Gemma 4 31B vs Mistral Large 4
Mistral Large 4 leads the LLM Stats Score 46.2 to 33.0. Gemma 4 31B is 6.8x cheaper per token.
Google · Mistral AI · Updated for 2026
Which is better?
Mistral Large 4 leads the overall LLM Stats Score 46.2 to 33.0, ranking #34 overall.
On price, Gemma 4 31B is roughly 6.8x 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 Gemma 4 31B
- cost matters — it's about 6.8x cheaper per token
- you need open weights you can self-host or fine-tune
Choose Mistral Large 4
- overall performance matters — it scores 46.2 and ranks #34 on LLM Stats
- your work emphasizes reasoning and agents — it leads those capability indexes
- 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
12 reported for Gemma 4 31B · 18 for Mistral Large 4
Gemma 4 31B and Mistral Large 4don't have any common benchmark datasets to compare. They may have been evaluated on different testing suites.
Human preference
Blind head-to-head votes and playground preference scores
Pricing Analysis
Price comparison per million tokens
For input processing, Gemma 4 31B ($0.09/1M tokens) is 7.6x cheaper than Mistral Large 4 ($0.68/1M tokens).
For output processing, Gemma 4 31B ($0.34/1M tokens) is 6.1x cheaper than Mistral Large 4 ($2.09/1M tokens).
In conclusion, Mistral Large 4 is more expensive than Gemma 4 31B.*
* Using a 3:1 ratio of input to output tokens
Model Size
Parameter count comparison
Mistral Large 4 has 1019.3B more parameters than Gemma 4 31B, making it 3320.2% larger.
Context Window
Maximum input and output token capacity
Mistral Large 4 accepts 1,000,000 input tokens compared to Gemma 4 31B's 262,144 tokens. Only Gemma 4 31B specifies output context (262,144 tokens).
Input capabilities
Documented input modalities across available providers
Both Gemma 4 31B and Mistral Large 4 support multimodal inputs.
They are both capable of processing various types of data, offering versatility in application.
Gemma 4 31B
Mistral Large 4
License
Usage and distribution terms
Gemma 4 31B is licensed under Apache 2.0, while Mistral Large 4 uses a proprietary license.
License differences may affect how you can use these models in commercial or open-source projects.
Apache 2.0
Open weights
Proprietary
Closed source
Release Timeline
When each model was launched
Gemma 4 31B was released on 2026-04-02, while Mistral Large 4 was released on 2026-10-06.
Mistral Large 4 is 6 months newer than Gemma 4 31B.
Apr 2, 2026
6 months ago
Oct 6, 2026
2 days ago
6mo newerKnowledge Cutoff
When training data ends
Gemma 4 31B has a documented knowledge cutoff of 2025-01-01, while Mistral Large 4's cutoff date is not specified.
We can confirm Gemma 4 31B's training data extends to 2025-01-01, but cannot make a direct comparison without Mistral Large 4's cutoff date.
Jan 2025
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Provider Availability
Gemma 4 31B is available from DeepInfra, FriendliAI, Novita, Together. Mistral Large 4 is available from Mistral AI.
Gemma 4 31B
Mistral Large 4
Outputs Comparison
Judge for yourself.
Run your own prompts against Gemma 4 31B and Mistral Large 4 side-by-side, then vote on the output you prefer.
FAQ
Common questions about Gemma 4 31B vs Mistral Large 4.