GPT-5 nano vs Mistral Small 3.1 24B Base
GPT-5 nano significantly outperforms across most benchmarks. GPT-5 nano is 1.1x cheaper per token.
OpenAI · Mistral AI · Updated for 2026
Which is better?
GPT-5 nano outperforms in 1 benchmarks (GPQA), while Mistral Small 3.1 24B Base is better at 0 benchmarks. GPT-5 nano significantly outperforms across most benchmarks.
On price, GPT-5 nano is roughly 1.1x 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 benchmark, pricing, and model metadata for 2026.
Choose GPT-5 nano
- you want the strongest raw capability — it leads on 1 of 1 shared benchmarks
- cost matters — it's about 1.1x cheaper per token
- you process long inputs — it offers a 400,000 token context window
- you want the most recent training data — it shipped Aug 2025
Choose Mistral Small 3.1 24B Base
- you need open weights you can self-host or fine-tune
At a glance
The differences that matter most.
Performance Benchmarks
Comparative analysis across standard metrics
GPT-5 nano outperforms in 1 benchmarks (GPQA), while Mistral Small 3.1 24B Base is better at 0 benchmarks.
GPT-5 nano significantly outperforms across most benchmarks.
Arena Performance
Playground indexes and blind preference scores
Pricing Analysis
Price comparison per million tokens
For input processing, GPT-5 nano ($0.05/1M tokens) is 2.0x cheaper than Mistral Small 3.1 24B Base ($0.10/1M tokens).
For output processing, GPT-5 nano ($0.40/1M tokens) is 1.3x more expensive than Mistral Small 3.1 24B Base ($0.30/1M tokens).
In conclusion, Mistral Small 3.1 24B Base 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 3.1 24B Base's 128,000 tokens. Both models can generate responses up to 128,000 tokens.
Input Capabilities
Supported data types and modalities
Both GPT-5 nano and Mistral Small 3.1 24B Base support multimodal inputs.
They are both capable of processing various types of data, offering versatility in application.
GPT-5 nano
Mistral Small 3.1 24B Base
License
Usage and distribution terms
GPT-5 nano is licensed under a proprietary license, while Mistral Small 3.1 24B Base 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 3.1 24B Base was released on 2025-03-17.
GPT-5 nano is 5 months newer than Mistral Small 3.1 24B Base.
Aug 7, 2025
1.0 years ago
4mo newerMar 17, 2025
1.4 years ago
Knowledge Cutoff
When training data ends
GPT-5 nano has a documented knowledge cutoff of 2024-05-30, while Mistral Small 3.1 24B Base'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 3.1 24B Base's cutoff date.
May 2024
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Provider Availability
GPT-5 nano is available from OpenAI. Mistral Small 3.1 24B Base is available from Mistral AI.
GPT-5 nano
Mistral Small 3.1 24B Base
Outputs Comparison
Judge for yourself.
Run your own prompts against GPT-5 nano and Mistral Small 3.1 24B Base side-by-side, then vote on the output you prefer.
FAQ
Common questions about GPT-5 nano vs Mistral Small 3.1 24B Base.