o4-mini vs Pixtral-12B
o4-mini leads the LLM Stats Score 27.7 to -1.4. Pixtral-12B is 12.8x cheaper per token.
OpenAI · Mistral AI · Updated for 2026
Which is better?
o4-mini leads the overall LLM Stats Score 27.7 to -1.4, ranking #131 overall.
In the 2 individual benchmarks reported for both models, o4-mini wins 2; this is a narrower head-to-head signal than the composite indexes.
On price, Pixtral-12B is roughly 12.8x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
o4-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 o4-mini
- overall performance matters — it scores 27.7 and ranks #131 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
- you want the most recent training data — it shipped Apr 2025
Choose Pixtral-12B
- cost matters — it's about 12.8x cheaper per token
- 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
14 reported for o4-mini · 12 for Pixtral-12B
o4-mini outperforms in 2 benchmarks (MathVista, MMMU), while Pixtral-12B is better at 0 benchmarks.
o4-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, o4-mini ($1.10/1M tokens) is 7.3x more expensive than Pixtral-12B ($0.15/1M tokens).
For output processing, o4-mini ($4.40/1M tokens) is 29.3x more expensive than Pixtral-12B ($0.15/1M tokens).
In conclusion, o4-mini is more expensive than Pixtral-12B.*
* Using a 3:1 ratio of input to output tokens
Context Window
Maximum input and output token capacity
o4-mini accepts 200,000 input tokens compared to Pixtral-12B's 128,000 tokens. o4-mini can generate longer responses up to 100,000 tokens, while Pixtral-12B is limited to 8,192 tokens.
Input capabilities
Documented input modalities across available providers
Both o4-mini and Pixtral-12B support multimodal inputs.
They are both capable of processing various types of data, offering versatility in application.
o4-mini
Pixtral-12B
License
Usage and distribution terms
o4-mini is licensed under a proprietary license, while Pixtral-12B 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
o4-mini was released on 2025-04-16, while Pixtral-12B was released on 2024-09-17.
o4-mini is 7 months newer than Pixtral-12B.
Apr 16, 2025
1.4 years ago
7mo newerSep 17, 2024
2.0 years ago
Knowledge Cutoff
When training data ends
o4-mini has a documented knowledge cutoff of 2024-05-31, while Pixtral-12B's cutoff date is not specified.
We can confirm o4-mini's training data extends to 2024-05-31, but cannot make a direct comparison without Pixtral-12B's cutoff date.
May 2024
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Provider Availability
o4-mini is available from OpenAI. Pixtral-12B is available from Mistral AI.
o4-mini
Pixtral-12B
Outputs Comparison
Judge for yourself.
Run your own prompts against o4-mini and Pixtral-12B side-by-side, then vote on the output you prefer.
FAQ
Common questions about o4-mini vs Pixtral-12B.