Model Comparison

DeepSeek VL2 vs Magistral Medium

Comparing DeepSeek VL2 and Magistral Medium across benchmarks, pricing, and capabilities.

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Performance Benchmarks

Comparative analysis across standard metrics

No common benchmarks found

DeepSeek VL2 and Magistral Medium don't have any common benchmark datasets to compare. They may have been evaluated on different testing suites.

Arena Performance

Human preference votes

Model Size

Parameter count comparison

3.0B diff

DeepSeek VL2 has 3.0B more parameters than Magistral Medium, making it 12.5% larger.

DeepSeek
DeepSeek VL2
27.0Bparameters
Mistral AI
Magistral Medium
24.0Bparameters
27.0B
DeepSeek VL2
24.0B
Magistral Medium

Context Window

Maximum input and output token capacity

Only DeepSeek VL2 specifies input context (129,280 tokens). Only DeepSeek VL2 specifies output context (129,280 tokens).

DeepSeek
DeepSeek VL2
Input129,280 tokens
Output129,280 tokens
Mistral AI
Magistral Medium
Input- tokens
Output- tokens
Sat May 30 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

Both DeepSeek VL2 and Magistral Medium support multimodal inputs.

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

DeepSeek VL2

Text
Images
Audio
Video

Magistral Medium

Text
Images
Audio
Video

License

Usage and distribution terms

DeepSeek VL2 is licensed under deepseek, while Magistral Medium uses Apache 2.0.

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

DeepSeek VL2

deepseek

Open weights

Magistral Medium

Apache 2.0

Open weights

Release Timeline

When each model was launched

DeepSeek VL2 was released on 2024-12-13, while Magistral Medium was released on 2025-06-10.

Magistral Medium is 6 months newer than DeepSeek VL2.

DeepSeek VL2

Dec 13, 2024

1.5 years ago

Magistral Medium

Jun 10, 2025

11 months ago

5mo newer

Knowledge Cutoff

When training data ends

Magistral Medium has a documented knowledge cutoff of 2025-06-01, while DeepSeek VL2's cutoff date is not specified.

We can confirm Magistral Medium's training data extends to 2025-06-01, but cannot make a direct comparison without DeepSeek VL2's cutoff date.

DeepSeek VL2

—

Magistral Medium

Jun 2025

Outputs Comparison

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Key Takeaways

DeepSeek
Larger context window (129,280 tokens)
Mistral AI

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

Detailed Comparison

AI Model Comparison Table
Feature
DeepSeek
DeepSeek VL2
Mistral AI
Magistral Medium

FAQ

Common questions about DeepSeek VL2 vs Magistral Medium.

Which is better, DeepSeek VL2 or Magistral Medium?

DeepSeek VL2 (DeepSeek) and Magistral Medium (Mistral AI) each have strengths in different areas. Compare their benchmark scores, pricing, context windows, and capabilities above to determine which fits your needs.

How does DeepSeek VL2 compare to Magistral Medium in benchmarks?

DeepSeek VL2 scores DocVQA: 93.3%, ChartQA: 86.0%, TextVQA: 84.2%, AI2D: 81.4%, OCRBench: 81.1%. Magistral Medium scores AIME 2024: 73.6%, GPQA: 70.8%, AIME 2025: 64.9%, LiveCodeBench: 50.3%, Aider-Polyglot: 47.1%.

What are the context window sizes for DeepSeek VL2 and Magistral Medium?

DeepSeek VL2 supports 129K tokens and Magistral Medium supports an unknown number of 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 and Magistral Medium?

Key differences include licensing (deepseek vs Apache 2.0). See the full comparison above for benchmark-by-benchmark results.

Who makes DeepSeek VL2 and Magistral Medium?

DeepSeek VL2 is developed by DeepSeek and Magistral Medium is developed by Mistral AI.