Compare / Muse Glimmer 30B vs Qwen3 30B-A3B Thinking 2507
Muse Glimmer 30B vs Qwen3 30B-A3B Thinking 2507
Updated November 2026
Verdict
Muse Glimmer 30B scores higher on the Small LM Index: 72.6 vs 59.3. On the 5 benchmarks both labs report, Muse Glimmer 30B wins 5 and Qwen3 30B-A3B Thinking 2507 wins 0. Both need about 20.4 GB of memory at 4-bit quantization. Only Muse Glimmer 30B has a hosted API on OpenRouter ($0.53 per million tokens); the other has to be self-hosted.
Pick Muse Glimmer 30B if…
- you want the strongest model overall
- you mostly write code
- you need math and reasoning
- you need precise instruction following
- you want a hosted API rather than running it yourself
- you need image input
Pick Qwen3 30B-A3B Thinking 2507 if…
- you work with long documents
Specifications
| Muse Glimmer 30B | Qwen3 30B-A3B Thinking 2507 | |
|---|---|---|
| Small LM Index | 72.6 (likely 71–74) | 59.3 (likely 55–63) |
| Lab | Meta · United States | Alibaba (Qwen) · China |
| Released | 2026-08-09 | 2025-07-30 |
| Parameters | 29.6B (dense) | 30.5B (3.3B active, MoE) |
| Memory at 4-bit | ~19.2 GB | ~20.4 GB |
| Context window | 131K tokens | 262K tokens |
| Input | text, image | text |
| Reasoning | Always thinks | Always thinks |
| License | Apache-2.0 | Apache-2.0 |
| API price / 1M tokens | $0.53 ($0.30 in, $1.20 out) | Self-host only |
| Hugging Face downloads (30 days) | 189.7K | 66.6K |
Benchmarks
Higher is better. Bold marks the winner where both labs report a score. ≈ marks the index model's estimate for a score that wasn't reported, ✓ an independent measurement and * a score measured by another lab.
| Benchmark | Muse Glimmer 30B | Qwen3 30B-A3B Thinking 2507 |
|---|---|---|
| MMLU-Pro Knowledge | ≈ 86 | 80.9 |
| GPQA Diamond Knowledge | 83.5✓ | 73.4 |
| Humanity's Last Exam Reasoning | 22.0✓ | 9.8 |
| AIME Math | 94.7 | 85.0 |
| LiveCodeBench Coding | ≈ 83 | 66.0 |
| SWE-bench Verified Coding | 76.0 | 22.0* |
| Terminal-Bench Agentic | 51.7 | — |
| IFBench Instruction following | 77.0 | 51.5 |
| MMMU-Pro Vision | 74.0 | — |
Scores are mostly reported by each lab with its own settings, so small gaps are noise. See the methodology. Open in the interactive comparison to add more models.
Questions
Which is better, Muse Glimmer 30B or Qwen3 30B-A3B Thinking 2507?
Muse Glimmer 30B scores higher on the Small LM Index: 72.6 vs 59.3. On the 5 benchmarks both labs report, Muse Glimmer 30B wins 5 and Qwen3 30B-A3B Thinking 2507 wins 0.
Which is cheaper to run?
Only Muse Glimmer 30B has a hosted API on OpenRouter ($0.53 per million tokens); the other has to be self-hosted. Both need about 20.4 GB of memory at 4-bit quantization.
Which has the longer context window?
Qwen3 30B-A3B Thinking 2507 has the longer context window: 262K tokens against 131K.
Can I use Muse Glimmer 30B and Qwen3 30B-A3B Thinking 2507 commercially?
Both are released under the Apache-2.0 license. Apache 2.0 and MIT allow commercial use; other licenses can add conditions, so read the license before shipping a product.