DeepSeek-V3 vs Pixtral-12B
DeepSeek-V3 leads the LLM Stats Score 15.8 to -1.4. Pixtral-12B is 3.2x cheaper per token.
DeepSeek · Mistral AI · Updated for 2026
Which is better?
DeepSeek-V3 leads the overall LLM Stats Score 15.8 to -1.4, ranking #214 overall.
In the 2 individual benchmarks reported for both models, DeepSeek-V3 wins 2; this is a narrower head-to-head signal than the composite indexes.
On price, Pixtral-12B is roughly 3.2x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
DeepSeek-V3 also accepts a larger context window (131,072 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 DeepSeek-V3
- overall performance matters — it scores 15.8 and ranks #214 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 131,072 token context window
- you want the most recent training data — it shipped Dec 2024
Choose Pixtral-12B
- cost matters — it's about 3.2x cheaper per token
At a glance
The differences that matter most.
Capability indexes
Additional strengths measured across groups of related public benchmarks
Individual benchmarks
20 reported for DeepSeek-V3 · 12 for Pixtral-12B
DeepSeek-V3 outperforms in 2 benchmarks (IFEval, MMLU), while Pixtral-12B is better at 0 benchmarks.
DeepSeek-V3 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, DeepSeek-V3 ($0.27/1M tokens) is 1.8x more expensive than Pixtral-12B ($0.15/1M tokens).
For output processing, DeepSeek-V3 ($1.10/1M tokens) is 7.3x more expensive than Pixtral-12B ($0.15/1M tokens).
In conclusion, DeepSeek-V3 is more expensive than Pixtral-12B.*
* Using a 3:1 ratio of input to output tokens
Model Size
Parameter count comparison
DeepSeek-V3 has 658.6B more parameters than Pixtral-12B, making it 5311.3% larger.
Context Window
Maximum input and output token capacity
DeepSeek-V3 accepts 131,072 input tokens compared to Pixtral-12B's 128,000 tokens. DeepSeek-V3 can generate longer responses up to 131,072 tokens, while Pixtral-12B is limited to 8,192 tokens.
Input capabilities
Documented input modalities across available providers
Pixtral-12B supports multimodal inputs, whereas DeepSeek-V3 does not.
Pixtral-12B can handle both text and other forms of data like images, making it suitable for multimodal applications.
DeepSeek-V3
Pixtral-12B
License
Usage and distribution terms
DeepSeek-V3 is licensed under MIT + Model License (Commercial use allowed), while Pixtral-12B uses Apache 2.0.
License differences may affect how you can use these models in commercial or open-source projects.
MIT + Model License (Commercial use allowed)
Open weights
Apache 2.0
Open weights
Release Timeline
When each model was launched
DeepSeek-V3 was released on 2024-12-25, while Pixtral-12B was released on 2024-09-17.
DeepSeek-V3 is 3 months newer than Pixtral-12B.
Dec 25, 2024
1.7 years ago
3mo newerSep 17, 2024
2.0 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
DeepSeek-V3 is available from DeepSeek. Pixtral-12B is available from Mistral AI.
DeepSeek-V3
Pixtral-12B
Outputs Comparison
Judge for yourself.
Run your own prompts against DeepSeek-V3 and Pixtral-12B side-by-side, then vote on the output you prefer.
FAQ
Common questions about DeepSeek-V3 vs Pixtral-12B.