GPT-5 nano vs Mistral Medium 3.5
GPT-5 nano and Mistral Medium 3.5 are closely matched at 19.1 and 26.6 on the LLM Stats Score. GPT-5 nano is 21.8x cheaper per token.
OpenAI · Mistral AI · Updated for 2026
Which is better?
GPT-5 nano and Mistral Medium 3.5 are closely matched on the overall LLM Stats Score at 19.1 and 26.6.
In the 1 individual benchmarks reported for both models, Mistral Medium 3.5 wins 1; this is a narrower head-to-head signal than the composite indexes.
On price, GPT-5 nano is roughly 21.8x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
GPT-5 nano also accepts a larger context window (400,000 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 GPT-5 nano
- cost matters — it's about 21.8x cheaper per token
- you process long inputs — it offers a 400,000 token context window
Choose Mistral Medium 3.5
- you value its reported benchmark strengths — it wins 1 of 1 exact shared results
- you want the most recent training data — it shipped Apr 2026
- you need open weights you can self-host or fine-tune
At a glance
The differences that matter most.
Capability indexes
Additional strengths measured across groups of related public benchmarks
Individual benchmarks
5 reported for GPT-5 nano · 11 for Mistral Medium 3.5
GPT-5 nano outperforms in 0 benchmarks, while Mistral Medium 3.5 is better at 1 benchmark (AIME 2025).
Mistral Medium 3.5 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, GPT-5 nano ($0.05/1M tokens) is 30.0x cheaper than Mistral Medium 3.5 ($1.50/1M tokens).
For output processing, GPT-5 nano ($0.40/1M tokens) is 18.8x cheaper than Mistral Medium 3.5 ($7.50/1M tokens).
In conclusion, Mistral Medium 3.5 is more expensive than GPT-5 nano.*
* Using a 3:1 ratio of input to output tokens
Context Window
Maximum input and output token capacity
GPT-5 nano accepts 400,000 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 GPT-5 nano is limited to 128,000 tokens.
Input capabilities
Documented input modalities across available providers
Both GPT-5 nano and Mistral Medium 3.5 support multimodal inputs.
They are both capable of processing various types of data, offering versatility in application.
GPT-5 nano
Mistral Medium 3.5
License
Usage and distribution terms
GPT-5 nano 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
GPT-5 nano was released on 2025-08-07, while Mistral Medium 3.5 was released on 2026-04-29.
Mistral Medium 3.5 is 9 months newer than GPT-5 nano.
Aug 7, 2025
1.2 years ago
Apr 29, 2026
5 months ago
8mo newerKnowledge Cutoff
When training data ends
GPT-5 nano has a documented knowledge cutoff of 2024-05-30, while Mistral Medium 3.5's cutoff date is not specified.
We can confirm GPT-5 nano's training data extends to 2024-05-30, but cannot make a direct comparison without Mistral Medium 3.5's cutoff date.
May 2024
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Provider Availability
GPT-5 nano is available from OpenAI. Mistral Medium 3.5 is available from Mistral AI.
GPT-5 nano
Mistral Medium 3.5
Outputs Comparison
Judge for yourself.
Run your own prompts against GPT-5 nano and Mistral Medium 3.5 side-by-side, then vote on the output you prefer.
FAQ
Common questions about GPT-5 nano vs Mistral Medium 3.5.