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Muse Ember vs Qwen3 VL 32B Thinking

Muse Ember leads the LLM Stats Score 45.9 to 22.9.

Meta · Alibaba Cloud / Qwen Team · Updated for 2026

Which is better?

Muse Ember leads the overall LLM Stats Score 45.9 to 22.9, 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 and agents — it leads those capability indexes
  • you want the most recent training data — it shipped Nov 2026

Choose Qwen3 VL 32B Thinking

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

At a glance

The differences that matter most.

Muse Ember
Meta
Qwen3 VL 32B Thinking
Alibaba Cloud / Qwen Team
Core performance indexes
LLM Stats Score
45.9
#47
22.9
#218
Reasoning
48.1
#24
24.0
#197
Agents
31.6
#45
12.3
#136
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
Qwen3 VL 32B Thinking
Vision
23.4#78
16.8#111
Multimodal
23.6#74
19.0#98
Conservative TrueSkill rating · higher is betterHow scores work

Individual benchmarks

6 reported for Muse Ember · 47 for Qwen3 VL 32B Thinking

No common benchmarks found

Muse Ember and Qwen3 VL 32B Thinkingdon'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
Qwen3 VL 32B Thinking
Input- tokens
Output- tokens
Thu Nov 12 2026 • llm-stats.com

Input capabilities

Documented input modalities across available providers

Both Muse Ember and Qwen3 VL 32B Thinking support multimodal inputs.

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

Muse Ember

Text
Images
Audio
Video

Qwen3 VL 32B Thinking

Text
Images
Audio
Video

License

Usage and distribution terms

Muse Ember is licensed under a proprietary license, while Qwen3 VL 32B Thinking uses Apache 2.0.

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

Muse Ember

Proprietary

Closed source

Qwen3 VL 32B Thinking

Apache 2.0

Open weights

Release Timeline

When each model was launched

Muse Ember was released on 2026-11-09, while Qwen3 VL 32B Thinking was released on 2025-09-22.

Muse Ember is 14 months newer than Qwen3 VL 32B Thinking.

Muse Ember

Nov 9, 2026

3 days ago

1.1yr newer
Qwen3 VL 32B Thinking

Sep 22, 2025

1.1 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?

Judge for yourself.

Run your own prompts against Muse Ember and Qwen3 VL 32B Thinking side-by-side, then vote on the output you prefer.

Muse Ember
✓ Preferred
Qwen3 VL 32B Thinking
Open in Playground

FAQ

Common questions about Muse Ember vs Qwen3 VL 32B Thinking.

Which is better, Muse Ember or Qwen3 VL 32B Thinking?

Muse Ember leads the LLM Stats Score 45.9 to 22.9. Muse Ember is made by Meta and Qwen3 VL 32B Thinking 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 Qwen3 VL 32B Thinking 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%. Qwen3 VL 32B Thinking scores DocVQAtest: 96.1%, ScreenSpot: 95.7%, MMLU-Redux: 91.9%, MMBench-V1.1: 90.8%, CharXiv-D: 90.2%.

What are the context window sizes for Muse Ember and Qwen3 VL 32B Thinking?

Muse Ember supports 1.0M tokens and Qwen3 VL 32B Thinking 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 Qwen3 VL 32B Thinking?

Key differences include LLM Stats Score (45.9 vs 22.9), licensing (Proprietary vs Apache 2.0). See the full comparison above for benchmark-by-benchmark results.

Who makes Muse Ember and Qwen3 VL 32B Thinking?

Muse Ember is developed by Meta and Qwen3 VL 32B Thinking is developed by Alibaba Cloud / Qwen Team.

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