Mistral Large 3 vs o3-mini
o3-mini leads the LLM Stats Score 21.8 to 11.0. o3-mini is 1.4x cheaper per token.
Mistral AI · OpenAI · Updated for 2026
Which is better?
o3-mini leads the overall LLM Stats Score 21.8 to 11.0, ranking #169 overall.
In the 1 individual benchmarks reported for both models, o3-mini wins 1; this is a narrower head-to-head signal than the composite indexes.
On price, o3-mini is roughly 1.4x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
o3-mini also accepts a larger context window (200,000 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 Mistral Large 3
- you want the most recent training data — it shipped Sep 2025
- you need open weights you can self-host or fine-tune
Choose o3-mini
- overall performance matters — it scores 21.8 and ranks #169 on LLM Stats
- your work emphasizes reasoning — it leads those capability indexes
- you value its reported benchmark strengths — it wins 1 of 1 exact shared results
- cost matters — it's about 1.4x cheaper per token
- you process long inputs — it offers a 200,000 token context window
At a glance
The differences that matter most.
Capability indexes
Additional strengths measured across groups of related public benchmarks
Individual benchmarks
8 reported for Mistral Large 3 · 25 for o3-mini
Mistral Large 3 outperforms in 0 benchmarks, while o3-mini is better at 1 benchmark (MATH).
o3-mini 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, Mistral Large 3 ($2.00/1M tokens) is 1.8x more expensive than o3-mini ($1.10/1M tokens).
For output processing, Mistral Large 3 ($5.00/1M tokens) is 1.1x more expensive than o3-mini ($4.40/1M tokens).
In conclusion, Mistral Large 3 is more expensive than o3-mini.*
* Using a 3:1 ratio of input to output tokens
Context Window
Maximum input and output token capacity
o3-mini accepts 200,000 input tokens compared to Mistral Large 3's 128,000 tokens. o3-mini can generate longer responses up to 100,000 tokens, while Mistral Large 3 is limited to 8,192 tokens.
Input capabilities
Documented input modalities across available providers
Mistral Large 3 supports multimodal inputs, whereas o3-mini does not.
Mistral Large 3 can handle both text and other forms of data like images, making it suitable for multimodal applications.
Mistral Large 3
o3-mini
License
Usage and distribution terms
Mistral Large 3 is licensed under Apache 2.0, while o3-mini uses a proprietary license.
License differences may affect how you can use these models in commercial or open-source projects.
Apache 2.0
Open weights
Proprietary
Closed source
Release Timeline
When each model was launched
Mistral Large 3 was released on 2025-09-01, while o3-mini was released on 2025-01-30.
Mistral Large 3 is 7 months newer than o3-mini.
Sep 1, 2025
12 months ago
7mo newerJan 30, 2025
1.6 years ago
Knowledge Cutoff
When training data ends
o3-mini has a documented knowledge cutoff of 2023-09-30, while Mistral Large 3's cutoff date is not specified.
We can confirm o3-mini's training data extends to 2023-09-30, but cannot make a direct comparison without Mistral Large 3's cutoff date.
—
Sep 2023
Provider Availability
Mistral Large 3 is available from Mistral AI. o3-mini is available from Azure, OpenAI.
Mistral Large 3
o3-mini
Outputs Comparison
Judge for yourself.
Run your own prompts against Mistral Large 3 and o3-mini side-by-side, then vote on the output you prefer.
FAQ
Common questions about Mistral Large 3 vs o3-mini.