Muse Wonder vs Qwen3 VL 30B A3B Instruct
Muse Wonder leads the LLM Stats Score 47.9 to 16.4. Qwen3 VL 30B A3B Instruct is 30.5x cheaper per token.
Meta · Alibaba Cloud / Qwen Team · Updated for 2026
Which is better?
Muse Wonder leads the overall LLM Stats Score 47.9 to 16.4, ranking #29 overall.
On price, Qwen3 VL 30B A3B Instruct is roughly 30.5x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
Muse Wonder also accepts a larger context window (1,048,576 input tokens), making it the stronger choice for long documents and large codebases.
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 and agents — it leads those capability indexes
- you process long inputs — it offers a 1,048,576 token context window
- you want the most recent training data — it shipped Oct 2026
Choose Qwen3 VL 30B A3B Instruct
- cost matters — it's about 30.5x cheaper per token
- you need open weights you can self-host or fine-tune
At a glance
The differences that matter most.
Capability indexes
Additional strengths measured across groups of related public benchmarks
Individual benchmarks
16 reported for Muse Wonder · 50 for Qwen3 VL 30B A3B Instruct
Muse Wonder and Qwen3 VL 30B A3B 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
Pricing Analysis
Price comparison per million tokens
For input processing, Muse Wonder ($4.00/1M tokens) is 26.7x more expensive than Qwen3 VL 30B A3B Instruct ($0.15/1M tokens).
For output processing, Muse Wonder ($20.00/1M tokens) is 33.3x more expensive than Qwen3 VL 30B A3B Instruct ($0.60/1M tokens).
In conclusion, Muse Wonder is more expensive than Qwen3 VL 30B A3B Instruct.*
* Using a 3:1 ratio of input to output tokens
Context Window
Maximum input and output token capacity
Muse Wonder accepts 1,048,576 input tokens compared to Qwen3 VL 30B A3B Instruct's 262,144 tokens. Only Qwen3 VL 30B A3B Instruct specifies output context (262,144 tokens).
Input capabilities
Documented input modalities across available providers
Both Muse Wonder and Qwen3 VL 30B A3B Instruct support multimodal inputs.
They are both capable of processing various types of data, offering versatility in application.
Muse Wonder
Qwen3 VL 30B A3B Instruct
License
Usage and distribution terms
Muse Wonder is licensed under a proprietary license, while Qwen3 VL 30B A3B Instruct uses Apache 2.0.
License differences may affect how you can use these models in commercial or open-source projects.
Proprietary
Closed source
Apache 2.0
Open weights
Release Timeline
When each model was launched
Muse Wonder was released on 2026-10-12, while Qwen3 VL 30B A3B Instruct was released on 2025-09-22.
Muse Wonder is 13 months newer than Qwen3 VL 30B A3B Instruct.
Oct 12, 2026
1 days ago
1.1yr newerSep 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.
Provider Availability
Muse Wonder is available from Meta Model API. Qwen3 VL 30B A3B Instruct is available from DeepInfra, Novita.
Muse Wonder
Qwen3 VL 30B A3B Instruct
Outputs Comparison
Judge for yourself.
Run your own prompts against Muse Wonder and Qwen3 VL 30B A3B Instruct side-by-side, then vote on the output you prefer.
FAQ
Common questions about Muse Wonder vs Qwen3 VL 30B A3B Instruct.