Model Comparison

DeepSeek VL2 Small vs Pixtral LargeWhich is better in 2026?

Pixtral Large significantly outperforms across most benchmarks.

Verdict: DeepSeek VL2 Small vs Pixtral Large — which is better?

DeepSeek VL2 Small (by DeepSeek) and Pixtral Large (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.

DeepSeek VL2 Small outperforms in 0 benchmarks, while Pixtral Large is better at 5 benchmarks (AI2D, ChartQA, DocVQA, MathVista, MMMU). Pixtral Large significantly outperforms across most benchmarks.

Choose DeepSeek VL2 Small if…

  • you want the most recent training data — it shipped Dec 2024

Choose Pixtral Large if…

  • you want the strongest raw capability — it leads on 5 of 5 shared benchmarks
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Performance Benchmarks

Comparative analysis across standard metrics

5 benchmarks

DeepSeek VL2 Small outperforms in 0 benchmarks, while Pixtral Large is better at 5 benchmarks (AI2D, ChartQA, DocVQA, MathVista, MMMU).

Pixtral Large significantly outperforms across most benchmarks.

Mon Jun 15 2026 • llm-stats.com

Arena Performance

Human preference votes

Model Size

Parameter count comparison

108.0B diff

Pixtral Large has 108.0B more parameters than DeepSeek VL2 Small, making it 675.0% larger.

DeepSeek
DeepSeek VL2 Small
16.0Bparameters
Mistral AI
Pixtral Large
124.0Bparameters
16.0B
DeepSeek VL2 Small
124.0B
Pixtral Large

Context Window

Maximum input and output token capacity

Only Pixtral Large specifies input context (128,000 tokens). Only Pixtral Large specifies output context (128,000 tokens).

DeepSeek
DeepSeek VL2 Small
Input- tokens
Output- tokens
Mistral AI
Pixtral Large
Input128,000 tokens
Output128,000 tokens
Mon Jun 15 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

Both DeepSeek VL2 Small and Pixtral Large support multimodal inputs.

They are both capable of processing various types of data, offering versatility in application.

DeepSeek VL2 Small

Text
Images
Audio
Video

Pixtral Large

Text
Images
Audio
Video

License

Usage and distribution terms

DeepSeek VL2 Small is licensed under deepseek, while Pixtral Large uses Mistral Research License (MRL) for research; Mistral Commercial License for commercial use.

License differences may affect how you can use these models in commercial or open-source projects.

DeepSeek VL2 Small

deepseek

Open weights

Pixtral Large

Mistral Research License (MRL) for research; Mistral Commercial License for commercial use

Open weights

Release Timeline

When each model was launched

DeepSeek VL2 Small was released on 2024-12-13, while Pixtral Large was released on 2024-11-18.

DeepSeek VL2 Small is 1 month newer than Pixtral Large.

DeepSeek VL2 Small

Dec 13, 2024

1.5 years ago

3w newer
Pixtral Large

Nov 18, 2024

1.6 years ago

Knowledge Cutoff

When training data ends

Neither model specifies a knowledge cutoff date.

Unable to compare the recency of their training data.

No cutoff dates available

Outputs Comparison

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Key Takeaways

DeepSeek

No standout differentiators in the data we have for this pair.

Mistral AI
Larger context window (128,000 tokens)
Higher AI2D score (93.8% vs 80.0%)
Higher ChartQA score (88.1% vs 84.5%)
Higher DocVQA score (93.3% vs 92.3%)
Higher MathVista score (69.4% vs 60.7%)
Higher MMMU score (64.0% vs 48.0%)

Detailed Comparison

AI Model Comparison Table
Feature
DeepSeek
DeepSeek VL2 Small
Mistral AI
Pixtral Large

FAQ

Common questions about DeepSeek VL2 Small vs Pixtral Large.

Which is better, DeepSeek VL2 Small or Pixtral Large?

Pixtral Large significantly outperforms across most benchmarks. DeepSeek VL2 Small is made by DeepSeek and Pixtral Large is made by Mistral AI. The best choice depends on your use case — compare their benchmark scores, pricing, and capabilities above.

How does DeepSeek VL2 Small compare to Pixtral Large in benchmarks?

DeepSeek VL2 Small scores DocVQA: 92.3%, ChartQA: 84.5%, OCRBench: 83.4%, TextVQA: 83.4%, MMBench: 80.3%. Pixtral Large scores AI2D: 93.8%, DocVQA: 93.3%, ChartQA: 88.1%, VQAv2: 80.9%, MM-MT-Bench: 74.0%.

What are the context window sizes for DeepSeek VL2 Small and Pixtral Large?

DeepSeek VL2 Small supports an unknown number of tokens and Pixtral Large supports 128K tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.

What are the main differences between DeepSeek VL2 Small and Pixtral Large?

Key differences include licensing (deepseek vs Mistral Research License (MRL) for research; Mistral Commercial License for commercial use). See the full comparison above for benchmark-by-benchmark results.

Who makes DeepSeek VL2 Small and Pixtral Large?

DeepSeek VL2 Small is developed by DeepSeek and Pixtral Large is developed by Mistral AI.

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