Model Comparison
GPT-4 vs Mistral Small 3.1 24B BaseWhich is better in 2026?
Both models are evenly matched across the benchmarks. Mistral Small 3.1 24B Base is 250.0x cheaper per token.
Verdict: GPT-4 vs Mistral Small 3.1 24B Base — which is better?
GPT-4 (by OpenAI) and Mistral Small 3.1 24B Base (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.
GPT-4 outperforms in 1 benchmarks (MMLU), while Mistral Small 3.1 24B Base is better at 1 benchmark (GPQA). Both models are evenly matched across the benchmarks.
On price, Mistral Small 3.1 24B Base is roughly 250.0x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
Mistral Small 3.1 24B Base also accepts a larger context window (128,000 input tokens), making it the stronger choice for long documents and large codebases.
Choose GPT-4 if…
- you want predictable pricing at $30.00/M input and $60.00/M output
Choose Mistral Small 3.1 24B Base if…
- cost matters — it's about 250.0x cheaper per token
- you process long inputs — it offers a 128,000 token context window
- you want the most recent training data — it shipped Mar 2025
- you need open weights you can self-host or fine-tune
Performance Benchmarks
Comparative analysis across standard metrics
GPT-4 outperforms in 1 benchmarks (MMLU), while Mistral Small 3.1 24B Base is better at 1 benchmark (GPQA).
Both models are evenly matched across the benchmarks.
Arena Performance
Human preference votes
Pricing Analysis
Price comparison per million tokens
For input processing, GPT-4 ($30.00/1M tokens) is 300.0x more expensive than Mistral Small 3.1 24B Base ($0.10/1M tokens).
For output processing, GPT-4 ($60.00/1M tokens) is 200.0x more expensive than Mistral Small 3.1 24B Base ($0.30/1M tokens).
In conclusion, GPT-4 is more expensive than Mistral Small 3.1 24B Base.*
* Using a 3:1 ratio of input to output tokens
Context Window
Maximum input and output token capacity
Mistral Small 3.1 24B Base accepts 128,000 input tokens compared to GPT-4's 32,768 tokens. Mistral Small 3.1 24B Base can generate longer responses up to 128,000 tokens, while GPT-4 is limited to 32,768 tokens.
Input Capabilities
Supported data types and modalities
Both GPT-4 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-4
Mistral Small 3.1 24B Base
License
Usage and distribution terms
GPT-4 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-4 was released on 2023-06-13, while Mistral Small 3.1 24B Base was released on 2025-03-17.
Mistral Small 3.1 24B Base is 21 months newer than GPT-4.
Jun 13, 2023
3.1 years ago
Mar 17, 2025
1.3 years ago
1.8yr newerKnowledge Cutoff
When training data ends
GPT-4 has a documented knowledge cutoff of 2022-12-31, while Mistral Small 3.1 24B Base's cutoff date is not specified.
We can confirm GPT-4's training data extends to 2022-12-31, but cannot make a direct comparison without Mistral Small 3.1 24B Base's cutoff date.
Dec 2022
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Provider Availability
GPT-4 is available from Azure, OpenAI. Mistral Small 3.1 24B Base is available from Mistral AI.
GPT-4
Mistral Small 3.1 24B Base
Outputs Comparison
Key Takeaways
GPT-4
View detailsOpenAI
Mistral Small 3.1 24B Base
View detailsMistral AI
Detailed Comparison
Interactive Arena
Judge for yourself.
Run your own prompts against GPT-4 and Mistral Small 3.1 24B Base side-by-side, then vote on the output you prefer.
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FAQ
Common questions about GPT-4 vs Mistral Small 3.1 24B Base.