Model Comparison

DeepSeek-V3.2 (Non-thinking) vs Mistral Large 3 (675B Instruct 2512 NVFP4)

Comparing DeepSeek-V3.2 (Non-thinking) and Mistral Large 3 (675B Instruct 2512 NVFP4) across benchmarks, pricing, and capabilities.

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Performance Benchmarks

Comparative analysis across standard metrics

No common benchmarks found

DeepSeek-V3.2 (Non-thinking) and Mistral Large 3 (675B Instruct 2512 NVFP4) 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
Tue Apr 14 2026 • llm-stats.com
DeepSeek
DeepSeek-V3.2 (Non-thinking)
Input tokens$0.28
Output tokens$0.42
Best providerDeepSeek
Mistral AI
Mistral Large 3 (675B Instruct 2512 NVFP4)
Input tokens$0.00
Output tokens$0.00
Best providerUnknown Organization
Notice missing or incorrect data?Start an Issue→

Model Size

Parameter count comparison

10.0B diff

DeepSeek-V3.2 (Non-thinking) has 10.0B more parameters than Mistral Large 3 (675B Instruct 2512 NVFP4), making it 1.5% larger.

DeepSeek
DeepSeek-V3.2 (Non-thinking)
685.0Bparameters
Mistral AI
Mistral Large 3 (675B Instruct 2512 NVFP4)
675.0Bparameters
685.0B
DeepSeek-V3.2 (Non-thinking)
675.0B
Mistral Large 3 (675B Instruct 2512 NVFP4)

Context Window

Maximum input and output token capacity

Only DeepSeek-V3.2 (Non-thinking) specifies input context (131,072 tokens). Only DeepSeek-V3.2 (Non-thinking) specifies output context (8,192 tokens).

DeepSeek
DeepSeek-V3.2 (Non-thinking)
Input131,072 tokens
Output8,192 tokens
Mistral AI
Mistral Large 3 (675B Instruct 2512 NVFP4)
Input- tokens
Output- tokens
Tue Apr 14 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

Mistral Large 3 (675B Instruct 2512 NVFP4) supports multimodal inputs, whereas DeepSeek-V3.2 (Non-thinking) does not.

Mistral Large 3 (675B Instruct 2512 NVFP4) can handle both text and other forms of data like images, making it suitable for multimodal applications.

DeepSeek-V3.2 (Non-thinking)

Text
Images
Audio
Video

Mistral Large 3 (675B Instruct 2512 NVFP4)

Text
Images
Audio
Video

License

Usage and distribution terms

DeepSeek-V3.2 (Non-thinking) is licensed under MIT, while Mistral Large 3 (675B Instruct 2512 NVFP4) uses Apache 2.0.

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

DeepSeek-V3.2 (Non-thinking)

MIT

Open weights

Mistral Large 3 (675B Instruct 2512 NVFP4)

Apache 2.0

Open weights

Release Timeline

When each model was launched

DeepSeek-V3.2 (Non-thinking) was released on 2025-12-01, while Mistral Large 3 (675B Instruct 2512 NVFP4) was released on 2025-12-04.

Mistral Large 3 (675B Instruct 2512 NVFP4) is 0 month newer than DeepSeek-V3.2 (Non-thinking).

DeepSeek-V3.2 (Non-thinking)

Dec 1, 2025

4 months ago

Mistral Large 3 (675B Instruct 2512 NVFP4)

Dec 4, 2025

4 months ago

3d 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-V3.2 (Non-thinking)
Mistral AI
Mistral Large 3 (675B Instruct 2512 NVFP4)

FAQ

Common questions about DeepSeek-V3.2 (Non-thinking) vs Mistral Large 3 (675B Instruct 2512 NVFP4)

DeepSeek-V3.2 (Non-thinking) (DeepSeek) and Mistral Large 3 (675B Instruct 2512 NVFP4) (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 Instruct 2512 NVFP4) scores MMMLU: 85.5%, AMC_2022_23: 52.0%, GPQA: 43.9%, LiveCodeBench: 34.4%, SimpleQA: 23.8%.
DeepSeek-V3.2 (Non-thinking) supports 131K tokens and Mistral Large 3 (675B Instruct 2512 NVFP4) 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-V3.2 (Non-thinking) is developed by DeepSeek and Mistral Large 3 (675B Instruct 2512 NVFP4) is developed by Mistral AI.