Compare / Muse Glimmer 30B vs Granite 4.2 30B
Muse Glimmer 30B vs Granite 4.2 30B
Updated November 2026
Verdict
Muse Glimmer 30B scores higher on the Small LM Index: 72.6 vs 67.0. On the 4 benchmarks both labs report, Muse Glimmer 30B wins 3 and Granite 4.2 30B wins 1. Muse Glimmer 30B is smaller: it needs about 19.2 GB of memory at 4-bit, against 21.4 GB for Granite 4.2 30B. 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 build agents that call tools
- you have limited memory (about 19.2 GB at 4-bit)
- you want a hosted API rather than running it yourself
- you need image input
- you want the more widely used model (more quantized builds and community support)
Pick Granite 4.2 30B if…
- you need precise instruction following
Specifications
| Muse Glimmer 30B | Granite 4.2 30B | |
|---|---|---|
| Small LM Index | 72.6 (likely 71–74) | 67.0 (likely 66–69) |
| Lab | Meta · United States | IBM (Granite) · United States |
| Released | 2026-08-09 | 2026-08-07 |
| Parameters | 29.6B (dense) | 30B (dense) |
| Memory at 4-bit | ~19.2 GB | ~21.4 GB |
| Context window | 131K tokens | 131K tokens |
| Input | text, image | text |
| Reasoning | Always thinks | No thinking |
| 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 | 32K |
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 | Granite 4.2 30B |
|---|---|---|
| MMLU-Pro Knowledge | ≈ 86 | 77.6 |
| GPQA Diamond Knowledge | 83.5✓ | 66.4 |
| Humanity's Last Exam Reasoning | 22.0✓ | ≈ 15 |
| AIME Math | 94.7 | 89.2 |
| LiveCodeBench Coding | ≈ 83 | 75.8 |
| SWE-bench Verified Coding | 76.0 | ≈ 58 |
| Terminal-Bench Agentic | 51.7 | 29.2 |
| IFBench Instruction following | 77.0 | 77.2 |
| MMMU-Pro Vision | 74.0 | — |
| BFCL Agentic | — | 61.4 |
| HMMT Math | — | 89.2 |
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 Granite 4.2 30B?
Muse Glimmer 30B scores higher on the Small LM Index: 72.6 vs 67.0. On the 4 benchmarks both labs report, Muse Glimmer 30B wins 3 and Granite 4.2 30B wins 1.
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. Muse Glimmer 30B is smaller: it needs about 19.2 GB of memory at 4-bit, against 21.4 GB for Granite 4.2 30B.
Which has the longer context window?
Both have a 131K-token context window.
Can I use Muse Glimmer 30B and Granite 4.2 30B 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.