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MiniMax releases M3.1 Flash weights with 428B total parameters

AIMiniMax says the M3.1 Flash model weights are now public, with 428B total parameters and 23B activated per token. The company reports 73.7% on DeepSWE v1.1 and 82.2 on CyberGym, and lists API pricing of $0.15 and $0.60 per 1M input and output tokens.

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The post gives a benchmark table comparing MiniMax M3.1 Flash with several rival models, useful for judging its coding and agent performance against peers.

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MiniMax M3.1 Flash weights are now public. 428B parameters total, 23B activated per token.

Agentic performance: A generational leap in agentic tasks, coding, and cybersecurity — 76.2 on BankerToolBench, 73.7% on DeepSWE v1.1, 61.7 on OSWorld V2, 29.6 on Agents' Last Exam, and 82.2 on CyberGym.
Efficient by design: MiniMax Sparse Attention and DSpark speculative decoding improve inference efficiency.

Hugging Face:
https://huggingface.co/MiniMaxAI/MiniMax-M3.1-Flash
ModelScope:
https://modelscope.cn/models/MiniMax/MiniMax-M3.1-Flash

API: http://platform.minimax.io
M Plan: https://minimax.io/m-planMiniMax
MCode for desktop: https://agent.minimax.io/download

MiniMax (official)@MiniMax_AI
MiniMax M3.1 Flash: Space Performance + Bunny Speed 🚀🐰 Yes, Space Bunny - which has topped global leaderboards with 200T+ tokens - was an earlier version of M3.1 Flash. 💰Redefining the performance economics of agentic AI. M3.1 Flash achieves frontier-level intelligence across key tasks such as Cowork (Automation-Bench: 62%; ALE: 30%), Coding (DeepSWE: 74%) and Visual Reasoning (BabyVision: 91%), at 1/3 the cost of M3 and 3x the speed. API pricing (flat rate): $0.15 / $0.60 per 1M input/output tokens, with cache reads at $0.015 / 1M tokens. Model weights will arrive on Oct 23. API: http://platform.minimax.io M Plan: https://www.minimax.io/m-plan MiniMax Code for desktop: https://agent.minimax.io/download
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Original title: MiniMax M3.1 Flash weights are now public. 428B parameters total, 23B activated per token.

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MiniMaxAI agentsAI codingOpen-source ecosystemChina AIModel releasesEvals & benchmarks