GLM-5.3-Flash vs Muse Wonder
GLM-5.3-Flash and Muse Wonder are closely matched at 49.1 and 47.9 on the LLM Stats Score. GLM-5.3-Flash is 33.7x cheaper per token.
Zhipu AI · Meta · Updated for 2026
Which is better?
GLM-5.3-Flash and Muse Wonder are closely matched on the overall LLM Stats Score at 49.1 and 47.9.
The models split the 2 individual benchmarks reported for both models evenly.
On price, GLM-5.3-Flash is roughly 33.7x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
Based on current LLM Stats indexes, shared benchmarks, pricing, and model metadata for 2026.
Choose GLM-5.3-Flash
- your work emphasizes reasoning — it leads those capability indexes
- cost matters — it's about 33.7x cheaper per token
- you need open weights you can self-host or fine-tune
Choose Muse Wonder
- you want the most recent training data — it shipped Oct 2026
At a glance
The differences that matter most.
Capability indexes
Additional strengths measured across groups of related public benchmarks
Individual benchmarks
15 reported for GLM-5.3-Flash · 16 for Muse Wonder
GLM-5.3-Flash outperforms in 1 benchmarks (Artificial Analysis), while Muse Wonder is better at 1 benchmark (DeepSWE 1.1).
Both models are evenly matched across the benchmarks.
Human preference
Blind head-to-head votes and playground preference scores
Pricing Analysis
Price comparison per million tokens
For input processing, GLM-5.3-Flash ($0.15/1M tokens) is 26.7x cheaper than Muse Wonder ($4.00/1M tokens).
For output processing, GLM-5.3-Flash ($0.50/1M tokens) is 40.0x cheaper than Muse Wonder ($20.00/1M tokens).
In conclusion, Muse Wonder is more expensive than GLM-5.3-Flash.*
* Using a 3:1 ratio of input to output tokens
Context Window
Maximum input and output token capacity
Both models have the same input context window of 1,048,576 tokens. Only GLM-5.3-Flash specifies output context (1,048,576 tokens).
Input capabilities
Documented input modalities across available providers
Both GLM-5.3-Flash and Muse Wonder support multimodal inputs.
They are both capable of processing various types of data, offering versatility in application.
GLM-5.3-Flash
Muse Wonder
License
Usage and distribution terms
GLM-5.3-Flash is licensed under MIT, while Muse Wonder uses a proprietary license.
License differences may affect how you can use these models in commercial or open-source projects.
MIT
Open weights
Proprietary
Closed source
Release Timeline
When each model was launched
GLM-5.3-Flash was released on 2026-08-26, while Muse Wonder was released on 2026-10-12.
Muse Wonder is 2 months newer than GLM-5.3-Flash.
Aug 26, 2026
1 months ago
Oct 12, 2026
5 days ago
1mo newerKnowledge Cutoff
When training data ends
Neither model specifies a knowledge cutoff date.
Unable to compare the recency of their training data.
Provider Availability
GLM-5.3-Flash is available from DeepInfra, FriendliAI, Novita, ZAI. Muse Wonder is available from Meta Model API.
GLM-5.3-Flash
Muse Wonder
Outputs Comparison
Judge for yourself.
Run your own prompts against GLM-5.3-Flash and Muse Wonder side-by-side, then vote on the output you prefer.
FAQ
Common questions about GLM-5.3-Flash vs Muse Wonder.