Model Comparison
Gemini 3.1 Pro vs Mistral Medium 3.5Which is better in 2026?
Gemini 3.1 Pro significantly outperforms across most benchmarks. Mistral Medium 3.5 is 1.9x cheaper per token.
Verdict: Gemini 3.1 Pro vs Mistral Medium 3.5 — which is better?
Gemini 3.1 Pro (by Google) and Mistral Medium 3.5 (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.
Gemini 3.1 Pro outperforms in 2 benchmarks (BrowseComp, SWE-Bench Verified), while Mistral Medium 3.5 is better at 0 benchmarks. Gemini 3.1 Pro significantly outperforms across most benchmarks.
On price, Mistral Medium 3.5 is roughly 1.9x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
Gemini 3.1 Pro also accepts a larger context window (1,048,576 input tokens), making it the stronger choice for long documents and large codebases.
Choose Gemini 3.1 Pro if…
- you want the strongest raw capability — it leads on 2 of 2 shared benchmarks
- you process long inputs — it offers a 1,048,576 token context window
Choose Mistral Medium 3.5 if…
- cost matters — it's about 1.9x cheaper per token
- you want the most recent training data — it shipped Apr 2026
- you need open weights you can self-host or fine-tune
Performance Benchmarks
Comparative analysis across standard metrics
Gemini 3.1 Pro outperforms in 2 benchmarks (BrowseComp, SWE-Bench Verified), while Mistral Medium 3.5 is better at 0 benchmarks.
Gemini 3.1 Pro significantly outperforms across most benchmarks.
Arena Performance
Human preference votes
Pricing Analysis
Price comparison per million tokens
For input processing, Gemini 3.1 Pro ($2.50/1M tokens) is 1.7x more expensive than Mistral Medium 3.5 ($1.50/1M tokens).
For output processing, Gemini 3.1 Pro ($15.00/1M tokens) is 2.0x more expensive than Mistral Medium 3.5 ($7.50/1M tokens).
In conclusion, Gemini 3.1 Pro is more expensive than Mistral Medium 3.5.*
* Using a 3:1 ratio of input to output tokens
Context Window
Maximum input and output token capacity
Gemini 3.1 Pro accepts 1,048,576 input tokens compared to Mistral Medium 3.5's 256,000 tokens. Mistral Medium 3.5 can generate longer responses up to 256,000 tokens, while Gemini 3.1 Pro is limited to 65,536 tokens.
Input Capabilities
Supported data types and modalities
Both Gemini 3.1 Pro and Mistral Medium 3.5 support multimodal inputs.
They are both capable of processing various types of data, offering versatility in application.
Gemini 3.1 Pro
Mistral Medium 3.5
License
Usage and distribution terms
Gemini 3.1 Pro is licensed under a proprietary license, while Mistral Medium 3.5 uses Modified MIT License.
License differences may affect how you can use these models in commercial or open-source projects.
Proprietary
Closed source
Modified MIT License
Open weights
Release Timeline
When each model was launched
Gemini 3.1 Pro was released on 2026-02-19, while Mistral Medium 3.5 was released on 2026-04-29.
Mistral Medium 3.5 is 2 months newer than Gemini 3.1 Pro.
Feb 19, 2026
3 months ago
Apr 29, 2026
1 months ago
2mo newerKnowledge Cutoff
When training data ends
Gemini 3.1 Pro has a documented knowledge cutoff of 2025-01-31, while Mistral Medium 3.5's cutoff date is not specified.
We can confirm Gemini 3.1 Pro's training data extends to 2025-01-31, but cannot make a direct comparison without Mistral Medium 3.5's cutoff date.
Jan 2025
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Provider Availability
Gemini 3.1 Pro is available from Google. Mistral Medium 3.5 is available from Mistral AI.
Gemini 3.1 Pro
Mistral Medium 3.5
Outputs Comparison
Key Takeaways
Mistral Medium 3.5
View detailsMistral AI
Detailed Comparison
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FAQ
Common questions about Gemini 3.1 Pro vs Mistral Medium 3.5.