Muse Glimmer
Intelligence benchmarks
Artificial Analysis indexes - compared with the best open and proprietary models
Intelligence
6.3
AA Index
Coding
1.1
AA Index
Agentic
8.4
AA Index
Intelligence Index - Muse Glimmer vs. the field
Best open-weight models (you can run locally) and leading proprietary models for context.
Coding Index comparison
Agentic Index comparison
Benchmark data from Artificial Analysis · updated 2026-11-12.
Hosted API cost & speed
What it costs to rent this model instead of running it locally
| Metric | Value |
|---|---|
| Input (per 1M tokens) | $0.30 |
| Output (per 1M tokens) | $1.20 |
| Median speed (hosted API) | 106 tok/s |
Median across hosted providers, measured by Artificial Analysis - updated 2026-11-12. Local llama.cpp speed depends on your hardware — see the hardware pages for estimates.
Arena rating (LMArena)
Human preference wins from head-to-head chat battles
| Metric | Value |
|---|---|
| Overall arena rating | 1388.9 |
| Rank (overall) | #172 |
| Battle votes | 3,793 |
Overall rating published by LMArena on 2026-11-09 - a pairwise human-preference Elo across live chat battles; higher is better. Fetched 2026-11-12. Open-weights models compete head-to-head with proprietary ones here — no benchmark prompts, just what people pick.
Standard benchmarks
Performance across standard evaluations
| Benchmark | Score |
|---|---|
| GPQA Diamond | 83.5 |
| HLE | 22 |
| SciCode | 44.9 |
Source: Artificial Analysis component evals - updated 2026-11-12.
Will it run on your hardware?
Pick your GPU memory - see which quantizations fit, and the cheapest card for the rest
Need an exact figure for your context length? Use the VRAM calculator.
Run it locally
Copy-paste - running in under a minute
vllm serve RadixArk/Muse-Glimmer-NVFP4New to this? Start with Ollama · serve to many users with vLLM.
Deep dive
Notes, sources, and the full write-up
Muse Glimmer is a 18.1B-parameter open-weight model from Meta. It scores 6.3 on the Artificial Analysis Intelligence Index (coding 1.1). At Q4_K_M it needs roughly 10 GB of VRAM, placing it in the 8–12 GB GPU hardware tier.
BenchmarksLink to this section
Artificial Analysis Intelligence Index - Muse Glimmer vs. leading closed models:
| Model | Intelligence | Coding | GPQA |
|---|---|---|---|
| Muse Glimmer | 6.3 | 1.1 | 83.5 |
| Claude Fable 5.2 | 64.6 | 53.1 | - |
| Gemini 4 Carbon | 60 | 50.4 | - |
| Claude Opus 5.5 | 59.1 | 51.7 | - |
| GPT-6 Astra | 56.9 | 49.1 | 96.1 |
| GPT-6.1 Sol | 54.6 | 46.8 | - |
Source: Artificial Analysis (2026-11-12).
PopularityLink to this section
Muse Glimmer has 40 downloads in the last month on HuggingFace and 5 likes.
Frequently asked
Quick answers to common questions
How much VRAM does Muse Glimmer need?
Muse Glimmer with 18.1B parameters needs approximately 10 GB at Q4_K_M quantization. Use our VRAM calculator for an exact estimate.
Is Muse Glimmer better than other meta-models models?
Muse Glimmer has 18.1B parameters with 131,072 context - a strong choice for vision, long-context, general-chat.
What license is Muse Glimmer under?
Muse Glimmer is released under the Open Weights license, making it suitable for most commercial and personal projects.
What hardware runs Muse Glimmer well?
With 18.1B parameters, Muse Glimmer requires adequate VRAM. High-end GPUs like the RTX 4090 (24GB), RTX 5090 (32GB), or Mac Studio with unified memory are good options. Check our hardware directory for specific recommendations.
What is the best quantization for Muse Glimmer?
Q4_K_M is the recommended sweet spot - ~98% of FP16 quality at ~27% of the size. Q5_K_M (~13 GB) is an option if you have spare VRAM. Use our VRAM calculator to compare.
How long can Muse Glimmer's context window handle?
Muse Glimmer supports a 131,072-token context window - enough for very long documents, codebases, or multi-turn conversations. Real-world usable context may vary by implementation.
What models compete with Muse Glimmer?
Muse Glimmer competes with other models in its class. Browse our model directory for comparisons, benchmarks, and community reviews to find the best fit.
Nearby options
Similar models and compatible hardware by spec