Model Comparison

Mistral Large 3 vs MiniStral 3 (14B Instruct 2512)Which is better in 2026?

Mistral Large 3 has a slight edge in benchmark performance.

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

Mistral Large 3 (by Mistral AI) and MiniStral 3 (14B Instruct 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.

Mistral Large 3 outperforms in 1 benchmarks (MM-MT-Bench), while MiniStral 3 (14B Instruct 2512) is better at 0 benchmarks. Mistral Large 3 has a slight edge in benchmark performance.

Choose Mistral Large 3 if…

  • you want predictable pricing at $2.00/M input and $5.00/M output

Choose MiniStral 3 (14B Instruct 2512) if…

  • you want the strongest raw capability — it leads on 3 of 4 shared benchmarks
  • you want the most recent training data — it shipped Dec 2025
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Performance Benchmarks

Comparative analysis across standard metrics

4 benchmarks

Mistral Large 3 outperforms in 1 benchmarks (MM-MT-Bench), while MiniStral 3 (14B Instruct 2512) is better at 0 benchmarks.

Mistral Large 3 has a slight edge in benchmark performance.

Thu Jun 25 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 Instruct 2512), making it 4721.4% larger.

Mistral AI
Mistral Large 3
675.0Bparameters
Mistral AI
MiniStral 3 (14B Instruct 2512)
14.0Bparameters
675.0B
Mistral Large 3
14.0B
MiniStral 3 (14B Instruct 2512)

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
Mistral Large 3
Input128,000 tokens
Output8,192 tokens
Mistral AI
MiniStral 3 (14B Instruct 2512)
Input- tokens
Output- tokens
Thu Jun 25 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

Both Mistral Large 3 and MiniStral 3 (14B Instruct 2512) support multimodal inputs.

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

Mistral Large 3

Text
Images
Audio
Video

MiniStral 3 (14B Instruct 2512)

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.

Mistral Large 3

Apache 2.0

Open weights

MiniStral 3 (14B Instruct 2512)

Apache 2.0

Open weights

Release Timeline

When each model was launched

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

MiniStral 3 (14B Instruct 2512) is 3 months newer than Mistral Large 3.

Mistral Large 3

Sep 1, 2025

9 months ago

MiniStral 3 (14B Instruct 2512)

Dec 4, 2025

6 months ago

3mo 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

Mistral AI
Larger context window (128,000 tokens)
Higher MM-MT-Bench score (84.9% vs 8.5%)
Mistral AI

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

Detailed Comparison

AI Model Comparison Table
Feature
Mistral AI
Mistral Large 3
Mistral AI
MiniStral 3 (14B Instruct 2512)

FAQ

Common questions about Mistral Large 3 vs MiniStral 3 (14B Instruct 2512).

Which is better, Mistral Large 3 or MiniStral 3 (14B Instruct 2512)?

Mistral Large 3 has a slight edge in benchmark performance. Mistral Large 3 is made by Mistral AI and MiniStral 3 (14B Instruct 2512) is made by Mistral AI. The best choice depends on your use case — compare their benchmark scores, pricing, and capabilities above.

How does Mistral Large 3 compare to MiniStral 3 (14B Instruct 2512) in benchmarks?

Mistral Large 3 scores MATH: 90.4%, MM-MT-Bench: 84.9%, MMLU-Redux: 82.0%, TriviaQA: 74.9%, MMMLU: 74.2%. MiniStral 3 (14B Instruct 2512) scores MATH: 90.4%, Wild Bench: 68.5%, Arena Hard: 55.1%, MM-MT-Bench: 8.5%.

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

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

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