Model Comparison

Ministral 3 (14B Reasoning 2512) vs QvQ-72B-Preview

Comparing Ministral 3 (14B Reasoning 2512) and QvQ-72B-Preview across benchmarks, pricing, and capabilities.

Want to compare interactively?Try the playground

Performance Benchmarks

Comparative analysis across standard metrics

No common benchmarks found

Ministral 3 (14B Reasoning 2512) and QvQ-72B-Preview don't have any common benchmark datasets to compare. They may have been evaluated on different testing suites.

Arena Performance

Human preference votes

Pricing Analysis

Price comparison per million tokens

Cost data unavailable.

Lowest available price from all providers
Tue Apr 14 2026 • llm-stats.com
Mistral AI
Ministral 3 (14B Reasoning 2512)
Input tokens$0.20
Output tokens$0.20
Best providerMistral
Alibaba Cloud / Qwen Team
QvQ-72B-Preview
Input tokens$0.00
Output tokens$0.00
Best providerUnknown Organization
Notice missing or incorrect data?Start an Issue→

Model Size

Parameter count comparison

59.4B diff

QvQ-72B-Preview has 59.4B more parameters than Ministral 3 (14B Reasoning 2512), making it 424.3% larger.

Mistral AI
Ministral 3 (14B Reasoning 2512)
14.0Bparameters
Alibaba Cloud / Qwen Team
QvQ-72B-Preview
73.4Bparameters
14.0B
Ministral 3 (14B Reasoning 2512)
73.4B
QvQ-72B-Preview

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).

Mistral AI
Ministral 3 (14B Reasoning 2512)
Input262,100 tokens
Output262,100 tokens
Alibaba Cloud / Qwen Team
QvQ-72B-Preview
Input- tokens
Output- tokens
Tue Apr 14 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

Both Ministral 3 (14B Reasoning 2512) and QvQ-72B-Preview support multimodal inputs.

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

Ministral 3 (14B Reasoning 2512)

Text
Images
Audio
Video

QvQ-72B-Preview

Text
Images
Audio
Video

License

Usage and distribution terms

Ministral 3 (14B Reasoning 2512) is licensed under Apache 2.0, while QvQ-72B-Preview uses Qwen.

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

Ministral 3 (14B Reasoning 2512)

Apache 2.0

Open weights

QvQ-72B-Preview

Qwen

Open weights

Release Timeline

When each model was launched

Ministral 3 (14B Reasoning 2512) was released on 2025-12-04, while QvQ-72B-Preview was released on 2024-12-25.

Ministral 3 (14B Reasoning 2512) is 11 months newer than QvQ-72B-Preview.

Ministral 3 (14B Reasoning 2512)

Dec 4, 2025

4 months ago

11mo newer
QvQ-72B-Preview

Dec 25, 2024

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→

Key Takeaways

Mistral AI
Larger context window (262,100 tokens)
Alibaba Cloud / Qwen Team

QvQ-72B-Preview

View details

Alibaba Cloud / Qwen Team

Detailed Comparison

AI Model Comparison Table
Feature
Mistral AI
Ministral 3 (14B Reasoning 2512)
Alibaba Cloud / Qwen Team
QvQ-72B-Preview

FAQ

Common questions about Ministral 3 (14B Reasoning 2512) vs QvQ-72B-Preview

Ministral 3 (14B Reasoning 2512) (Mistral AI) and QvQ-72B-Preview (Alibaba Cloud / Qwen Team) each have strengths in different areas. Compare their benchmark scores, pricing, context windows, and capabilities above to determine which fits your needs.
Ministral 3 (14B Reasoning 2512) scores AIME 2024: 89.8%, AIME 2025: 85.0%, GPQA: 71.2%, LiveCodeBench: 64.6%. QvQ-72B-Preview scores MathVista: 71.4%, MMMU: 70.3%, MathVision: 35.9%, OlympiadBench: 20.4%.
Ministral 3 (14B Reasoning 2512) supports 262K tokens and QvQ-72B-Preview supports an unknown number of tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.
Key differences include licensing (Apache 2.0 vs Qwen). See the full comparison above for benchmark-by-benchmark results.
Ministral 3 (14B Reasoning 2512) is developed by Mistral AI and QvQ-72B-Preview is developed by Alibaba Cloud / Qwen Team.