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Ministral 3 (14B Base 2512) vs Qwen3 235B A22B

Qwen3 235B A22B significantly outperforms across most benchmarks.

Mistral AI · Alibaba Cloud / Qwen Team · Updated for 2026

Which is better?

Ministral 3 (14B Base 2512) outperforms in 0 benchmarks, while Qwen3 235B A22B is better at 2 benchmarks (MMLU, MMLU-Redux). Qwen3 235B A22B significantly outperforms across most benchmarks.

Based on current benchmark, pricing, and model metadata for 2026.

Choose Ministral 3 (14B Base 2512)

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

Choose Qwen3 235B A22B

  • you want the strongest raw capability — it leads on 2 of 2 shared benchmarks

At a glance

The differences that matter most.

Benchmark wins
0 of 2
2 of 2
Input price
— / M
$0.10 / M
Output price
— / M
$0.10 / M
Context window
128,000
Released
Dec 2025
Apr 2025
License
Apache 2.0
Apache 2.0

Performance Benchmarks

Comparative analysis across standard metrics

2 benchmarks

Ministral 3 (14B Base 2512) outperforms in 0 benchmarks, while Qwen3 235B A22B is better at 2 benchmarks (MMLU, MMLU-Redux).

Qwen3 235B A22B significantly outperforms across most benchmarks.

Thu Aug 27 2026 • llm-stats.com

Arena Performance

Playground indexes and blind preference scores

Model Size

Parameter count comparison

221.0B diff

Qwen3 235B A22B has 221.0B more parameters than Ministral 3 (14B Base 2512), making it 1578.6% larger.

Mistral AI
Ministral 3 (14B Base 2512)
14.0Bparameters
Alibaba Cloud / Qwen Team
Qwen3 235B A22B
235.0Bparameters
14.0B
Ministral 3 (14B Base 2512)
235.0B
Qwen3 235B A22B

Context Window

Maximum input and output token capacity

Only Qwen3 235B A22B specifies input context (128,000 tokens). Only Qwen3 235B A22B specifies output context (128,000 tokens).

Mistral AI
Ministral 3 (14B Base 2512)
Input- tokens
Output- tokens
Alibaba Cloud / Qwen Team
Qwen3 235B A22B
Input128,000 tokens
Output128,000 tokens
Thu Aug 27 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

Ministral 3 (14B Base 2512) supports multimodal inputs, whereas Qwen3 235B A22B does not.

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

Ministral 3 (14B Base 2512)

Text
Images
Audio
Video

Qwen3 235B A22B

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

Qwen3 235B A22B

Apache 2.0

Open weights

Release Timeline

When each model was launched

Ministral 3 (14B Base 2512) was released on 2025-12-04, while Qwen3 235B A22B was released on 2025-04-29.

Ministral 3 (14B Base 2512) is 7 months newer than Qwen3 235B A22B.

Ministral 3 (14B Base 2512)

Dec 4, 2025

8 months ago

7mo newer
Qwen3 235B A22B

Apr 29, 2025

1.3 years 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

Judge for yourself.

Run your own prompts against Ministral 3 (14B Base 2512) and Qwen3 235B A22B side-by-side, then vote on the output you prefer.

Ministral 3 (14B Base 2512)
✓ Preferred
Qwen3 235B A22B
Open in Playground

FAQ

Common questions about Ministral 3 (14B Base 2512) vs Qwen3 235B A22B.

Which is better, Ministral 3 (14B Base 2512) or Qwen3 235B A22B?

Qwen3 235B A22B significantly outperforms across most benchmarks. Ministral 3 (14B Base 2512) is made by Mistral AI and Qwen3 235B A22B is made by Alibaba Cloud / Qwen Team. 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 Qwen3 235B A22B 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%. Qwen3 235B A22B scores Arena Hard: 95.6%, GSM8k: 94.4%, BBH: 88.9%, MMLU: 87.8%, MMLU-Redux: 87.4%.

What are the context window sizes for Ministral 3 (14B Base 2512) and Qwen3 235B A22B?

Ministral 3 (14B Base 2512) supports an unknown number of tokens and Qwen3 235B A22B supports 128K tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.

What are the main differences between Ministral 3 (14B Base 2512) and Qwen3 235B A22B?

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

Who makes Ministral 3 (14B Base 2512) and Qwen3 235B A22B?

Ministral 3 (14B Base 2512) is developed by Mistral AI and Qwen3 235B A22B is developed by Alibaba Cloud / Qwen Team.