Mistral Large 3 vs o1
o1 leads the LLM Stats Score 20.9 to 10.4. Mistral Large 3 is 9.5x cheaper per token.
Mistral AI · OpenAI · Updated for 2026
Which is better?
o1 leads the overall LLM Stats Score 20.9 to 10.4, ranking #190 overall.
In the 2 individual benchmarks reported for both models, o1 wins 2; this is a narrower head-to-head signal than the composite indexes.
On price, Mistral Large 3 is roughly 9.5x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
o1 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
- cost matters — it's about 9.5x cheaper per token
- you want the most recent training data — it shipped Sep 2025
- you need open weights you can self-host or fine-tune
Choose o1
- overall performance matters — it scores 20.9 and ranks #190 on LLM Stats
- your work emphasizes reasoning — it leads those capability indexes
- you value its reported benchmark strengths — it wins 2 of 2 exact shared results
- 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 · 19 for o1
Mistral Large 3 outperforms in 0 benchmarks, while o1 is better at 2 benchmarks (MATH, MMMLU).
o1 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 7.5x cheaper than o1 ($15.00/1M tokens).
For output processing, Mistral Large 3 ($5.00/1M tokens) is 12.0x cheaper than o1 ($60.00/1M tokens).
In conclusion, o1 is more expensive than Mistral Large 3.*
* Using a 3:1 ratio of input to output tokens
Context Window
Maximum input and output token capacity
o1 accepts 200,000 input tokens compared to Mistral Large 3's 128,000 tokens. o1 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 o1 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
o1
License
Usage and distribution terms
Mistral Large 3 is licensed under Apache 2.0, while o1 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 o1 was released on 2024-12-17.
Mistral Large 3 is 9 months newer than o1.
Sep 1, 2025
1.0 years ago
8mo newerDec 17, 2024
1.7 years ago
Knowledge Cutoff
When training data ends
Neither model specifies a knowledge cutoff date.
Unable to compare the recency of their training data.
Provider Availability
Mistral Large 3 is available from Mistral AI. o1 is available from Azure, OpenAI.
Mistral Large 3
o1
Outputs Comparison
Judge for yourself.
Run your own prompts against Mistral Large 3 and o1 side-by-side, then vote on the output you prefer.
FAQ
Common questions about Mistral Large 3 vs o1.