Model Comparison

Gemini Diffusion vs Ministral 3 (14B Reasoning 2512)

Ministral 3 (14B Reasoning 2512) significantly outperforms across most benchmarks.

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Performance Benchmarks

Comparative analysis across standard metrics

3 benchmarks

Gemini Diffusion outperforms in 0 benchmarks, while Ministral 3 (14B Reasoning 2512) is better at 3 benchmarks (AIME 2025, GPQA, LiveCodeBench).

Ministral 3 (14B Reasoning 2512) significantly outperforms across most benchmarks.

Thu Apr 16 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
Thu Apr 16 2026 • llm-stats.com
Google
Gemini Diffusion
Input tokens$0.00
Output tokens$0.00
Best providerUnknown Organization
Mistral AI
Ministral 3 (14B Reasoning 2512)
Input tokens$0.20
Output tokens$0.20
Best providerMistral
Notice missing or incorrect data?Start an Issue→

Context Window

Maximum input and output token capacity

Only Ministral 3 (14B Reasoning 2512) specifies input context (262,100 tokens). Only Ministral 3 (14B Reasoning 2512) specifies output context (262,100 tokens).

Google
Gemini Diffusion
Input- tokens
Output- tokens
Mistral AI
Ministral 3 (14B Reasoning 2512)
Input262,100 tokens
Output262,100 tokens
Thu Apr 16 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

Ministral 3 (14B Reasoning 2512) supports multimodal inputs, whereas Gemini Diffusion does not.

Ministral 3 (14B Reasoning 2512) can handle both text and other forms of data like images, making it suitable for multimodal applications.

Gemini Diffusion

Text
Images
Audio
Video

Ministral 3 (14B Reasoning 2512)

Text
Images
Audio
Video

License

Usage and distribution terms

Gemini Diffusion is licensed under a proprietary license, while Ministral 3 (14B Reasoning 2512) uses Apache 2.0.

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

Gemini Diffusion

Proprietary

Closed source

Ministral 3 (14B Reasoning 2512)

Apache 2.0

Open weights

Release Timeline

When each model was launched

Gemini Diffusion was released on 2025-05-20, while Ministral 3 (14B Reasoning 2512) was released on 2025-12-04.

Ministral 3 (14B Reasoning 2512) is 7 months newer than Gemini Diffusion.

Gemini Diffusion

May 20, 2025

11 months ago

Ministral 3 (14B Reasoning 2512)

Dec 4, 2025

4 months ago

6mo 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

Google
Mistral AI
Larger context window (262,100 tokens)
Supports multimodal inputs
Has open weights
Higher AIME 2025 score (85.0% vs 23.3%)
Higher GPQA score (71.2% vs 40.4%)
Higher LiveCodeBench score (64.6% vs 30.9%)

Detailed Comparison

AI Model Comparison Table
Feature
Google
Gemini Diffusion
Mistral AI
Ministral 3 (14B Reasoning 2512)

FAQ

Common questions about Gemini Diffusion vs Ministral 3 (14B Reasoning 2512)

Ministral 3 (14B Reasoning 2512) significantly outperforms across most benchmarks. Gemini Diffusion is made by Google and Ministral 3 (14B Reasoning 2512) is made by Mistral AI. The best choice depends on your use case — compare their benchmark scores, pricing, and capabilities above.
Gemini Diffusion scores HumanEval: 89.6%, MBPP: 76.0%, Global-MMLU-Lite: 69.1%, LBPP (v2): 56.8%, BigCodeBench: 45.4%. Ministral 3 (14B Reasoning 2512) scores AIME 2024: 89.8%, AIME 2025: 85.0%, GPQA: 71.2%, LiveCodeBench: 64.6%.
Gemini Diffusion supports an unknown number of tokens and Ministral 3 (14B Reasoning 2512) supports 262K 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 (Proprietary vs Apache 2.0). See the full comparison above for benchmark-by-benchmark results.
Gemini Diffusion is developed by Google and Ministral 3 (14B Reasoning 2512) is developed by Mistral AI.