GPT-4o mini vs Mistral Large 2
GPT-4o mini and Mistral Large 2 are closely matched at 3.8 and 7.7 on the LLM Stats Score. GPT-4o mini is 11.4x cheaper per token.
OpenAI · Mistral AI · Updated for 2026
Which is better?
GPT-4o mini and Mistral Large 2 are closely matched on the overall LLM Stats Score at 3.8 and 7.7.
In the 2 individual benchmarks reported for both models, Mistral Large 2 wins 2; this is a narrower head-to-head signal than the composite indexes.
On price, GPT-4o mini is roughly 11.4x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
Based on current LLM Stats indexes, shared benchmarks, pricing, and model metadata for 2026.
Choose GPT-4o mini
- cost matters — it's about 11.4x cheaper per token
Choose Mistral Large 2
- your work emphasizes coding — it leads those capability indexes
- you value its reported benchmark strengths — it wins 2 of 2 exact shared results
- 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
9 reported for GPT-4o mini · 5 for Mistral Large 2
GPT-4o mini outperforms in 0 benchmarks, while Mistral Large 2 is better at 2 benchmarks (HumanEval, MMLU).
Mistral Large 2 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-4o mini ($0.15/1M tokens) is 13.3x cheaper than Mistral Large 2 ($2.00/1M tokens).
For output processing, GPT-4o mini ($0.60/1M tokens) is 10.0x cheaper than Mistral Large 2 ($6.00/1M tokens).
In conclusion, Mistral Large 2 is more expensive than GPT-4o mini.*
* Using a 3:1 ratio of input to output tokens
Context Window
Maximum input and output token capacity
Both models have the same input context window of 128,000 tokens. Mistral Large 2 can generate longer responses up to 128,000 tokens, while GPT-4o mini is limited to 16,384 tokens.
Input capabilities
Documented input modalities across available providers
GPT-4o mini supports multimodal inputs, whereas Mistral Large 2 does not.
GPT-4o mini can handle both text and other forms of data like images, making it suitable for multimodal applications.
GPT-4o mini
Mistral Large 2
License
Usage and distribution terms
GPT-4o mini 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-4o mini was released on 2024-07-18, while Mistral Large 2 was released on 2024-07-24.
Mistral Large 2 is 0 month newer than GPT-4o mini.
Jul 18, 2024
2.1 years ago
Jul 24, 2024
2.1 years ago
6d newerKnowledge Cutoff
When training data ends
GPT-4o mini has a documented knowledge cutoff of 2023-10-01, while Mistral Large 2's cutoff date is not specified.
We can confirm GPT-4o mini's training data extends to 2023-10-01, but cannot make a direct comparison without Mistral Large 2's cutoff date.
Oct 2023
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Provider Availability
GPT-4o mini is available from Azure. Mistral Large 2 is available from Google, Mistral AI.
GPT-4o mini
Mistral Large 2
Outputs Comparison
Judge for yourself.
Run your own prompts against GPT-4o mini and Mistral Large 2 side-by-side, then vote on the output you prefer.
FAQ
Common questions about GPT-4o mini vs Mistral Large 2.