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Muse Wonder vs Qwen2-VL-72B-Instruct

Muse Wonder leads the LLM Stats Score 47.9 to 14.3.

Meta · Alibaba Cloud / Qwen Team · Updated for 2026

Which is better?

Muse Wonder leads the overall LLM Stats Score 47.9 to 14.3, ranking #29 overall.

Based on current LLM Stats indexes, shared benchmarks, pricing, and model metadata for 2026.

Choose Muse Wonder

  • overall performance matters — it scores 47.9 and ranks #29 on LLM Stats
  • your work emphasizes reasoning — it leads those capability indexes
  • you want the most recent training data — it shipped Oct 2026

Choose Qwen2-VL-72B-Instruct

  • you need open weights you can self-host or fine-tune

At a glance

The differences that matter most.

Muse Wonder
Meta
Qwen2-VL-72B-Instruct
Alibaba Cloud / Qwen Team
Core performance indexes
LLM Stats Score
47.9
#29
14.3
#253
Reasoning
33.1
#108
11.6
#268
Cost, coverage & limits
Benchmark wins
—
—
Input price
$4.00 / M
— / M
Output price
$20.00 / M
— / M
Context window
1,048,576
—

Capability indexes

Additional strengths measured across groups of related public benchmarks

2 shared
Index
Muse Wonder
Qwen2-VL-72B-Instruct
Vision
25.4#53
10.5#131
Multimodal
25.4#52
11.4#123
Conservative TrueSkill rating · higher is betterHow scores work

Individual benchmarks

16 reported for Muse Wonder · 15 for Qwen2-VL-72B-Instruct

No common benchmarks found

Muse Wonder and Qwen2-VL-72B-Instructdon't have any common benchmark datasets to compare. They may have been evaluated on different testing suites.

Human preference

Blind head-to-head votes and playground preference scores

Context Window

Maximum input and output token capacity

Only Muse Wonder specifies input context (1,048,576 tokens).

Meta
Muse Wonder
Input1,048,576 tokens
Output- tokens
Alibaba Cloud / Qwen Team
Qwen2-VL-72B-Instruct
Input- tokens
Output- tokens
Wed Oct 14 2026 • llm-stats.com

Input capabilities

Documented input modalities across available providers

Both Muse Wonder and Qwen2-VL-72B-Instruct support multimodal inputs.

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

Muse Wonder

Text
Images
Audio
Video

Qwen2-VL-72B-Instruct

Text
Images
Audio
Video

License

Usage and distribution terms

Muse Wonder is licensed under a proprietary license, while Qwen2-VL-72B-Instruct uses tongyi-qianwen.

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

Muse Wonder

Proprietary

Closed source

Qwen2-VL-72B-Instruct

tongyi-qianwen

Open weights

Release Timeline

When each model was launched

Muse Wonder was released on 2026-10-12, while Qwen2-VL-72B-Instruct was released on 2024-08-29.

Muse Wonder is 26 months newer than Qwen2-VL-72B-Instruct.

Muse Wonder

Oct 12, 2026

1 days ago

2.1yr newer
Qwen2-VL-72B-Instruct

Aug 29, 2024

2.1 years ago

Knowledge Cutoff

When training data ends

Qwen2-VL-72B-Instruct has a documented knowledge cutoff of 2023-06-30, while Muse Wonder's cutoff date is not specified.

We can confirm Qwen2-VL-72B-Instruct's training data extends to 2023-06-30, but cannot make a direct comparison without Muse Wonder's cutoff date.

Muse Wonder

—

Qwen2-VL-72B-Instruct

Jun 2023

Outputs Comparison

Notice missing or incorrect data?

Judge for yourself.

Run your own prompts against Muse Wonder and Qwen2-VL-72B-Instruct side-by-side, then vote on the output you prefer.

Muse Wonder
✓ Preferred
Qwen2-VL-72B-Instruct
Open in Playground

FAQ

Common questions about Muse Wonder vs Qwen2-VL-72B-Instruct.

Which is better, Muse Wonder or Qwen2-VL-72B-Instruct?

Muse Wonder leads the LLM Stats Score 47.9 to 14.3. Muse Wonder is made by Meta and Qwen2-VL-72B-Instruct is made by Alibaba Cloud / Qwen Team. The best choice depends on your use case — compare their capability indexes, individual benchmarks, pricing, and limits above.

How does Muse Wonder compare to Qwen2-VL-72B-Instruct in benchmarks?

Muse Wonder scores MemoryBench: 85.6%, DeepSWE 1.1: 78.8%, OSWorld 2.1 (partial): 72.6%, JobBench: 70.5%, HealthBench Professional: 60.5%. Qwen2-VL-72B-Instruct scores DocVQAtest: 96.5%, VCR_en_easy: 91.9%, ChartQA: 88.3%, OCRBench: 87.7%, MMBench: 86.5%.

What are the context window sizes for Muse Wonder and Qwen2-VL-72B-Instruct?

Muse Wonder supports 1.0M tokens and Qwen2-VL-72B-Instruct supports an unknown number of tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.

What are the main differences between Muse Wonder and Qwen2-VL-72B-Instruct?

Key differences include LLM Stats Score (47.9 vs 14.3), licensing (Proprietary vs tongyi-qianwen). See the full comparison above for benchmark-by-benchmark results.

Who makes Muse Wonder and Qwen2-VL-72B-Instruct?

Muse Wonder is developed by Meta and Qwen2-VL-72B-Instruct is developed by Alibaba Cloud / Qwen Team.

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