Model Comparison
DeepSeek-R1-0528 vs Pixtral-12BWhich is better in 2026?
Comparing DeepSeek-R1-0528 and Pixtral-12B across benchmarks, pricing, and capabilities.
Verdict: DeepSeek-R1-0528 vs Pixtral-12B — which is better?
DeepSeek-R1-0528 (by DeepSeek) and Pixtral-12B (by Mistral AI) are two of the AI models people compare most. Here is how they stack up on benchmarks, price and capabilities, and which one to pick in 2026.
On price, Pixtral-12B is roughly 6.1x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
DeepSeek-R1-0528 also accepts a larger context window (131,072 input tokens), making it the stronger choice for long documents and large codebases.
Choose DeepSeek-R1-0528 if…
- you process long inputs — it offers a 131,072 token context window
- you want the most recent training data — it shipped May 2025
Choose Pixtral-12B if…
- cost matters — it's about 6.1x cheaper per token
Performance Benchmarks
Comparative analysis across standard metrics
DeepSeek-R1-0528 and Pixtral-12Bdon't have any common benchmark datasets to compare. They may have been evaluated on different testing suites.
Arena Performance
Human preference votes
Pricing Analysis
Price comparison per million tokens
For input processing, DeepSeek-R1-0528 ($0.50/1M tokens) is 3.3x more expensive than Pixtral-12B ($0.15/1M tokens).
For output processing, DeepSeek-R1-0528 ($2.15/1M tokens) is 14.3x more expensive than Pixtral-12B ($0.15/1M tokens).
In conclusion, DeepSeek-R1-0528 is more expensive than Pixtral-12B.*
* Using a 3:1 ratio of input to output tokens
Model Size
Parameter count comparison
DeepSeek-R1-0528 has 658.6B more parameters than Pixtral-12B, making it 5311.3% larger.
Context Window
Maximum input and output token capacity
DeepSeek-R1-0528 accepts 131,072 input tokens compared to Pixtral-12B's 128,000 tokens. DeepSeek-R1-0528 can generate longer responses up to 131,072 tokens, while Pixtral-12B is limited to 8,192 tokens.
Input Capabilities
Supported data types and modalities
Pixtral-12B supports multimodal inputs, whereas DeepSeek-R1-0528 does not.
Pixtral-12B can handle both text and other forms of data like images, making it suitable for multimodal applications.
DeepSeek-R1-0528
Pixtral-12B
License
Usage and distribution terms
DeepSeek-R1-0528 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
DeepSeek-R1-0528 was released on 2025-05-28, while Pixtral-12B was released on 2024-09-17.
DeepSeek-R1-0528 is 8 months newer than Pixtral-12B.
May 28, 2025
1.0 years ago
8mo newerSep 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
DeepSeek-R1-0528 is available from DeepInfra, DeepSeek, Novita. Pixtral-12B is available from Mistral AI.
DeepSeek-R1-0528
Pixtral-12B
Outputs Comparison
Key Takeaways
DeepSeek-R1-0528
View detailsDeepSeek
Pixtral-12B
View detailsMistral AI
Detailed Comparison
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FAQ
Common questions about DeepSeek-R1-0528 vs Pixtral-12B.