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GLM-5.3-Flash vs Muse Glimmer-30B

GLM-5.3-Flash leads the LLM Stats Score 51.6 to 35.5.

Zhipu AI · Meta · Updated for 2026

Which is better?

GLM-5.3-Flash leads the overall LLM Stats Score 51.6 to 35.5, ranking #11 overall.

In the 3 individual benchmarks reported for both models, GLM-5.3-Flash wins 3; this is a narrower head-to-head signal than the composite indexes.

Based on current LLM Stats indexes, shared benchmarks, pricing, and model metadata for 2026.

Choose GLM-5.3-Flash

  • overall performance matters — it scores 51.6 and ranks #11 on LLM Stats
  • your work emphasizes reasoning and coding — it leads those capability indexes
  • you value its reported benchmark strengths — it wins 3 of 3 exact shared results
  • you want the most recent training data — it shipped Aug 2026

Choose Muse Glimmer-30B

  • you are already invested in the Meta ecosystem

At a glance

The differences that matter most.

GLM-5.3-Flash
Zhipu AI
Muse Glimmer-30B
Meta
Core performance indexes
LLM Stats Score
51.6
#11
35.5
#76
Reasoning
50.3
#13
34.7
#77
Coding
37.8
#22
23.8
#65
Agents
39.1
#9
18.5
#62
Cost, coverage & limits
Benchmark wins
3 of 3
0 of 3
Input price
$0.15 / M
— / M
Output price
$0.50 / M
— / M
Context window
1,048,576
—

Capability indexes

Additional strengths measured across groups of related public benchmarks

3 shared
Index
GLM-5.3-Flash
Muse Glimmer-30B
Vision
32.0#21
20.4#61
Tool use
34.2#4
18.6#59
Multimodal
30.9#24
23.2#47
Conservative TrueSkill rating · higher is betterHow scores work

Individual benchmarks

15 reported for GLM-5.3-Flash · 25 for Muse Glimmer-30B

3 shared

GLM-5.3-Flash outperforms in 3 benchmarks (CharXiv-R, Humanity's Last Exam, Terminal-Bench 2.1), while Muse Glimmer-30B is better at 0 benchmarks.

GLM-5.3-Flash significantly outperforms across most benchmarks.

Fri Aug 28 2026 • llm-stats.com

Human preference

Blind head-to-head votes and playground preference scores

Model Size

Parameter count comparison

290.4B diff

GLM-5.3-Flash has 290.4B more parameters than Muse Glimmer-30B, making it 981.1% larger.

Zhipu AI
GLM-5.3-Flash
320.0Bparameters
Meta
Muse Glimmer-30B
29.6Bparameters
320.0B
GLM-5.3-Flash
29.6B
Muse Glimmer-30B

Context Window

Maximum input and output token capacity

Only GLM-5.3-Flash specifies input context (1,048,576 tokens). Only GLM-5.3-Flash specifies output context (131,072 tokens).

Zhipu AI
GLM-5.3-Flash
Input1,048,576 tokens
Output131,072 tokens
Meta
Muse Glimmer-30B
Input- tokens
Output- tokens
Fri Aug 28 2026 • llm-stats.com

Input capabilities

Documented input modalities across available providers

Both GLM-5.3-Flash and Muse Glimmer-30B support multimodal inputs.

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

GLM-5.3-Flash

Text
Images
Audio
Video

Muse Glimmer-30B

Text
Images
Audio
Video

License

Usage and distribution terms

GLM-5.3-Flash 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.

GLM-5.3-Flash

MIT

Open weights

Muse Glimmer-30B

Apache 2.0

Open weights

Release Timeline

When each model was launched

GLM-5.3-Flash was released on 2026-08-26, while Muse Glimmer-30B was released on 2026-08-10.

GLM-5.3-Flash is 1 month newer than Muse Glimmer-30B.

GLM-5.3-Flash

Aug 26, 2026

2 days ago

2w newer
Muse Glimmer-30B

Aug 10, 2026

2 weeks ago

Knowledge Cutoff

When training data ends

Muse Glimmer-30B has a documented knowledge cutoff of 2026-01-04, while GLM-5.3-Flash'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-5.3-Flash's cutoff date.

GLM-5.3-Flash

—

Muse Glimmer-30B

Jan 2026

Outputs Comparison

Notice missing or incorrect data?Start an Issue discussion→

Judge for yourself.

Run your own prompts against GLM-5.3-Flash and Muse Glimmer-30B side-by-side, then vote on the output you prefer.

GLM-5.3-Flash
✓ Preferred
Muse Glimmer-30B
Open in Playground

FAQ

Common questions about GLM-5.3-Flash vs Muse Glimmer-30B.

Which is better, GLM-5.3-Flash or Muse Glimmer-30B?

GLM-5.3-Flash leads the LLM Stats Score 51.6 to 35.5. GLM-5.3-Flash is made by Zhipu AI and Muse Glimmer-30B is made by Meta. The best choice depends on your use case — compare their capability indexes, individual benchmarks, pricing, and limits above.

How does GLM-5.3-Flash compare to Muse Glimmer-30B in benchmarks?

GLM-5.3-Flash scores CharXiv-R: 89.4%, Terminal-Bench 2.1: 84.3%, MMVU: 80.5%, Toolathlon: 78.4%, Chartography: 78.0%. Muse Glimmer-30B scores AIME 2026: 94.7%, Siren AgentDojo Utility: 94.2%, GPQA: 83.5%, AA-LCR: 80.0%, CharXiv-R: 78.8%.

What are the context window sizes for GLM-5.3-Flash and Muse Glimmer-30B?

GLM-5.3-Flash supports 1.0M tokens and Muse Glimmer-30B 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 GLM-5.3-Flash and Muse Glimmer-30B?

Key differences include LLM Stats Score (51.6 vs 35.5), licensing (MIT vs Apache 2.0). See the full comparison above for benchmark-by-benchmark results.

Who makes GLM-5.3-Flash and Muse Glimmer-30B?

GLM-5.3-Flash is developed by Zhipu AI and Muse Glimmer-30B is developed by Meta.

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