Model Comparison

DeepSeek-R1-0528 vs Mistral Small 3.2 24B Instruct

DeepSeek-R1-0528 significantly outperforms across most benchmarks.

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Performance Benchmarks

Comparative analysis across standard metrics

3 benchmarks

DeepSeek-R1-0528 outperforms in 3 benchmarks (GPQA, MMLU-Pro, SimpleQA), while Mistral Small 3.2 24B Instruct is better at 0 benchmarks.

DeepSeek-R1-0528 significantly outperforms across most benchmarks.

Wed Apr 22 2026 • llm-stats.com

Arena Performance

Human preference votes

Pricing Analysis

Price comparison per million tokens

Cost data unavailable.

Lowest available price from all providers
Wed Apr 22 2026 • llm-stats.com
DeepSeek
DeepSeek-R1-0528
Input tokens$0.50
Output tokens$2.15
Best providerDeepinfra
Mistral AI
Mistral Small 3.2 24B Instruct
Input tokens$0.00
Output tokens$0.00
Best providerUnknown Organization
Notice missing or incorrect data?Start an Issue→

Model Size

Parameter count comparison

647.4B diff

DeepSeek-R1-0528 has 647.4B more parameters than Mistral Small 3.2 24B Instruct, making it 2743.2% larger.

DeepSeek
DeepSeek-R1-0528
671.0Bparameters
Mistral AI
Mistral Small 3.2 24B Instruct
23.6Bparameters
671.0B
DeepSeek-R1-0528
23.6B
Mistral Small 3.2 24B Instruct

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
Mistral Small 3.2 24B Instruct
Input- tokens
Output- tokens
Wed Apr 22 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

Mistral Small 3.2 24B Instruct supports multimodal inputs, whereas DeepSeek-R1-0528 does not.

Mistral Small 3.2 24B Instruct can handle both text and other forms of data like images, making it suitable for multimodal applications.

DeepSeek-R1-0528

Text
Images
Audio
Video

Mistral Small 3.2 24B Instruct

Text
Images
Audio
Video

License

Usage and distribution terms

DeepSeek-R1-0528 is licensed under MIT, while Mistral Small 3.2 24B Instruct 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

Mistral Small 3.2 24B Instruct

Apache 2.0

Open weights

Release Timeline

When each model was launched

DeepSeek-R1-0528 was released on 2025-05-28, while Mistral Small 3.2 24B Instruct was released on 2025-06-20.

Mistral Small 3.2 24B Instruct is 1 month newer than DeepSeek-R1-0528.

DeepSeek-R1-0528

May 28, 2025

10 months ago

Mistral Small 3.2 24B Instruct

Jun 20, 2025

10 months ago

3w newer

Knowledge Cutoff

When training data ends

Mistral Small 3.2 24B Instruct has a documented knowledge cutoff of 2023-10-01, while DeepSeek-R1-0528's cutoff date is not specified.

We can confirm Mistral Small 3.2 24B Instruct's training data extends to 2023-10-01, but cannot make a direct comparison without DeepSeek-R1-0528's cutoff date.

DeepSeek-R1-0528

—

Mistral Small 3.2 24B Instruct

Oct 2023

Outputs Comparison

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Key Takeaways

DeepSeek
Larger context window (131,072 tokens)
Higher GPQA score (81.0% vs 46.1%)
Higher MMLU-Pro score (85.0% vs 69.1%)
Higher SimpleQA score (92.3% vs 12.1%)
Mistral AI
Supports multimodal inputs

Detailed Comparison

AI Model Comparison Table
Feature
DeepSeek
DeepSeek-R1-0528
Mistral AI
Mistral Small 3.2 24B Instruct

FAQ

Common questions about DeepSeek-R1-0528 vs Mistral Small 3.2 24B Instruct

DeepSeek-R1-0528 significantly outperforms across most benchmarks. DeepSeek-R1-0528 is made by DeepSeek and Mistral Small 3.2 24B Instruct is made by Mistral AI. The best choice depends on your use case — compare their benchmark scores, pricing, and capabilities above.
DeepSeek-R1-0528 scores MMLU-Redux: 93.4%, SimpleQA: 92.3%, AIME 2024: 91.4%, AIME 2025: 87.5%, MMLU-Pro: 85.0%. Mistral Small 3.2 24B Instruct scores DocVQA: 94.9%, AI2D: 92.9%, HumanEval Plus: 92.9%, ChartQA: 87.4%, IF: 84.8%.
DeepSeek-R1-0528 supports 131K tokens and Mistral Small 3.2 24B Instruct supports an unknown number of tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.
Key differences include multimodal support (no vs yes), licensing (MIT vs Apache 2.0). See the full comparison above for benchmark-by-benchmark results.
DeepSeek-R1-0528 is developed by DeepSeek and Mistral Small 3.2 24B Instruct is developed by Mistral AI.