Gemma 3 4B vs Mistral Large 4
Mistral Large 4 leads the LLM Stats Score 46.2 to -1.9. Gemma 3 4B is 41.3x cheaper per token.
Google · Mistral AI · Updated for 2026
Which is better?
Mistral Large 4 leads the overall LLM Stats Score 46.2 to -1.9, ranking #34 overall.
On price, Gemma 3 4B is roughly 41.3x 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 3 4B
- cost matters — it's about 41.3x 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 coding — 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
26 reported for Gemma 3 4B · 18 for Mistral Large 4
Gemma 3 4B 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 3 4B ($0.02/1M tokens) is 34.0x cheaper than Mistral Large 4 ($0.68/1M tokens).
For output processing, Gemma 3 4B ($0.04/1M tokens) is 52.2x cheaper than Mistral Large 4 ($2.09/1M tokens).
In conclusion, Mistral Large 4 is more expensive than Gemma 3 4B.*
* Using a 3:1 ratio of input to output tokens
Model Size
Parameter count comparison
Mistral Large 4 has 1046.0B more parameters than Gemma 3 4B, making it 26150.0% larger.
Context Window
Maximum input and output token capacity
Mistral Large 4 accepts 1,000,000 input tokens compared to Gemma 3 4B's 131,072 tokens. Only Gemma 3 4B specifies output context (131,072 tokens).
Input capabilities
Documented input modalities across available providers
Both Gemma 3 4B and Mistral Large 4 support multimodal inputs.
They are both capable of processing various types of data, offering versatility in application.
Gemma 3 4B
Mistral Large 4
License
Usage and distribution terms
Gemma 3 4B is licensed under Gemma, while Mistral Large 4 uses a proprietary license.
License differences may affect how you can use these models in commercial or open-source projects.
Gemma
Open weights
Proprietary
Closed source
Release Timeline
When each model was launched
Gemma 3 4B was released on 2025-03-12, while Mistral Large 4 was released on 2026-10-06.
Mistral Large 4 is 19 months newer than Gemma 3 4B.
Mar 12, 2025
1.6 years ago
Oct 6, 2026
1 days ago
1.6yr newerKnowledge Cutoff
When training data ends
Gemma 3 4B has a documented knowledge cutoff of 2024-08-01, while Mistral Large 4's cutoff date is not specified.
We can confirm Gemma 3 4B's training data extends to 2024-08-01, but cannot make a direct comparison without Mistral Large 4's cutoff date.
Aug 2024
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Provider Availability
Gemma 3 4B is available from DeepInfra. Mistral Large 4 is available from Mistral AI.
Gemma 3 4B
Mistral Large 4
Outputs Comparison
Judge for yourself.
Run your own prompts against Gemma 3 4B and Mistral Large 4 side-by-side, then vote on the output you prefer.
FAQ
Common questions about Gemma 3 4B vs Mistral Large 4.