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MiniMax-M1 is a large-scale, open-weight reasoning model designed for extended context and high-efficiency inference. It leverages a hybrid Mixture-of-Experts (MoE) architecture paired with a custom "lightning attention" mechanism, allowing it...
Best for
Price history
Local run command
# Refer to provider docs:
Presumptive Specs:
Typical GPU
12–24 GB VRAM
System RAM
16+ GB
Disk
20+ GB free
Runtime
Docker / local runtime
Community reliability estimate · not official
About this score: Community-estimated based on user reports and publicly available benchmark data (e.g. TruthfulQA). This is not an official score from the model provider. Scores may be inaccurate — always verify with the official leaderboard before making production decisions.
Input & output cost per 1M tokens over time
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Learn how to use MiniMax: MiniMax M1
💡 Tip: Start with the sample prompts above to see how MiniMax: MiniMax M1 works best.
Proven prompts shared by the community for this model