AI Observatory / Model Radar
Minimax / minimax/minimax-m1
MiniMax: 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...
1,000,000
Context
40,000
Max output
$0.40 / 1M
Prompt price
2025-06-17
Created
01 / Snapshot
Pricing, context, modalities, and parameters.
Model Radar detail pages stay neutral and operator-readable: core metadata first, then workflow fit.
| Provider | Minimax | Input modalities | text |
|---|---|---|---|
| Output modalities | text | Prompt price | $0.40 / 1M |
| Completion price | $2.20 / 1M | Request price | N/A |
| Context length | 1,000,000 | Max completion tokens | 40,000 |
| Supported parameters | frequency_penalty, include_reasoning, max_tokens, presence_penalty, reasoning, repetition_penalty, seed, stop, temperature, tool_choice, tools, top_k, top_p | ||
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minimax/minimax-m1
MiniMax: 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...
Deep analysis
Long context
High-volume usage
Coding workflows
tool-capable
long-context
low-cost
03 / Colophon
Routes and exits.
Each model page stays simple: overview, compare, related models, then back to the public hub.