Author's Description
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...
Key Specifications
Supported Parameters
This model supports the following parameters:
Features
This model supports the following features:
Performance Summary
MiniMax M1 demonstrates exceptional reliability with a 98% success rate, consistently providing usable responses. However, it tends to have longer response times, ranking in the 3rd percentile for speed, and is positioned at premium pricing levels, ranking in the 16th percentile for cost-effectiveness. The model exhibits strong performance in several key areas. It achieves perfect accuracy in Email Classification, highlighting its proficiency in categorization tasks, and shows high accuracy in General Knowledge (99.8%) and Ethics (99.0%). Its 93.9% accuracy in Reasoning and 91.0% in Coding underscore its capabilities in complex problem-solving and software engineering, aligning with its design for multi-step reasoning. A notable strength is its ability to handle long contexts, as indicated by its high accuracy in areas requiring deep understanding. Conversely, M1 shows a relative weakness in Instruction Following (62.6% accuracy) and Hallucinations (89.8% accuracy), suggesting room for improvement in precisely adhering to complex directives and acknowledging uncertainty. While its Mathematics score of 87.5% is respectable, it's not a standout compared to its other high-performing categories. The model's high duration across most benchmarks further emphasizes its slower processing speed.
Model Pricing
Current Pricing
| Feature | Price (per 1M tokens) |
|---|---|
| Prompt | $0.4 |
| Completion | $2.2 |
Price History
Available Endpoints
| Provider | Endpoint Name | Context Length | Pricing (Input) | Pricing (Output) |
|---|---|---|---|---|
|
Minimax
|
Minimax | minimax/minimax-m1 | 1M | $0.4 / 1M tokens | $2.2 / 1M tokens |
|
Novita
|
Novita | minimax/minimax-m1 | 1M | $0.4 / 1M tokens | $2.2 / 1M tokens |
|
SiliconFlow
|
SiliconFlow | minimax/minimax-m1 | 131K | $0.4 / 1M tokens | $2.2 / 1M tokens |
|
Novita
|
Novita | minimax/minimax-m1 | 1M | $0.44 / 1M tokens | $1.76 / 1M tokens |
Benchmark Results
| Benchmark | Category | Reasoning | Strategy | Free | Executions | Accuracy | Cost | Duration |
|---|
Other Models by minimax
|
|
Released | Params | Context |
|
Speed | Ability | Cost |
|---|---|---|---|---|---|---|---|
| MiniMax: MiniMax M2.7 Unavailable | Mar 18, 2026 | — | 204K |
Text input
Text output
|
★ | ★★★★ | $$$$ |
| MiniMax: MiniMax M2.7 | Mar 18, 2026 | — | 204K |
Text input
Text output
|
★ | ★★★★ | $$$$ |
| MiniMax: MiniMax M2.5 | Feb 12, 2026 | — | 204K |
Text input
Text output
|
★★ | ★★★★ | $$$$ |
| MiniMax: MiniMax M2-her | Jan 23, 2026 | — | 65K |
Text input
Text output
|
★★ | ★ | $$$ |
| MiniMax: MiniMax M2.1 | Dec 22, 2025 | ~10B | 204K |
Text input
Text output
|
★ | ★★★★ | $$$$$ |
| MiniMax: MiniMax M2 | Oct 23, 2025 | ~230B | 196K |
Text input
Text output
|
★ | ★★★ | $$$$$ |
| MiniMax: MiniMax M1 (extended) Unavailable | Jun 17, 2025 | — | 128K |
Text input
Text output
|
★ | ★ | $$$$ |
| MiniMax: MiniMax-01 | Jan 14, 2025 | ~456B | 1M |
Text input
Image input
Text output
|
★★★ | ★★ | $$$ |