Specifications
Context Window
—
Input Price/1M
—
Output Price/1M
—
Parameters
—
Benchmarks
MiniMax M1 40k results on the main AI model evaluation benchmarks. Higher scores indicate better performance.
Agentic
| Benchmark | Score | Maximum | Methodology |
|---|---|---|---|
| Terminal-Bench Hard | 2.0 | 100.0 | — |
Coding
| Benchmark | Score | Maximum | Methodology |
|---|---|---|---|
| LiveCodeBench | 66.0 | 100.0 | Artificial Analysis official API |
| SciCode | 38.0 | 100.0 | — |
| AA Coding Index | 14.1 | 100.0 | Artificial Analysis official API |
Knowledge
| Benchmark | Score | Maximum | Methodology |
|---|---|---|---|
| MMLU-Pro | 81.0 | 100.0 | — |
Long Context
| Benchmark | Score | Maximum | Methodology |
|---|---|---|---|
| AA-LCR | 52.0 | 100.0 | — |
Math
| Benchmark | Score | Maximum | Methodology |
|---|---|---|---|
| MATH-500 | 97.2 | 100.0 | Artificial Analysis official API |
| AIME 2025 | 14.0 | 100.0 | Artificial Analysis official API |
| AA Math Index | 13.7 | 100.0 | Artificial Analysis official API |
overall
| Benchmark | Score | Maximum | Methodology |
|---|---|---|---|
| AA Intelligence Index | 20.9 | 100.0 | Artificial Analysis official API |
Reasoning
| Benchmark | Score | Maximum | Methodology |
|---|---|---|---|
| MMLU Pro | 80.8 | 100.0 | Artificial Analysis official API |
| GPQA Diamond | 68.0 | 100.0 | Artificial Analysis official API |
| IFBench | 41.0 | 100.0 | — |
| HLE | 8.0 | 100.0 | — |
Tool Use
| Benchmark | Score | Maximum | Methodology |
|---|---|---|---|
| Tau²-Bench | 32.0 | 100.0 | — |
Information
- Release date
- June 17, 2025
- Tool Calling
- ❌ Not supported
- Vision
- ❌ Not supported
- Audio
- ❌ Not supported
Full Analysis: MiniMax M1 40k
What is MiniMax M1 40k?
MiniMax M1 40k is an AI model developed by MiniMax, classified as a text model. It focuses on text processing and natural language generation. As a proprietary model, it is available via MiniMax's cloud API.
Pricing & Costs in 2026
MiniMax M1 40k does not have public per-token pricing available at this time. Some models offer access via enterprise plans or research programs. Check MiniMax's official website for up-to-date availability and pricing.
Benchmarks & Performance
MiniMax M1 40k was evaluated on 15 different benchmarks, covering categories like Agentic, Coding, Knowledge, Long Context, Math, overall, Reasoning, Tool Use. Results show exceptional performance across available evaluations.
It's important to note that benchmarks measure specific aspects and don't capture the full user experience. Factors like instruction adherence, behavior in long conversations, and real-world task quality vary significantly between models and aren't always reflected in standard scores.
Recommended Use Cases
MiniMax M1 40k specializes in text, offering advanced capabilities for creating and processing text content.
Comparison with Alternatives
In the 2026 AI model ecosystem, MiniMax M1 40k competes directly with similarly capable models. MiniMax competes in this segment against OpenAI, Anthropic, Google, and Meta. The choice between models depends on the specific use case, budget, latency requirements, and need for features like multimodality and tool calling.
For a detailed side-by-side comparison, use our comparison tool or check the overall model ranking.
Frequently Asked Questions
What is MiniMax M1 40k?
MiniMax M1 40k is an AI model developed by MiniMax. It is a text model.
How much does MiniMax M1 40k cost?
MiniMax M1 40k does not have public per-token pricing available at this time. Check MiniMax's official website for up-to-date information.
How does MiniMax M1 40k compare with other models?
In available benchmarks, MiniMax M1 40k scored: Terminal-Bench Hard: 2/100, LiveCodeBench: 66/100, SciCode: 38/100. See the full table above for a detailed comparison.
Is MiniMax M1 40k open source?
No, MiniMax M1 40k is a proprietary model from MiniMax. It is available via cloud API. For open source alternatives, check our open source model ranking.
What is MiniMax M1 40k best for?
MiniMax M1 40k excels at general-purpose language tasks.
Last updated: June 01, 2026 • View methodology →