Model benchmarks
Muse-Glimmer-30B-oQ8e local LLM performance
As of August 2026, Muse-Glimmer-30B-oQ8e runs at up to 17.2 tok/s for local inference (best of 3 community benchmark runs across 1 GPU).
Model size
30B
Peak speed
17.2 tok/s
Average speed
17.0 tok/s
Min memory
31.6 GB
Max context
131,072 tokens
Avg output / run
14,637 tokens
Avg runtime / run
15m 40s
Avg quality
83.9
Benchmark runs
3
GPUs tested
1
Quality by task
Average LLM-judged quality (0–100) with the run-to-run spread shown as a P5–P95 band, overall and for each benchmark task, across all 3 runs. The low and high columns show how much the judge’s score varies between runs, and need at least two runs to display.
| Task | P5 (low) | Avg | P95 (high) |
|---|---|---|---|
| Overall | 83.3 | 83.9 | 84.3 |
| Agent Workflow | 88.4 | 89.4 | 90.3 |
| Code Generation | 69.9 | 72.3 | 75.3 |
| Role Play & Narrative | 91.6 | 92.0 | 92.5 |
| Research & Analysis | 79.3 | 82.1 | 85.7 |
Performance by hardware and tool
Every hardware/tool/quantization combination Muse-Glimmer-30B-oQ8e has been benchmarked on, ranked by peak token generation speed. Last updated August 2026.
| Hardware | Tool | Quant | Best tok/s | Avg tok/s | Memory | Context | Quality | Runs |
|---|---|---|---|---|---|---|---|---|
| Apple M5 Max | oMLX | — | 17.2 tok/s | 17.0 tok/s | 31.6 GB | 131,072 tokens | 83.9 | 3 |
Benchmark runs
All 3 Muse-Glimmer-30B-oQ8e runs submitted so far — expand one for its hardware, quality breakdown and per-scenario detail.
Frequently asked questions
- Is Muse-Glimmer-30B-oQ8e good for coding?
- In our benchmarks, Muse-Glimmer-30B-oQ8e scores 72.3/100 for coding. It runs at about 17.0 tok/s, so if you want more speed, IsValorum/Nex-N2.5-mini-APEX-I-MiniPlus-V2.1-GGUF:1 is faster (~25.7 tok/s) and still scores well for coding (85.0/100).
- Is Muse-Glimmer-30B-oQ8e good for agentic (tool-using) tasks?
- In our benchmarks, Muse-Glimmer-30B-oQ8e scores 89.4/100 for agentic workflows. It runs at about 17.0 tok/s, so if you want more speed, granite-4.2-8b-Q4_K_L is faster (~71.6 tok/s) and still scores well for agentic workflows (92.9/100).
- How fast is Muse-Glimmer-30B-oQ8e for local inference?
- Across 3 community benchmark runs, Muse-Glimmer-30B-oQ8e reaches up to 17.2 tok/s and averages 17.0 tok/s, with the fastest results on Apple M5 Max.
- How much memory does Muse-Glimmer-30B-oQ8e need?
- The leanest observed configuration used about 31.6 GB of memory.
- Which tools have been used to run Muse-Glimmer-30B-oQ8e?
- Benchmarks were submitted using oMLX. Results are community-contributed and updated as new runs arrive.