Mistral Large 4 vs Qwen3.7 Max
Mistral Large 4 and Qwen3.7 Max are closely matched at 46.2 and 45.2 on the LLM Stats Score. Mistral Large 4 is 1.8x cheaper per token.
Mistral AI · Alibaba Cloud / Qwen Team · Updated for 2026
Which is better?
Mistral Large 4 and Qwen3.7 Max are closely matched on the overall LLM Stats Score at 46.2 and 45.2.
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, Mistral Large 4 is roughly 1.8x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
Based on current LLM Stats indexes, shared benchmarks, pricing, and model metadata for 2026.
Choose Mistral Large 4
- your work emphasizes agents — it leads those capability indexes
- you value its reported benchmark strengths — it wins 2 of 2 exact shared results
- cost matters — it's about 1.8x cheaper per token
- you want the most recent training data — it shipped Oct 2026
Choose Qwen3.7 Max
- you want predictable pricing at $1.25/M input and $3.75/M output
At a glance
The differences that matter most.
Capability indexes
Additional strengths measured across groups of related public benchmarks
Individual benchmarks
18 reported for Mistral Large 4 · 42 for Qwen3.7 Max
Mistral Large 4 outperforms in 2 benchmarks (Finance Agent v2, SciCode), while Qwen3.7 Max is better at 0 benchmarks.
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, Mistral Large 4 ($0.68/1M tokens) is 1.8x cheaper than Qwen3.7 Max ($1.25/1M tokens).
For output processing, Mistral Large 4 ($2.09/1M tokens) is 1.8x cheaper than Qwen3.7 Max ($3.75/1M tokens).
In conclusion, Qwen3.7 Max is more expensive than Mistral Large 4.*
* Using a 3:1 ratio of input to output tokens
Context Window
Maximum input and output token capacity
Both models have the same input context window of 1,000,000 tokens. Only Qwen3.7 Max specifies output context (65,536 tokens).
Input capabilities
Documented input modalities across available providers
Mistral Large 4 supports multimodal inputs, whereas Qwen3.7 Max does not.
Mistral Large 4 can handle both text and other forms of data like images, making it suitable for multimodal applications.
Mistral Large 4
Qwen3.7 Max
License
Usage and distribution terms
Both models are licensed under proprietary licenses.
Both models have usage restrictions defined by their respective organizations.
Proprietary
Closed source
Proprietary
Closed source
Release Timeline
When each model was launched
Mistral Large 4 was released on 2026-10-06, while Qwen3.7 Max was released on 2026-05-19.
Mistral Large 4 is 5 months newer than Qwen3.7 Max.
Oct 6, 2026
6 days ago
4mo newerMay 19, 2026
4 months 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
Mistral Large 4 is available from Mistral AI. Qwen3.7 Max is available from Novita, DeepInfra, Together.
Mistral Large 4
Qwen3.7 Max
Outputs Comparison
Judge for yourself.
Run your own prompts against Mistral Large 4 and Qwen3.7 Max side-by-side, then vote on the output you prefer.
FAQ
Common questions about Mistral Large 4 vs Qwen3.7 Max.