Model Comparison

DeepSeek-R1-0528 vs Magistral Small 2506Which is better in 2026?

DeepSeek-R1-0528 significantly outperforms across most benchmarks.

Verdict: DeepSeek-R1-0528 vs Magistral Small 2506 — which is better?

DeepSeek-R1-0528 (by DeepSeek) and Magistral Small 2506 (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-R1-0528 outperforms in 4 benchmarks (AIME 2024, AIME 2025, GPQA, LiveCodeBench), while Magistral Small 2506 is better at 0 benchmarks. DeepSeek-R1-0528 significantly outperforms across most benchmarks.

Choose DeepSeek-R1-0528 if…

  • you want the strongest raw capability — it leads on 4 of 4 shared benchmarks

Choose Magistral Small 2506 if…

  • you want the most recent training data — it shipped Jun 2025

Performance Benchmarks

Comparative analysis across standard metrics

4 benchmarks

DeepSeek-R1-0528 outperforms in 4 benchmarks (AIME 2024, AIME 2025, GPQA, LiveCodeBench), while Magistral Small 2506 is better at 0 benchmarks.

DeepSeek-R1-0528 significantly outperforms across most benchmarks.

Thu Jun 18 2026 • llm-stats.com

Arena Performance

Human preference votes

Model Size

Parameter count comparison

647.0B diff

DeepSeek-R1-0528 has 647.0B more parameters than Magistral Small 2506, making it 2695.8% larger.

DeepSeek
DeepSeek-R1-0528
671.0Bparameters
Mistral AI
Magistral Small 2506
24.0Bparameters
671.0B
DeepSeek-R1-0528
24.0B
Magistral Small 2506

Context Window

Maximum input and output token capacity

Only DeepSeek-R1-0528 specifies input context (131,072 tokens). Only DeepSeek-R1-0528 specifies output context (131,072 tokens).

DeepSeek
DeepSeek-R1-0528
Input131,072 tokens
Output131,072 tokens
Mistral AI
Magistral Small 2506
Input- tokens
Output- tokens
Thu Jun 18 2026 • llm-stats.com

License

Usage and distribution terms

DeepSeek-R1-0528 is licensed under MIT, while Magistral Small 2506 uses Apache 2.0.

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

DeepSeek-R1-0528

MIT

Open weights

Magistral Small 2506

Apache 2.0

Open weights

Release Timeline

When each model was launched

DeepSeek-R1-0528 was released on 2025-05-28, while Magistral Small 2506 was released on 2025-06-10.

Magistral Small 2506 is 0 month newer than DeepSeek-R1-0528.

DeepSeek-R1-0528

May 28, 2025

1.1 years ago

Magistral Small 2506

Jun 10, 2025

1.0 years ago

1w newer

Knowledge Cutoff

When training data ends

Magistral Small 2506 has a documented knowledge cutoff of 2025-06-01, while DeepSeek-R1-0528's cutoff date is not specified.

We can confirm Magistral Small 2506's training data extends to 2025-06-01, but cannot make a direct comparison without DeepSeek-R1-0528's cutoff date.

DeepSeek-R1-0528

Magistral Small 2506

Jun 2025

Outputs Comparison

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Key Takeaways

Larger context window (131,072 tokens)
Higher AIME 2024 score (91.4% vs 70.7%)
Higher AIME 2025 score (87.5% vs 62.8%)
Higher GPQA score (81.0% vs 68.2%)
Higher LiveCodeBench score (73.3% vs 51.3%)

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

Detailed Comparison

AI Model Comparison Table
Feature
DeepSeek
DeepSeek-R1-0528
Mistral AI
Magistral Small 2506

FAQ

Common questions about DeepSeek-R1-0528 vs Magistral Small 2506.

Which is better, DeepSeek-R1-0528 or Magistral Small 2506?

DeepSeek-R1-0528 significantly outperforms across most benchmarks. DeepSeek-R1-0528 is made by DeepSeek and Magistral Small 2506 is made by Mistral AI. The best choice depends on your use case — compare their benchmark scores, pricing, and capabilities above.

How does DeepSeek-R1-0528 compare to Magistral Small 2506 in benchmarks?

DeepSeek-R1-0528 scores MMLU-Redux: 93.4%, SimpleQA: 92.3%, AIME 2024: 91.4%, AIME 2025: 87.5%, MMLU-Pro: 85.0%. Magistral Small 2506 scores AIME 2024: 70.7%, GPQA: 68.2%, AIME 2025: 62.8%, LiveCodeBench: 51.3%.

What are the context window sizes for DeepSeek-R1-0528 and Magistral Small 2506?

DeepSeek-R1-0528 supports 131K tokens and Magistral Small 2506 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-R1-0528 and Magistral Small 2506?

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

Who makes DeepSeek-R1-0528 and Magistral Small 2506?

DeepSeek-R1-0528 is developed by DeepSeek and Magistral Small 2506 is developed by Mistral AI.