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MiniStral 3 (14B Instruct 2512) vs QvQ-72B-Preview

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

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

Which is better?

MiniStral 3 (14B Instruct 2512) and QvQ-72B-Preview trade strengths across price, capabilities, and technical limits. The better choice depends on the workload.

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

Choose MiniStral 3 (14B Instruct 2512)

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

Choose QvQ-72B-Preview

  • you are already invested in the Alibaba Cloud / Qwen Team ecosystem

At a glance

The differences that matter most.

Benchmark wins
Input price
— / M
— / M
Output price
— / M
— / M
Context window
Released
Dec 2025
Dec 2024
License
Apache 2.0
Qwen

Performance Benchmarks

Comparative analysis across standard metrics

No common benchmarks found

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

Arena Performance

Playground indexes and blind preference scores

Model Size

Parameter count comparison

59.4B diff

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

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

Input Capabilities

Supported data types and modalities

Both MiniStral 3 (14B Instruct 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 Instruct 2512)

Text
Images
Audio
Video

QvQ-72B-Preview

Text
Images
Audio
Video

License

Usage and distribution terms

MiniStral 3 (14B Instruct 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 Instruct 2512)

Apache 2.0

Open weights

QvQ-72B-Preview

Qwen

Open weights

Release Timeline

When each model was launched

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

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

MiniStral 3 (14B Instruct 2512)

Dec 4, 2025

8 months ago

11mo newer
QvQ-72B-Preview

Dec 25, 2024

1.7 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 Instruct 2512) and QvQ-72B-Preview side-by-side, then vote on the output you prefer.

MiniStral 3 (14B Instruct 2512)
✓ Preferred
QvQ-72B-Preview
Open in Playground

FAQ

Common questions about MiniStral 3 (14B Instruct 2512) vs QvQ-72B-Preview.

Which is better, MiniStral 3 (14B Instruct 2512) or QvQ-72B-Preview?

MiniStral 3 (14B Instruct 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.

How does MiniStral 3 (14B Instruct 2512) compare to QvQ-72B-Preview in benchmarks?

MiniStral 3 (14B Instruct 2512) scores MATH: 90.4%, Wild Bench: 68.5%, Arena Hard: 55.1%, MM-MT-Bench: 8.5%. QvQ-72B-Preview scores MathVista: 71.4%, MMMU: 70.3%, MathVision: 35.9%, OlympiadBench: 20.4%.

What are the main differences between MiniStral 3 (14B Instruct 2512) and QvQ-72B-Preview?

Key differences include licensing (Apache 2.0 vs Qwen). See the full comparison above for benchmark-by-benchmark results.

Who makes MiniStral 3 (14B Instruct 2512) and QvQ-72B-Preview?

MiniStral 3 (14B Instruct 2512) is developed by Mistral AI and QvQ-72B-Preview is developed by Alibaba Cloud / Qwen Team.