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Muse Ember vs Qwen2-VL-72B-Instruct

Muse Ember leads the LLM Stats Score 45.9 to 13.6.

Meta · Alibaba Cloud / Qwen Team · Updated for 2026

Which is better?

Muse Ember leads the overall LLM Stats Score 45.9 to 13.6, ranking #47 overall.

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

Choose Muse Ember

  • overall performance matters — it scores 45.9 and ranks #47 on LLM Stats
  • your work emphasizes reasoning — it leads those capability indexes
  • you want the most recent training data — it shipped Nov 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.

Core performance indexes
45.9
#47
13.6
#284
48.1
#24
11.2
#295
Cost, coverage & limits
Benchmark wins
—
—
Input price
$0.10 / M
— / M
Output price
$0.50 / M
— / M
Context window
1,048,576
—

Capability indexes

Additional strengths measured across groups of related public benchmarks

2 shared
Index
Muse Ember
Qwen2-VL-72B-Instruct
23.4#78
10.1#152
23.6#74
10.9#138
Conservative TrueSkill rating · higher is betterHow scores work

Individual benchmarks

6 reported for Muse Ember · 15 for Qwen2-VL-72B-Instruct

No common benchmarks found

Muse Ember 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 Ember specifies input context (1,048,576 tokens). Only Muse Ember specifies output context (524,288 tokens).

Meta
Muse Ember
Input1,048,576 tokens
Output524,288 tokens
Alibaba Cloud / Qwen Team
Qwen2-VL-72B-Instruct
Input- tokens
Output- tokens
Thu Nov 12 2026 • llm-stats.com

Input capabilities

Documented input modalities across available providers

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

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

Muse Ember

Text
Images
Audio
Video

Qwen2-VL-72B-Instruct

Text
Images
Audio
Video

License

Usage and distribution terms

Muse Ember 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 Ember

Proprietary

Closed source

Qwen2-VL-72B-Instruct

tongyi-qianwen

Open weights

Release Timeline

When each model was launched

Muse Ember was released on 2026-11-09, while Qwen2-VL-72B-Instruct was released on 2024-08-29.

Muse Ember is 27 months newer than Qwen2-VL-72B-Instruct.

Muse Ember

Nov 9, 2026

3 days ago

2.2yr newer
Qwen2-VL-72B-Instruct

Aug 29, 2024

2.2 years ago

Knowledge Cutoff

When training data ends

Qwen2-VL-72B-Instruct has a documented knowledge cutoff of 2023-06-30, while Muse Ember'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 Ember's cutoff date.

Muse Ember

—

Qwen2-VL-72B-Instruct

Jun 2023

Outputs Comparison

Notice missing or incorrect data?

Judge for yourself.

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

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

FAQ

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

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

Muse Ember leads the LLM Stats Score 45.9 to 13.6. Muse Ember 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 Ember compare to Qwen2-VL-72B-Instruct in benchmarks?

Muse Ember scores PerceptionBench: 80.6%, OSWorld 2.1 (partial): 69.5%, Agents' Last Exam: 61.6%, Personal Superintelligence Index: 46.8%, Terminal-Bench 4.0: 40.9%. 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 Ember and Qwen2-VL-72B-Instruct?

Muse Ember 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 Ember and Qwen2-VL-72B-Instruct?

Key differences include LLM Stats Score (45.9 vs 13.6), licensing (Proprietary vs tongyi-qianwen). See the full comparison above for benchmark-by-benchmark results.

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

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