GLM-5.2 vs Muse Wonder
GLM-5.2 and Muse Wonder are closely matched at 44.9 and 47.9 on the LLM Stats Score. GLM-5.2 is 6.9x cheaper per token.
Zhipu AI · Meta · Updated for 2026
Which is better?
GLM-5.2 and Muse Wonder are closely matched on the overall LLM Stats Score at 44.9 and 47.9.
In the 3 individual benchmarks reported for both models, Muse Wonder wins 2; this is a narrower head-to-head signal than the composite indexes.
On price, GLM-5.2 is roughly 6.9x 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-5.2
- cost matters — it's about 6.9x cheaper per token
- you need open weights you can self-host or fine-tune
Choose Muse Wonder
- your work emphasizes coding and agents — it leads those capability indexes
- you value its reported benchmark strengths — it wins 2 of 3 exact shared results
- you want the most recent training data — it shipped Oct 2026
At a glance
The differences that matter most.
Individual benchmarks
19 reported for GLM-5.2 · 16 for Muse Wonder
GLM-5.2 outperforms in 1 benchmarks (Program Bench), while Muse Wonder is better at 2 benchmarks (DeepSWE 1.1, SWE-Marathon).
Muse Wonder shows notably better performance in the majority of benchmarks.
Human preference
Blind head-to-head votes and playground preference scores
Pricing Analysis
Price comparison per million tokens
For input processing, GLM-5.2 ($0.75/1M tokens) is 5.3x cheaper than Muse Wonder ($4.00/1M tokens).
For output processing, GLM-5.2 ($2.40/1M tokens) is 8.3x cheaper than Muse Wonder ($20.00/1M tokens).
In conclusion, Muse Wonder is more expensive than GLM-5.2.*
* 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-5.2 specifies output context (1,048,576 tokens).
Input capabilities
Documented input modalities across available providers
Muse Wonder supports multimodal inputs, whereas GLM-5.2 does not.
Muse Wonder can handle both text and other forms of data like images, making it suitable for multimodal applications.
GLM-5.2
Muse Wonder
License
Usage and distribution terms
GLM-5.2 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-5.2 was released on 2026-06-16, while Muse Wonder was released on 2026-10-12.
Muse Wonder is 4 months newer than GLM-5.2.
Jun 16, 2026
3 months ago
Oct 12, 2026
1 days ago
3mo 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-5.2 is available from DeepInfra, Fireworks, FriendliAI, Novita, Together, ZAI. Muse Wonder is available from Meta Model API.
GLM-5.2
Muse Wonder
Outputs Comparison
Judge for yourself.
Run your own prompts against GLM-5.2 and Muse Wonder side-by-side, then vote on the output you prefer.
FAQ
Common questions about GLM-5.2 vs Muse Wonder.