GLM-5.2 vs Muse Glimmer-30B
GLM-5.2 leads the LLM Stats Score 45.6 to 35.0. Muse Glimmer-30B is 2.2x cheaper per token.
Zhipu AI · Meta · Updated for 2026
Which is better?
GLM-5.2 leads the overall LLM Stats Score 45.6 to 35.0, ranking #27 overall.
In the 6 individual benchmarks reported for both models, GLM-5.2 wins 6; this is a narrower head-to-head signal than the composite indexes.
On price, Muse Glimmer-30B is roughly 2.2x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
GLM-5.2 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 GLM-5.2
- overall performance matters — it scores 45.6 and ranks #27 on LLM Stats
- your work emphasizes reasoning and coding — it leads those capability indexes
- you value its reported benchmark strengths — it wins 6 of 6 exact shared results
- you process long inputs — it offers a 1,048,576 token context window
Choose Muse Glimmer-30B
- cost matters — it's about 2.2x cheaper per token
- you want the most recent training data — it shipped Aug 2026
At a glance
The differences that matter most.
Capability indexes
Additional strengths measured across groups of related public benchmarks
Individual benchmarks
19 reported for GLM-5.2 · 25 for Muse Glimmer-30B
GLM-5.2 outperforms in 6 benchmarks (AIME 2026, GPQA, Humanity's Last Exam, MCP Atlas, SWE-Bench Pro, Terminal-Bench 2.1), while Muse Glimmer-30B is better at 0 benchmarks.
GLM-5.2 significantly outperforms across most 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 2.5x more expensive than Muse Glimmer-30B ($0.30/1M tokens).
For output processing, GLM-5.2 ($2.40/1M tokens) is 2.0x more expensive than Muse Glimmer-30B ($1.20/1M tokens).
In conclusion, GLM-5.2 is more expensive than Muse Glimmer-30B.*
* Using a 3:1 ratio of input to output tokens
Model Size
Parameter count comparison
GLM-5.2 has 723.4B more parameters than Muse Glimmer-30B, making it 2443.9% larger.
Context Window
Maximum input and output token capacity
GLM-5.2 accepts 1,048,576 input tokens compared to Muse Glimmer-30B's 131,072 tokens. GLM-5.2 can generate longer responses up to 1,048,576 tokens, while Muse Glimmer-30B is limited to 131,072 tokens.
Input capabilities
Documented input modalities across available providers
Muse Glimmer-30B supports multimodal inputs, whereas GLM-5.2 does not.
Muse Glimmer-30B can handle both text and other forms of data like images, making it suitable for multimodal applications.
GLM-5.2
Muse Glimmer-30B
License
Usage and distribution terms
GLM-5.2 is licensed under MIT, while Muse Glimmer-30B uses Apache 2.0.
License differences may affect how you can use these models in commercial or open-source projects.
MIT
Open weights
Apache 2.0
Open weights
Release Timeline
When each model was launched
GLM-5.2 was released on 2026-06-16, while Muse Glimmer-30B was released on 2026-08-10.
Muse Glimmer-30B is 2 months newer than GLM-5.2.
Jun 16, 2026
2 months ago
Aug 10, 2026
1 months ago
1mo newerKnowledge Cutoff
When training data ends
Muse Glimmer-30B has a documented knowledge cutoff of 2026-01-04, while GLM-5.2's cutoff date is not specified.
We can confirm Muse Glimmer-30B's training data extends to 2026-01-04, but cannot make a direct comparison without GLM-5.2's cutoff date.
—
Jan 2026
Provider Availability
GLM-5.2 is available from DeepInfra, Fireworks, FriendliAI, Novita, Together, ZAI. Muse Glimmer-30B is available from DeepInfra.
GLM-5.2
Muse Glimmer-30B
Outputs Comparison
Judge for yourself.
Run your own prompts against GLM-5.2 and Muse Glimmer-30B side-by-side, then vote on the output you prefer.
FAQ
Common questions about GLM-5.2 vs Muse Glimmer-30B.