Model Comparison

DeepSeek-R1 vs Mistral Large 3 (675B Base)

Comparing DeepSeek-R1 and Mistral Large 3 (675B Base) across benchmarks, pricing, and capabilities.

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Performance Benchmarks

Comparative analysis across standard metrics

No common benchmarks found

DeepSeek-R1 and Mistral Large 3 (675B Base) don't have any common benchmark datasets to compare. They may have been evaluated on different testing suites.

Arena Performance

Human preference votes

Pricing Analysis

Price comparison per million tokens

Cost data unavailable.

Lowest available price from all providers
Wed Apr 15 2026 • llm-stats.com
DeepSeek
DeepSeek-R1
Input tokens$0.55
Output tokens$2.19
Best providerDeepSeek
Mistral AI
Mistral Large 3 (675B Base)
Input tokens$0.00
Output tokens$0.00
Best providerUnknown Organization
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Model Size

Parameter count comparison

4.0B diff

Mistral Large 3 (675B Base) has 4.0B more parameters than DeepSeek-R1, making it 0.6% larger.

DeepSeek
DeepSeek-R1
671.0Bparameters
Mistral AI
Mistral Large 3 (675B Base)
675.0Bparameters
671.0B
DeepSeek-R1
675.0B
Mistral Large 3 (675B Base)

Context Window

Maximum input and output token capacity

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

DeepSeek
DeepSeek-R1
Input131,072 tokens
Output131,072 tokens
Mistral AI
Mistral Large 3 (675B Base)
Input- tokens
Output- tokens
Wed Apr 15 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

Mistral Large 3 (675B Base) supports multimodal inputs, whereas DeepSeek-R1 does not.

Mistral Large 3 (675B Base) can handle both text and other forms of data like images, making it suitable for multimodal applications.

DeepSeek-R1

Text
Images
Audio
Video

Mistral Large 3 (675B Base)

Text
Images
Audio
Video

License

Usage and distribution terms

DeepSeek-R1 is licensed under MIT, while Mistral Large 3 (675B Base) uses Apache 2.0.

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

DeepSeek-R1

MIT

Open weights

Mistral Large 3 (675B Base)

Apache 2.0

Open weights

Release Timeline

When each model was launched

DeepSeek-R1 was released on 2025-01-20, while Mistral Large 3 (675B Base) was released on 2025-12-04.

Mistral Large 3 (675B Base) is 11 months newer than DeepSeek-R1.

DeepSeek-R1

Jan 20, 2025

1.2 years ago

Mistral Large 3 (675B Base)

Dec 4, 2025

4 months ago

10mo newer

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
Larger context window (131,072 tokens)
Mistral AI
Supports multimodal inputs

Detailed Comparison

AI Model Comparison Table
Feature
DeepSeek
DeepSeek-R1
Mistral AI
Mistral Large 3 (675B Base)

FAQ

Common questions about DeepSeek-R1 vs Mistral Large 3 (675B Base)

DeepSeek-R1 (DeepSeek) and Mistral Large 3 (675B Base) (Mistral AI) each have strengths in different areas. Compare their benchmark scores, pricing, context windows, and capabilities above to determine which fits your needs.
Mistral Large 3 (675B Base) scores MMMLU: 85.5%, AMC_2022_23: 52.0%, GPQA: 43.9%, LiveCodeBench: 34.4%, SimpleQA: 23.8%.
DeepSeek-R1 supports 131K tokens and Mistral Large 3 (675B Base) 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 is developed by DeepSeek and Mistral Large 3 (675B Base) is developed by Mistral AI.