Compare / Muse Glimmer 30B vs North Mini Code
Muse Glimmer 30B vs North Mini Code
Updated November 2026
Verdict
Muse Glimmer 30B scores higher on the Small LM Index: 70.1 vs 64.7, although their likely ranges overlap, so the lead is not certain. On the 3 benchmarks both labs report, Muse Glimmer 30B wins 3 and North Mini Code wins 0. Muse Glimmer 30B is smaller: it needs about 19.2 GB of memory at 4-bit, against 21.4 GB for North Mini Code. 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 need precise instruction following
- you have limited memory (about 19.2 GB at 4-bit)
- you want a hosted API rather than running it yourself
- you need a permissive license (Apache-2.0)
- you need image input
- you want the more widely used model (more quantized builds and community support)
Pick North Mini Code if…
- you work with long documents
Specifications
| Muse Glimmer 30B | North Mini Code | |
|---|---|---|
| Small LM Index | 70.1 (likely 69–72) | 64.7 (likely 55–72) |
| Lab | Meta · United States | Cohere · Other |
| Released | 2026-08-09 | 2026-06-17 |
| Parameters | 29.6B (dense) | 30B (3B active, MoE) |
| Memory at 4-bit | ~19.2 GB | ~21.4 GB |
| Context window | 131K tokens | 256K tokens |
| Input | text, image | text |
| Reasoning | Always thinks | No thinking |
| License | Apache-2.0 | Unverified |
| API price / 1M tokens | $0.53 ($0.30 in, $1.20 out) | Self-host only |
| Hugging Face downloads (30 days) | 187.5K | — |
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 | North Mini Code |
|---|---|---|
| GPQA Diamond Knowledge | 83.5✓ | 75.7✓ |
| Humanity's Last Exam Reasoning | 22.0✓ | 11.1✓ |
| AIME Math | 94.7 | ≈ 89 |
| SWE-bench Verified Coding | 76.0 | ≈ 56 |
| Terminal-Bench Agentic | 51.7 | — |
| τ²-Bench Agentic | — | 37.4✓ |
| IFBench Instruction following | 77.0 | 57.6✓ |
| MMMU-Pro Vision | 74.0 | — |
| AA-LCR Long context | — | 37.3✓ |
| SciCode Coding | — | 38.8✓ |
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 North Mini Code?
Muse Glimmer 30B scores higher on the Small LM Index: 70.1 vs 64.7, although their likely ranges overlap, so the lead is not certain. On the 3 benchmarks both labs report, Muse Glimmer 30B wins 3 and North Mini Code 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. Muse Glimmer 30B is smaller: it needs about 19.2 GB of memory at 4-bit, against 21.4 GB for North Mini Code.
Which has the longer context window?
North Mini Code has the longer context window: 256K tokens against 131K.
Can I use Muse Glimmer 30B and North Mini Code commercially?
Muse Glimmer 30B is released under Apache-2.0 and North Mini Code under Unverified. Apache 2.0 and MIT allow commercial use; other licenses can add conditions, so read the license before shipping a product.