MiniMax M1
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 to process long sequences—up to 1 million tokens—while maintaining competitive FLOP efficiency. With 456 billion total parameters and 45.9B active per token, this variant is optimized for complex, multi-step reasoning tasks. Trained via a custom reinforce
Context window
This model accepts 1M tokens in one request (~750K words of text).
What fits in one request
- FitsShort documentAbout 1,500 words of text
- FitsLong documentAbout 37K words of text
- FitsSmall codebaseAbout 150K words of text
- FitsFull novelAbout 375K words of text
Specifications
Context size, pricing, and release info in one place.
- Context window
- 1,000,000 tokens (1M)
- Max output tokens
- 40,000 tokens (40K)
- Speed tier
- fast
- Provider
- Minimax
- Release date
- Jun 2025
Capabilities
See which features this model supports, such as vision, tools, and streaming.
- Tool use
- Can call external tools and APIs
- Supported
- Function calling
- Structured function call interface
- Supported
- Extended thinking
- Shows its chain-of-thought reasoning
- Supported
- Streaming
- Returns tokens as they are generated
- Supported
- Vision
- Accepts image inputs alongside text
- Not supported
- Web search
- Can browse the web during a request
- Not supported
- Batch API
- Process many requests asynchronously
- Not supported
- Prompt caching
- Reuse repeated prompt prefixes cheaply
- Not supported
Best for
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Compare MiniMax M1
Open a side-by-side comparison with one click.
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MiniMax M1 has 2280% larger context window
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MiniMax M1 has 2280% larger context window
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- MiniMax M1 vs Apac Amazon Nova 2 Pro Preview 20251202
Same context window size
Frequently asked questions
Short answers about context size and how this model behaves.
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