Model Comparison

DeepSeek-V3 vs Magistral MediumWhich is better in 2026?

Magistral Medium shows notably better performance in the majority of benchmarks.

Verdict: DeepSeek-V3 vs Magistral Medium — which is better?

DeepSeek-V3 (by DeepSeek) and Magistral Medium (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-V3 outperforms in 1 benchmarks (Aider-Polyglot), while Magistral Medium is better at 3 benchmarks (AIME 2024, GPQA, LiveCodeBench). Magistral Medium shows notably better performance in the majority of benchmarks.

Choose DeepSeek-V3 if…

  • you want predictable pricing at $0.27/M input and $1.10/M output

Choose Magistral Medium if…

  • you want the strongest raw capability — it leads on 3 of 4 shared benchmarks
  • you want the most recent training data — it shipped Jun 2025
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Performance Benchmarks

Comparative analysis across standard metrics

4 benchmarks

DeepSeek-V3 outperforms in 1 benchmarks (Aider-Polyglot), while Magistral Medium is better at 3 benchmarks (AIME 2024, GPQA, LiveCodeBench).

Magistral Medium shows notably better performance in the majority of benchmarks.

Mon Jun 15 2026 • llm-stats.com

Arena Performance

Human preference votes

Model Size

Parameter count comparison

647.0B diff

DeepSeek-V3 has 647.0B more parameters than Magistral Medium, making it 2695.8% larger.

DeepSeek
DeepSeek-V3
671.0Bparameters
Mistral AI
Magistral Medium
24.0Bparameters
671.0B
DeepSeek-V3
24.0B
Magistral Medium

Context Window

Maximum input and output token capacity

Only DeepSeek-V3 specifies input context (131,072 tokens). Only DeepSeek-V3 specifies output context (131,072 tokens).

DeepSeek
DeepSeek-V3
Input131,072 tokens
Output131,072 tokens
Mistral AI
Magistral Medium
Input- tokens
Output- tokens
Mon Jun 15 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

Magistral Medium supports multimodal inputs, whereas DeepSeek-V3 does not.

Magistral Medium can handle both text and other forms of data like images, making it suitable for multimodal applications.

DeepSeek-V3

Text
Images
Audio
Video

Magistral Medium

Text
Images
Audio
Video

License

Usage and distribution terms

DeepSeek-V3 is licensed under MIT + Model License (Commercial use allowed), while Magistral Medium uses Apache 2.0.

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

DeepSeek-V3

MIT + Model License (Commercial use allowed)

Open weights

Magistral Medium

Apache 2.0

Open weights

Release Timeline

When each model was launched

DeepSeek-V3 was released on 2024-12-25, while Magistral Medium was released on 2025-06-10.

Magistral Medium is 6 months newer than DeepSeek-V3.

DeepSeek-V3

Dec 25, 2024

1.5 years ago

Magistral Medium

Jun 10, 2025

1.0 years ago

5mo newer

Knowledge Cutoff

When training data ends

Magistral Medium has a documented knowledge cutoff of 2025-06-01, while DeepSeek-V3'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-V3's cutoff date.

DeepSeek-V3

—

Magistral Medium

Jun 2025

Outputs Comparison

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Key Takeaways

DeepSeek
Larger context window (131,072 tokens)
Higher Aider-Polyglot score (49.6% vs 47.1%)
Mistral AI
Supports multimodal inputs
Higher AIME 2024 score (73.6% vs 39.2%)
Higher GPQA score (70.8% vs 59.1%)
Higher LiveCodeBench score (50.3% vs 37.6%)

Detailed Comparison

AI Model Comparison Table
Feature
DeepSeek
DeepSeek-V3
Mistral AI
Magistral Medium

FAQ

Common questions about DeepSeek-V3 vs Magistral Medium.

Which is better, DeepSeek-V3 or Magistral Medium?

Magistral Medium shows notably better performance in the majority of benchmarks. DeepSeek-V3 is made by DeepSeek and Magistral Medium is made by Mistral AI. The best choice depends on your use case — compare their benchmark scores, pricing, and capabilities above.

How does DeepSeek-V3 compare to Magistral Medium in benchmarks?

DeepSeek-V3 scores DROP: 91.6%, CLUEWSC: 90.9%, MATH-500: 90.2%, MMLU-Redux: 89.1%, MMLU: 88.5%. 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-V3 and Magistral Medium?

DeepSeek-V3 supports 131K 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-V3 and Magistral Medium?

Key differences include multimodal support (no vs yes), licensing (MIT + Model License (Commercial use allowed) vs Apache 2.0). See the full comparison above for benchmark-by-benchmark results.

Who makes DeepSeek-V3 and Magistral Medium?

DeepSeek-V3 is developed by DeepSeek and Magistral Medium is developed by Mistral AI.

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