Model Comparison

DeepSeek-V3.2 (Thinking) vs Ministral 3 (8B Base 2512)

Comparing DeepSeek-V3.2 (Thinking) and Ministral 3 (8B Base 2512) across benchmarks, pricing, and capabilities.

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Performance Benchmarks

Comparative analysis across standard metrics

No common benchmarks found

DeepSeek-V3.2 (Thinking) and Ministral 3 (8B Base 2512) 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
Sat Apr 18 2026 • llm-stats.com
DeepSeek
DeepSeek-V3.2 (Thinking)
Input tokens$0.28
Output tokens$0.42
Best providerDeepSeek
Mistral AI
Ministral 3 (8B Base 2512)
Input tokens$0.00
Output tokens$0.00
Best providerUnknown Organization
Notice missing or incorrect data?Start an Issue→

Model Size

Parameter count comparison

677.0B diff

DeepSeek-V3.2 (Thinking) has 677.0B more parameters than Ministral 3 (8B Base 2512), making it 8462.5% larger.

DeepSeek
DeepSeek-V3.2 (Thinking)
685.0Bparameters
Mistral AI
Ministral 3 (8B Base 2512)
8.0Bparameters
685.0B
DeepSeek-V3.2 (Thinking)
8.0B
Ministral 3 (8B Base 2512)

Context Window

Maximum input and output token capacity

Only DeepSeek-V3.2 (Thinking) specifies input context (131,072 tokens). Only DeepSeek-V3.2 (Thinking) specifies output context (65,536 tokens).

DeepSeek
DeepSeek-V3.2 (Thinking)
Input131,072 tokens
Output65,536 tokens
Mistral AI
Ministral 3 (8B Base 2512)
Input- tokens
Output- tokens
Sat Apr 18 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

Ministral 3 (8B Base 2512) supports multimodal inputs, whereas DeepSeek-V3.2 (Thinking) does not.

Ministral 3 (8B Base 2512) can handle both text and other forms of data like images, making it suitable for multimodal applications.

DeepSeek-V3.2 (Thinking)

Text
Images
Audio
Video

Ministral 3 (8B Base 2512)

Text
Images
Audio
Video

License

Usage and distribution terms

DeepSeek-V3.2 (Thinking) is licensed under MIT, while Ministral 3 (8B Base 2512) uses Apache 2.0.

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

DeepSeek-V3.2 (Thinking)

MIT

Open weights

Ministral 3 (8B Base 2512)

Apache 2.0

Open weights

Release Timeline

When each model was launched

DeepSeek-V3.2 (Thinking) was released on 2025-12-01, while Ministral 3 (8B Base 2512) was released on 2025-12-04.

Ministral 3 (8B Base 2512) is 0 month newer than DeepSeek-V3.2 (Thinking).

DeepSeek-V3.2 (Thinking)

Dec 1, 2025

4 months ago

Ministral 3 (8B Base 2512)

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

Notice missing or incorrect data?Start an Issue discussion→

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 (Thinking)
Mistral AI
Ministral 3 (8B Base 2512)

FAQ

Common questions about DeepSeek-V3.2 (Thinking) vs Ministral 3 (8B Base 2512)

DeepSeek-V3.2 (Thinking) (DeepSeek) and Ministral 3 (8B Base 2512) (Mistral AI) each have strengths in different areas. Compare their benchmark scores, pricing, context windows, and capabilities above to determine which fits your needs.
DeepSeek-V3.2 (Thinking) scores AIME 2025: 93.1%, HMMT 2025: 90.2%, MMLU-Pro: 85.0%, LiveCodeBench: 83.3%, GPQA: 82.4%. Ministral 3 (8B Base 2512) scores MMLU-Redux: 79.3%, MMLU: 76.1%, Multilingual MMLU: 70.6%, TriviaQA: 68.1%, MATH (CoT): 62.6%.
DeepSeek-V3.2 (Thinking) supports 131K tokens and Ministral 3 (8B Base 2512) 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 (Thinking) is developed by DeepSeek and Ministral 3 (8B Base 2512) is developed by Mistral AI.