GPT-4 vs Mistral Large 2
GPT-4 and Mistral Large 2 are closely matched at 3.3 and 7.8 on the LLM Stats Score. Mistral Large 2 is 12.5x cheaper per token.
OpenAI · Mistral AI · Updated for 2026
Which is better?
GPT-4 and Mistral Large 2 are closely matched on the overall LLM Stats Score at 3.3 and 7.8.
The models split the 2 individual benchmarks reported for both models evenly.
On price, Mistral Large 2 is roughly 12.5x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
Mistral Large 2 also accepts a larger context window (128,000 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-4
- you want predictable pricing at $30.00/M input and $60.00/M output
Choose Mistral Large 2
- your work emphasizes coding — it leads those capability indexes
- cost matters — it's about 12.5x cheaper per token
- you process long inputs — it offers a 128,000 token context window
- you want the most recent training data — it shipped Jul 2024
- 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
12 reported for GPT-4 · 5 for Mistral Large 2
GPT-4 outperforms in 1 benchmarks (MMLU), while Mistral Large 2 is better at 1 benchmark (HumanEval).
Both models are evenly matched across the benchmarks.
Human preference
Blind head-to-head votes and playground preference scores
Pricing Analysis
Price comparison per million tokens
For input processing, GPT-4 ($30.00/1M tokens) is 15.0x more expensive than Mistral Large 2 ($2.00/1M tokens).
For output processing, GPT-4 ($60.00/1M tokens) is 10.0x more expensive than Mistral Large 2 ($6.00/1M tokens).
In conclusion, GPT-4 is more expensive than Mistral Large 2.*
* Using a 3:1 ratio of input to output tokens
Context Window
Maximum input and output token capacity
Mistral Large 2 accepts 128,000 input tokens compared to GPT-4's 32,768 tokens. Mistral Large 2 can generate longer responses up to 128,000 tokens, while GPT-4 is limited to 32,768 tokens.
Input capabilities
Documented input modalities across available providers
GPT-4 supports multimodal inputs, whereas Mistral Large 2 does not.
GPT-4 can handle both text and other forms of data like images, making it suitable for multimodal applications.
GPT-4
Mistral Large 2
License
Usage and distribution terms
GPT-4 is licensed under a proprietary license, while Mistral Large 2 uses Mistral Research License.
License differences may affect how you can use these models in commercial or open-source projects.
Proprietary
Closed source
Mistral Research License
Open weights
Release Timeline
When each model was launched
GPT-4 was released on 2023-06-13, while Mistral Large 2 was released on 2024-07-24.
Mistral Large 2 is 14 months newer than GPT-4.
Jun 13, 2023
3.2 years ago
Jul 24, 2024
2.1 years ago
1.1yr newerKnowledge Cutoff
When training data ends
GPT-4 has a documented knowledge cutoff of 2022-12-31, while Mistral Large 2'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 Large 2's cutoff date.
Dec 2022
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Provider Availability
GPT-4 is available from Azure, OpenAI. Mistral Large 2 is available from Google, Mistral AI.
GPT-4
Mistral Large 2
Outputs Comparison
Judge for yourself.
Run your own prompts against GPT-4 and Mistral Large 2 side-by-side, then vote on the output you prefer.
FAQ
Common questions about GPT-4 vs Mistral Large 2.