Model Comparison

Ministral 3 (14B Base 2512) vs Mistral Large 3Which is better in 2026?

Both models are evenly matched across the benchmarks.

Verdict: Ministral 3 (14B Base 2512) vs Mistral Large 3 — which is better?

Ministral 3 (14B Base 2512) (by Mistral AI) and Mistral Large 3 (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.

Ministral 3 (14B Base 2512) outperforms in 0 benchmarks, while Mistral Large 3 is better at 0 benchmarks. Both models are evenly matched across the benchmarks.

Choose Ministral 3 (14B Base 2512) if…

  • you want the most recent training data — it shipped Dec 2025

Choose Mistral Large 3 if…

  • you want the strongest raw capability — it leads on 3 of 3 shared benchmarks

Performance Benchmarks

Comparative analysis across standard metrics

3 benchmarks

Ministral 3 (14B Base 2512) outperforms in 0 benchmarks, while Mistral Large 3 is better at 0 benchmarks.

Both models are evenly matched across the benchmarks.

Tue Jul 28 2026 • llm-stats.com

Arena Performance

Human preference votes

Model Size

Parameter count comparison

661.0B diff

Mistral Large 3 has 661.0B more parameters than Ministral 3 (14B Base 2512), making it 4721.4% larger.

Mistral AI
Ministral 3 (14B Base 2512)
14.0Bparameters
Mistral AI
Mistral Large 3
675.0Bparameters
14.0B
Ministral 3 (14B Base 2512)
675.0B
Mistral Large 3

Context Window

Maximum input and output token capacity

Only Mistral Large 3 specifies input context (128,000 tokens). Only Mistral Large 3 specifies output context (8,192 tokens).

Mistral AI
Ministral 3 (14B Base 2512)
Input- tokens
Output- tokens
Mistral AI
Mistral Large 3
Input128,000 tokens
Output8,192 tokens
Tue Jul 28 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

Both Ministral 3 (14B Base 2512) and Mistral Large 3 support multimodal inputs.

They are both capable of processing various types of data, offering versatility in application.

Ministral 3 (14B Base 2512)

Text
Images
Audio
Video

Mistral Large 3

Text
Images
Audio
Video

License

Usage and distribution terms

Both models are licensed under Apache 2.0.

Both models share the same licensing terms, providing consistent usage rights.

Ministral 3 (14B Base 2512)

Apache 2.0

Open weights

Mistral Large 3

Apache 2.0

Open weights

Release Timeline

When each model was launched

Ministral 3 (14B Base 2512) was released on 2025-12-04, while Mistral Large 3 was released on 2025-09-01.

Ministral 3 (14B Base 2512) is 3 months newer than Mistral Large 3.

Ministral 3 (14B Base 2512)

Dec 4, 2025

7 months ago

3mo newer
Mistral Large 3

Sep 1, 2025

11 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

Mistral AI

No standout differentiators in the data we have for this pair.

Mistral AI
Larger context window (128,000 tokens)

Detailed Comparison

Interactive Arena

Judge for yourself.

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

Ministral 3 (14B Base 2512)
✓ Preferred
Mistral Large 3
Open in Playground
AI Model Comparison Table
Feature
Mistral AI
Ministral 3 (14B Base 2512)
Mistral AI
Mistral Large 3

FAQ

Common questions about Ministral 3 (14B Base 2512) vs Mistral Large 3.

Which is better, Ministral 3 (14B Base 2512) or Mistral Large 3?

Both models are evenly matched across the benchmarks. Ministral 3 (14B Base 2512) is made by Mistral AI and Mistral Large 3 is made by Mistral AI. The best choice depends on your use case — compare their benchmark scores, pricing, and capabilities above.

How does Ministral 3 (14B Base 2512) compare to Mistral Large 3 in benchmarks?

Ministral 3 (14B Base 2512) scores MMLU-Redux: 82.0%, MMLU: 79.4%, TriviaQA: 74.9%, Multilingual MMLU: 74.2%, MATH (CoT): 67.6%. Mistral Large 3 scores MATH: 90.4%, MM-MT-Bench: 84.9%, MMLU-Redux: 82.0%, TriviaQA: 74.9%, MMMLU: 74.2%.

What are the context window sizes for Ministral 3 (14B Base 2512) and Mistral Large 3?

Ministral 3 (14B Base 2512) supports an unknown number of tokens and Mistral Large 3 supports 128K tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.

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