Model Comparison
Gemini 3.5 Flash vs Mistral Medium 3.5Which is better in 2026?
Gemini 3.5 Flash significantly outperforms across most benchmarks. Mistral Medium 3.5 is 1.1x cheaper per token.
Verdict: Gemini 3.5 Flash vs Mistral Medium 3.5 — which is better?
Gemini 3.5 Flash (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 3.5 Flash outperforms in 2 benchmarks (Finance Agent v2, GDPval-AA), while Mistral Medium 3.5 is better at 0 benchmarks. Gemini 3.5 Flash significantly outperforms across most benchmarks.
On price, Mistral Medium 3.5 is roughly 1.1x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
Gemini 3.5 Flash also accepts a larger context window (1,048,576 input tokens), making it the stronger choice for long documents and large codebases.
Choose Gemini 3.5 Flash 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
- you want the most recent training data — it shipped May 2026
Choose Mistral Medium 3.5 if…
- cost matters — it's about 1.1x cheaper per token
- you need open weights you can self-host or fine-tune
Performance Benchmarks
Comparative analysis across standard metrics
Gemini 3.5 Flash outperforms in 2 benchmarks (Finance Agent v2, GDPval-AA), while Mistral Medium 3.5 is better at 0 benchmarks.
Gemini 3.5 Flash significantly outperforms across most benchmarks.
Arena Performance
Human preference votes
Pricing Analysis
Price comparison per million tokens
For input processing, Gemini 3.5 Flash ($1.50/1M tokens) costs the same as Mistral Medium 3.5 ($1.50/1M tokens).
For output processing, Gemini 3.5 Flash ($9.00/1M tokens) is 1.2x more expensive than Mistral Medium 3.5 ($7.50/1M tokens).
In conclusion, Gemini 3.5 Flash 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 3.5 Flash 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 3.5 Flash is limited to 65,536 tokens.
Input Capabilities
Supported data types and modalities
Both Gemini 3.5 Flash and Mistral Medium 3.5 support multimodal inputs.
They are both capable of processing various types of data, offering versatility in application.
Gemini 3.5 Flash
Mistral Medium 3.5
License
Usage and distribution terms
Gemini 3.5 Flash 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 3.5 Flash was released on 2026-05-19, while Mistral Medium 3.5 was released on 2026-04-29.
Gemini 3.5 Flash is 1 month newer than Mistral Medium 3.5.
May 19, 2026
1 months ago
2w newerApr 29, 2026
2 months ago
Knowledge Cutoff
When training data ends
Gemini 3.5 Flash has a documented knowledge cutoff of 2026-01-31, while Mistral Medium 3.5's cutoff date is not specified.
We can confirm Gemini 3.5 Flash's training data extends to 2026-01-31, but cannot make a direct comparison without Mistral Medium 3.5's cutoff date.
Jan 2026
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Provider Availability
Gemini 3.5 Flash is available from Google. Mistral Medium 3.5 is available from Mistral AI.
Gemini 3.5 Flash
Mistral Medium 3.5
Outputs Comparison
Key Takeaways
Mistral Medium 3.5
View detailsMistral AI
Detailed Comparison
Interactive Arena
Judge for yourself.
Run your own prompts against Gemini 3.5 Flash and Mistral Medium 3.5 side-by-side, then vote on the output you prefer.
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FAQ
Common questions about Gemini 3.5 Flash vs Mistral Medium 3.5.