DeepSeek-V2.5 vs Pixtral-12B
DeepSeek-V2.5 significantly outperforms across most benchmarks. Pixtral-12B is 1.2x cheaper per token.
DeepSeek · Mistral AI · Updated for 2026
Which is better?
DeepSeek-V2.5 outperforms in 4 benchmarks (HumanEval, MATH, MMLU, MT-Bench), while Pixtral-12B is better at 0 benchmarks. DeepSeek-V2.5 significantly outperforms across most benchmarks.
On price, Pixtral-12B is roughly 1.2x 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 benchmark, pricing, and model metadata for 2026.
Choose DeepSeek-V2.5
- you want the strongest raw capability — it leads on 4 of 4 shared benchmarks
Choose Pixtral-12B
- cost matters — it's about 1.2x cheaper per token
- you process long inputs — it offers a 128,000 token context window
- you want the most recent training data — it shipped Sep 2024
At a glance
The differences that matter most.
Performance Benchmarks
Comparative analysis across standard metrics
DeepSeek-V2.5 outperforms in 4 benchmarks (HumanEval, MATH, MMLU, MT-Bench), while Pixtral-12B is better at 0 benchmarks.
DeepSeek-V2.5 significantly outperforms across most benchmarks.
Arena Performance
Playground indexes and blind preference scores
Pricing Analysis
Price comparison per million tokens
For input processing, DeepSeek-V2.5 ($0.14/1M tokens) is 1.1x cheaper than Pixtral-12B ($0.15/1M tokens).
For output processing, DeepSeek-V2.5 ($0.28/1M tokens) is 1.9x more expensive than Pixtral-12B ($0.15/1M tokens).
In conclusion, DeepSeek-V2.5 is more expensive than Pixtral-12B.*
* Using a 3:1 ratio of input to output tokens
Model Size
Parameter count comparison
DeepSeek-V2.5 has 223.6B more parameters than Pixtral-12B, making it 1803.2% larger.
Context Window
Maximum input and output token capacity
Pixtral-12B accepts 128,000 input tokens compared to DeepSeek-V2.5's 8,192 tokens. Both models can generate responses up to 8,192 tokens.
Input Capabilities
Supported data types and modalities
Pixtral-12B supports multimodal inputs, whereas DeepSeek-V2.5 does not.
Pixtral-12B can handle both text and other forms of data like images, making it suitable for multimodal applications.
DeepSeek-V2.5
Pixtral-12B
License
Usage and distribution terms
DeepSeek-V2.5 is licensed under deepseek, while Pixtral-12B uses Apache 2.0.
License differences may affect how you can use these models in commercial or open-source projects.
deepseek
Open weights
Apache 2.0
Open weights
Release Timeline
When each model was launched
DeepSeek-V2.5 was released on 2024-05-08, while Pixtral-12B was released on 2024-09-17.
Pixtral-12B is 4 months newer than DeepSeek-V2.5.
May 8, 2024
2.3 years ago
Sep 17, 2024
1.9 years ago
4mo newerKnowledge Cutoff
When training data ends
Neither model specifies a knowledge cutoff date.
Unable to compare the recency of their training data.
Provider Availability
DeepSeek-V2.5 is available from DeepSeek, DeepInfra, Hyperbolic. Pixtral-12B is available from Mistral AI.
DeepSeek-V2.5
Pixtral-12B
Outputs Comparison
Judge for yourself.
Run your own prompts against DeepSeek-V2.5 and Pixtral-12B side-by-side, then vote on the output you prefer.
FAQ
Common questions about DeepSeek-V2.5 vs Pixtral-12B.