against GLM and Claude Sonnet. -- Key Takeaways: 🚀 MiniMax M2 launches as a compact 230B total / 10B activated model optimized for coding and agentic workflows. 🧠 Strong general reasoning, reliable tool use, and multi-step task execution with low latency. 🧩 Weights are on HuggingFace and it appears likely open-sourced; free to try via OpenRouter and the MiniMax API. 💸 Pricing is around $0.50 input / $2.20 output per 1M tokens, making it very cost-effective. 📏 205k-token context window (down from the previous 1M), an intentional trade-off for efficiency. 📈 Artificial Analysis places it just below Claude 4.5 Sonnet; speed and provider variance look solid. 🛠️ Excellent tool calling and code quality: clean structure, no hardcoded keys, effective use of KiloCode tools. 🧪 My tests: mixed results on visual/UX code tasks (floor plan weak, panda good, Pokeball off, chessboard/Minecraft fail). 🎮 Agentic tasks shine: Movie Tracker and Go TUI Calculator are great; Godot/Nuxt/Rust remain weak spots. 🏆 Ranks 12th on my general leaderboard and 5th on my agentic leaderboard; better than GLM-4.6 on long-running tasks. 🔌 Works with Kilo, Claude Code, and most coder UIs; OpenRouter access makes it easy and free to experiment. ✅ Ideal for persistent, long-running agent workflows and potentially for local cluster deployment.

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