Phi 4 vs Pixtral-12B
Phi 4 leads the LLM Stats Score 5.4 to -1.6. Phi 4 is 1.7x cheaper per token.
Microsoft · Mistral AI · Updated for 2026
Which is better?
Phi 4 leads the overall LLM Stats Score 5.4 to -1.6, ranking #296 overall.
In the 4 individual benchmarks reported for both models, Phi 4 wins 4; this is a narrower head-to-head signal than the composite indexes.
On price, Phi 4 is roughly 1.7x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
Pixtral-12B 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 Phi 4
- overall performance matters — it scores 5.4 and ranks #296 on LLM Stats
- your work emphasizes reasoning — it leads those capability indexes
- you value its reported benchmark strengths — it wins 4 of 4 exact shared results
- cost matters — it's about 1.7x cheaper per token
- you want the most recent training data — it shipped Dec 2024
Choose Pixtral-12B
- you process long inputs — it offers a 128,000 token context window
At a glance
The differences that matter most.
Capability indexes
Additional strengths measured across groups of related public benchmarks
Individual benchmarks
13 reported for Phi 4 · 12 for Pixtral-12B
Phi 4 outperforms in 4 benchmarks (HumanEval, IFEval, MATH, MMLU), while Pixtral-12B is better at 0 benchmarks.
Phi 4 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, Phi 4 ($0.07/1M tokens) is 2.1x cheaper than Pixtral-12B ($0.15/1M tokens).
For output processing, Phi 4 ($0.14/1M tokens) is 1.1x cheaper than Pixtral-12B ($0.15/1M tokens).
In conclusion, Pixtral-12B is more expensive than Phi 4.*
* Using a 3:1 ratio of input to output tokens
Model Size
Parameter count comparison
Phi 4 has 2.3B more parameters than Pixtral-12B, making it 18.5% larger.
Context Window
Maximum input and output token capacity
Pixtral-12B accepts 128,000 input tokens compared to Phi 4's 16,384 tokens. Phi 4 can generate longer responses up to 16,384 tokens, while Pixtral-12B is limited to 8,192 tokens.
Input capabilities
Documented input modalities across available providers
Pixtral-12B supports multimodal inputs, whereas Phi 4 does not.
Pixtral-12B can handle both text and other forms of data like images, making it suitable for multimodal applications.
Phi 4
Pixtral-12B
License
Usage and distribution terms
Phi 4 is licensed under MIT, while Pixtral-12B uses Apache 2.0.
License differences may affect how you can use these models in commercial or open-source projects.
MIT
Open weights
Apache 2.0
Open weights
Release Timeline
When each model was launched
Phi 4 was released on 2024-12-12, while Pixtral-12B was released on 2024-09-17.
Phi 4 is 3 months newer than Pixtral-12B.
Dec 12, 2024
1.8 years ago
2mo newerSep 17, 2024
2.0 years ago
Knowledge Cutoff
When training data ends
Phi 4 has a documented knowledge cutoff of 2024-06-01, while Pixtral-12B's cutoff date is not specified.
We can confirm Phi 4's training data extends to 2024-06-01, but cannot make a direct comparison without Pixtral-12B's cutoff date.
Jun 2024
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Provider Availability
Phi 4 is available from DeepInfra. Pixtral-12B is available from Mistral AI.
Phi 4
Pixtral-12B
Outputs Comparison
Judge for yourself.
Run your own prompts against Phi 4 and Pixtral-12B side-by-side, then vote on the output you prefer.
FAQ
Common questions about Phi 4 vs Pixtral-12B.