Model Comparison
MiniMax M1 80K vs Mistral Small 3.1 24B BaseWhich is better in 2026?
MiniMax M1 80K significantly outperforms across most benchmarks. Mistral Small 3.1 24B Base is 6.4x cheaper per token.
Verdict: MiniMax M1 80K vs Mistral Small 3.1 24B Base — which is better?
MiniMax M1 80K (by MiniMax) and Mistral Small 3.1 24B Base (by Mistral AI) are two of the AI models people compare most. Here is how they stack up on benchmarks, price and capabilities, and which one to pick in 2026.
MiniMax M1 80K outperforms in 2 benchmarks (GPQA, MMLU-Pro), while Mistral Small 3.1 24B Base is better at 0 benchmarks. MiniMax M1 80K significantly outperforms across most benchmarks.
On price, Mistral Small 3.1 24B Base is roughly 6.4x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
MiniMax M1 80K also accepts a larger context window (1,000,000 input tokens), making it the stronger choice for long documents and large codebases.
Choose MiniMax M1 80K if…
- you want the strongest raw capability — it leads on 2 of 2 shared benchmarks
- you process long inputs — it offers a 1,000,000 token context window
- you want the most recent training data — it shipped Jun 2025
Choose Mistral Small 3.1 24B Base if…
- cost matters — it's about 6.4x cheaper per token
Performance Benchmarks
Comparative analysis across standard metrics
MiniMax M1 80K outperforms in 2 benchmarks (GPQA, MMLU-Pro), while Mistral Small 3.1 24B Base is better at 0 benchmarks.
MiniMax M1 80K significantly outperforms across most benchmarks.
Arena Performance
Human preference votes
Pricing Analysis
Price comparison per million tokens
For input processing, MiniMax M1 80K ($0.55/1M tokens) is 5.5x more expensive than Mistral Small 3.1 24B Base ($0.10/1M tokens).
For output processing, MiniMax M1 80K ($2.20/1M tokens) is 7.3x more expensive than Mistral Small 3.1 24B Base ($0.30/1M tokens).
In conclusion, MiniMax M1 80K is more expensive than Mistral Small 3.1 24B Base.*
* Using a 3:1 ratio of input to output tokens
Model Size
Parameter count comparison
MiniMax M1 80K has 432.0B more parameters than Mistral Small 3.1 24B Base, making it 1800.0% larger.
Context Window
Maximum input and output token capacity
MiniMax M1 80K accepts 1,000,000 input tokens compared to Mistral Small 3.1 24B Base's 128,000 tokens. Mistral Small 3.1 24B Base can generate longer responses up to 128,000 tokens, while MiniMax M1 80K is limited to 40,000 tokens.
Input Capabilities
Supported data types and modalities
Mistral Small 3.1 24B Base supports multimodal inputs, whereas MiniMax M1 80K does not.
Mistral Small 3.1 24B Base can handle both text and other forms of data like images, making it suitable for multimodal applications.
MiniMax M1 80K
Mistral Small 3.1 24B Base
License
Usage and distribution terms
MiniMax M1 80K is licensed under MIT, while Mistral Small 3.1 24B Base uses Apache 2.0.
License differences may affect how you can use these models in commercial or open-source projects.
MIT
Open weights
Apache 2.0
Open weights
Release Timeline
When each model was launched
MiniMax M1 80K was released on 2025-06-16, while Mistral Small 3.1 24B Base was released on 2025-03-17.
MiniMax M1 80K is 3 months newer than Mistral Small 3.1 24B Base.
Jun 16, 2025
1.1 years ago
3mo newerMar 17, 2025
1.4 years ago
Knowledge Cutoff
When training data ends
Neither model specifies a knowledge cutoff date.
Unable to compare the recency of their training data.
Provider Availability
MiniMax M1 80K is available from Novita. Mistral Small 3.1 24B Base is available from Mistral AI.
MiniMax M1 80K
Mistral Small 3.1 24B Base
Outputs Comparison
Key Takeaways
MiniMax M1 80K
View detailsMiniMax
Mistral Small 3.1 24B Base
View detailsMistral AI
Detailed Comparison
Interactive Arena
Judge for yourself.
Run your own prompts against MiniMax M1 80K and Mistral Small 3.1 24B Base side-by-side, then vote on the output you prefer.
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FAQ
Common questions about MiniMax M1 80K vs Mistral Small 3.1 24B Base.