MiniMax M3 vs Mistral Large 4
Mistral Large 4 leads the LLM Stats Score 45.8 to 40.9. MiniMax M3 is 2.1x cheaper per token.
MiniMax · Mistral AI · Updated for 2026
Which is better?
Mistral Large 4 leads the overall LLM Stats Score 45.8 to 40.9, ranking #39 overall.
In the 2 individual benchmarks reported for both models, Mistral Large 4 wins 2; this is a narrower head-to-head signal than the composite indexes.
On price, MiniMax M3 is roughly 2.1x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
Mistral Large 4 also accepts a larger context window (1,000,000 input tokens), making it the stronger choice for long documents and large codebases.
Based on current LLM Stats indexes, shared benchmarks, pricing, and model metadata for 2026.
Choose MiniMax M3
- cost matters — it's about 2.1x cheaper per token
- you need open weights you can self-host or fine-tune
Choose Mistral Large 4
- overall performance matters — it scores 45.8 and ranks #39 on LLM Stats
- your work emphasizes agents — it leads those capability indexes
- you value its reported benchmark strengths — it wins 2 of 2 exact shared results
- you process long inputs — it offers a 1,000,000 token context window
- you want the most recent training data — it shipped Oct 2026
At a glance
The differences that matter most.
Capability indexes
Additional strengths measured across groups of related public benchmarks
Individual benchmarks
35 reported for MiniMax M3 · 18 for Mistral Large 4
MiniMax M3 outperforms in 0 benchmarks, while Mistral Large 4 is better at 2 benchmarks (Finance Agent v2, SWE Atlas - Codebase QnA).
Mistral Large 4 significantly outperforms across most benchmarks.
Human preference
Blind head-to-head votes and playground preference scores
Pricing Analysis
Price comparison per million tokens
For input processing, MiniMax M3 ($0.28/1M tokens) is 2.4x cheaper than Mistral Large 4 ($0.68/1M tokens).
For output processing, MiniMax M3 ($1.10/1M tokens) is 1.9x cheaper than Mistral Large 4 ($2.09/1M tokens).
In conclusion, Mistral Large 4 is more expensive than MiniMax M3.*
* Using a 3:1 ratio of input to output tokens
Model Size
Parameter count comparison
Mistral Large 4 has 622.0B more parameters than MiniMax M3, making it 145.3% larger.
Context Window
Maximum input and output token capacity
Mistral Large 4 accepts 1,000,000 input tokens compared to MiniMax M3's 524,288 tokens. Only MiniMax M3 specifies output context (524,288 tokens).
Input capabilities
Documented input modalities across available providers
Both MiniMax M3 and Mistral Large 4 support multimodal inputs.
They are both capable of processing various types of data, offering versatility in application.
MiniMax M3
Mistral Large 4
License
Usage and distribution terms
MiniMax M3 is licensed under MIT, while Mistral Large 4 uses a proprietary license.
License differences may affect how you can use these models in commercial or open-source projects.
MIT
Open weights
Proprietary
Closed source
Release Timeline
When each model was launched
MiniMax M3 was released on 2026-06-01, while Mistral Large 4 was released on 2026-10-06.
Mistral Large 4 is 4 months newer than MiniMax M3.
Jun 1, 2026
4 months ago
Oct 6, 2026
2 weeks ago
4mo newerKnowledge Cutoff
When training data ends
Neither model specifies a knowledge cutoff date.
Unable to compare the recency of their training data.
Provider Availability
MiniMax M3 is available from DeepInfra, Fireworks, MiniMax, Novita, Together. Mistral Large 4 is available from Mistral AI.
MiniMax M3
Mistral Large 4
Outputs Comparison
Judge for yourself.
Run your own prompts against MiniMax M3 and Mistral Large 4 side-by-side, then vote on the output you prefer.
FAQ
Common questions about MiniMax M3 vs Mistral Large 4.