GPT-5 nano vs Mistral Small 4
GPT-5 nano and Mistral Small 4 are closely matched at 19.1 and 18.6 on the LLM Stats Score. GPT-5 nano is 1.9x cheaper per token.
OpenAI · Mistral AI · Updated for 2026
Which is better?
GPT-5 nano and Mistral Small 4 are closely matched on the overall LLM Stats Score at 19.1 and 18.6.
The models split the 2 individual benchmarks reported for both models evenly.
On price, GPT-5 nano is roughly 1.9x 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 1.9x cheaper per token
- you process long inputs — it offers a 400,000 token context window
Choose Mistral Small 4
- you want the most recent training data — it shipped Mar 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 · 9 for Mistral Small 4
GPT-5 nano outperforms in 1 benchmarks (AIME 2025), while Mistral Small 4 is better at 0 benchmarks.
GPT-5 nano has a slight edge in benchmark performance.
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 3.0x cheaper than Mistral Small 4 ($0.15/1M tokens).
For output processing, GPT-5 nano ($0.40/1M tokens) is 1.5x cheaper than Mistral Small 4 ($0.60/1M tokens).
In conclusion, Mistral Small 4 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 Small 4's 256,000 tokens. Mistral Small 4 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 Small 4 support multimodal inputs.
They are both capable of processing various types of data, offering versatility in application.
GPT-5 nano
Mistral Small 4
License
Usage and distribution terms
GPT-5 nano is licensed under a proprietary license, while Mistral Small 4 uses Apache 2.0.
License differences may affect how you can use these models in commercial or open-source projects.
Proprietary
Closed source
Apache 2.0
Open weights
Release Timeline
When each model was launched
GPT-5 nano was released on 2025-08-07, while Mistral Small 4 was released on 2026-03-16.
Mistral Small 4 is 7 months newer than GPT-5 nano.
Aug 7, 2025
1.2 years ago
Mar 16, 2026
7 months ago
7mo newerKnowledge Cutoff
When training data ends
GPT-5 nano has a documented knowledge cutoff of 2024-05-30, while Mistral Small 4'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 Small 4's cutoff date.
May 2024
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Provider Availability
GPT-5 nano is available from OpenAI. Mistral Small 4 is available from Mistral AI.
GPT-5 nano
Mistral Small 4
Outputs Comparison
Judge for yourself.
Run your own prompts against GPT-5 nano and Mistral Small 4 side-by-side, then vote on the output you prefer.
FAQ
Common questions about GPT-5 nano vs Mistral Small 4.