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Model Comparison

DeepSeek-V4-Flash-0731 vs Ministral 3 (14B Base 2512)Which is better in 2026?

Comparing DeepSeek-V4-Flash-0731 and Ministral 3 (14B Base 2512) across benchmarks, pricing, and capabilities.

Verdict: DeepSeek-V4-Flash-0731 vs Ministral 3 (14B Base 2512) — which is better?

DeepSeek-V4-Flash-0731 (by DeepSeek) and Ministral 3 (14B Base 2512) (by Mistral AI) are two of the AI models people compare most. Here is how they stack up on benchmarks, price and capabilities, and which one to pick in 2026.

Choose DeepSeek-V4-Flash-0731 if…

  • you want the most recent training data — it shipped Jul 2026

Choose Ministral 3 (14B Base 2512) if…

  • you are already invested in the Mistral AI ecosystem

Performance Benchmarks

Comparative analysis across standard metrics

No common benchmarks found

DeepSeek-V4-Flash-0731 and Ministral 3 (14B 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

Model Size

Parameter count comparison

290.0B diff

DeepSeek-V4-Flash-0731 has 290.0B more parameters than Ministral 3 (14B Base 2512), making it 2071.4% larger.

DeepSeek
DeepSeek-V4-Flash-0731
304.0Bparameters
Mistral AI
Ministral 3 (14B Base 2512)
14.0Bparameters
304.0B
DeepSeek-V4-Flash-0731
14.0B
Ministral 3 (14B Base 2512)

Context Window

Maximum input and output token capacity

Only DeepSeek-V4-Flash-0731 specifies input context (1,048,576 tokens). Only DeepSeek-V4-Flash-0731 specifies output context (65,536 tokens).

DeepSeek
DeepSeek-V4-Flash-0731
Input1,048,576 tokens
Output65,536 tokens
Mistral AI
Ministral 3 (14B Base 2512)
Input- tokens
Output- tokens
Fri Aug 07 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

Ministral 3 (14B Base 2512) supports multimodal inputs, whereas DeepSeek-V4-Flash-0731 does not.

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

DeepSeek-V4-Flash-0731

Text
Images
Audio
Video

Ministral 3 (14B Base 2512)

Text
Images
Audio
Video

License

Usage and distribution terms

DeepSeek-V4-Flash-0731 is licensed under MIT, while Ministral 3 (14B Base 2512) uses Apache 2.0.

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

DeepSeek-V4-Flash-0731

MIT

Open weights

Ministral 3 (14B Base 2512)

Apache 2.0

Open weights

Release Timeline

When each model was launched

DeepSeek-V4-Flash-0731 was released on 2026-07-31, while Ministral 3 (14B Base 2512) was released on 2025-12-04.

DeepSeek-V4-Flash-0731 is 8 months newer than Ministral 3 (14B Base 2512).

DeepSeek-V4-Flash-0731

Jul 31, 2026

1 weeks ago

7mo newer
Ministral 3 (14B Base 2512)

Dec 4, 2025

8 months ago

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 (1,048,576 tokens)
Mistral AI
Supports multimodal inputs

Detailed Comparison

Interactive Arena

Judge for yourself.

Run your own prompts against DeepSeek-V4-Flash-0731 and Ministral 3 (14B Base 2512) side-by-side, then vote on the output you prefer.

DeepSeek-V4-Flash-0731
✓ Preferred
Ministral 3 (14B Base 2512)
Open in Playground
AI Model Comparison Table
Feature
DeepSeek
DeepSeek-V4-Flash-0731
Mistral AI
Ministral 3 (14B Base 2512)

FAQ

Common questions about DeepSeek-V4-Flash-0731 vs Ministral 3 (14B Base 2512).

Which is better, DeepSeek-V4-Flash-0731 or Ministral 3 (14B Base 2512)?

DeepSeek-V4-Flash-0731 (DeepSeek) and Ministral 3 (14B 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.

How does DeepSeek-V4-Flash-0731 compare to Ministral 3 (14B Base 2512) in benchmarks?

DeepSeek-V4-Flash-0731 scores Terminal-Bench 2.1: 82.7%, CyberGym: 76.7%, Toolathlon: 70.3%, DSBench-FullStack: 68.7%, DSBench-Hard: 59.6%. Ministral 3 (14B Base 2512) scores MMLU-Redux: 82.0%, MMLU: 79.4%, TriviaQA: 74.9%, Multilingual MMLU: 74.2%, MATH (CoT): 67.6%.

What are the context window sizes for DeepSeek-V4-Flash-0731 and Ministral 3 (14B Base 2512)?

DeepSeek-V4-Flash-0731 supports 1.0M tokens and Ministral 3 (14B Base 2512) supports an unknown number of tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.

What are the main differences between DeepSeek-V4-Flash-0731 and Ministral 3 (14B Base 2512)?

Key differences include multimodal support (no vs yes), licensing (MIT vs Apache 2.0). See the full comparison above for benchmark-by-benchmark results.

Who makes DeepSeek-V4-Flash-0731 and Ministral 3 (14B Base 2512)?

DeepSeek-V4-Flash-0731 is developed by DeepSeek and Ministral 3 (14B Base 2512) is developed by Mistral AI.

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