Muse Glimmer benchmarks, pricing and specs
Muse Glimmer is a Meta model released on August 10, 2026 that takes text and image input and produces text. Its price is not published and accepts up to 131,072 tokens of context. It scores 1425 Elo on Arena Text, #41 of 49 current models (Arena, measured October 8, 2026).
- Context window
- 131K
- Arena Text
- 1425 Elo · #41/49
Data verified October 13, 2026 · Dataset 2026-10-13
Key facts
- Provider
- Meta
- Model family
- Muse Glimmer
- Release date
- August 10, 2026
- Status
- Current
- Access
- open weights
- API model id
- Not reported
- Context window
- 131,072 tokens
- Max output
- Not reported
- Input
- text, image
- Output
- text
- Task families
- text, multimodal
- Declared capabilities
- reasoning, coding, agentic coding, image understanding, document understanding
Muse Glimmer pricing
Independent benchmark results
Scores come from independent evaluators that ran the model themselves, pinned to a dated snapshot. Rank is among current models in the same snapshot. Meta's own launch figures are listed under strengths with the publisher named, because they are not measured the same way.
| Benchmark | Score | Rank | Measured | Source |
|---|---|---|---|---|
| Arena Text | 1425 Elo | #41 of 49 | October 8, 2026 | Arena · 2026-10-12 |
Strengths, cautions and best uses
Strengths
- A 30-billion-parameter open-weight model distilled from Muse Spark, released under Apache 2.0 for local agent workflows
- Meta reports that 4-bit quantization brings the language model under 20 GB, enough for one consumer GPU or a Mac
- Meta reports 76.0 on SWE-Bench Verified and 75.5 on MCP Atlas at high reasoning
Cautions
- Self-hosted only: Meta does not serve it over its Model API, so there is no first-party per-token price
- Audio is not supported and video is read as individual frames; the default context is 128K tokens
Best for
- Local or on-device coding agents on a single GPU
- Fine-tuning an Apache 2.0 multimodal base
Alternatives to Muse Glimmer
The closest current textmodels by price. The cheapest model that scores as well or better is listed first; failing that, the cheapest one within 3% of the benchmark's scale.
Nemotron 3.5 Lightning
- 76 points lower on Arena Text, 1349 vs 1425
- 1M context window vs 131K
- From NVIDIA
Grok 4.6
- 29 points higher on Arena Text, 1454 vs 1425
- 500K context window vs 131K
- From xAI
DeepSeek-V4-Pro
- 40 points higher on Arena Text, 1465 vs 1425
- 1M context window vs 131K
- From DeepSeek
Gemini 3.7 Flash
- 61 points higher on Arena Text, 1486 vs 1425
- 1.05M context window vs 131K
- From Google
Compare Muse Glimmer with
Articles about Muse Glimmer
- Muse Glimmer: The Reported Local Agent Model, ReviewedAugust 12, 2026
Muse Glimmer FAQ
What is the context window of Muse Glimmer?
Muse Glimmer accepts up to 131,072 tokens of context. That ranks #51 of 57 current text models by context length.
How does Muse Glimmer score on independent benchmarks?
Muse Glimmer scores 1425 Elo on Arena Text, #41 of 49 current models (Arena, measured October 8, 2026). These are independent evaluations, not Meta's own launch figures.
Is Muse Glimmer open source or API only?
Muse Glimmer is released as open weights that you can run yourself.
What are the best alternatives to Muse Glimmer?
The closest current alternatives by price and measured performance are Nemotron 3.5 Lightning (76 points lower on Arena Text, 1349 vs 1425), Grok 4.6 (29 points higher on Arena Text, 1454 vs 1425), DeepSeek-V4-Pro (40 points higher on Arena Text, 1465 vs 1425) and Gemini 3.7 Flash (61 points higher on Arena Text, 1486 vs 1425).
Sources
- Muse Glimmer documentation · Meta · official · verified October 13, 2026
- Introducing Muse Glimmer · Meta · official · verified October 13, 2026
- Arena leaderboard dataset (lmarena-ai/leaderboard-dataset) · Arena · independent · verified October 12, 2026 · CC-BY-4.0
Cite this page
Van Data Team. "Muse Glimmer Benchmarks, Pricing and Specs." AI Model Benchmark Dataset 2026-10-13. https://vandatateam.com/ai-model-benchmarks/muse-glimmer
Reuse the data: JSON · CSV · or explore every model in the AI model benchmark comparison.
Production evaluation
Deciding whether Muse Glimmer fits your workload?
Public benchmarks narrow the shortlist. We test the finalists on your own tasks, data and cost limits, then build the routing and review controls to run the winner in production.
- Evaluation cases and acceptance thresholds tied to real work
- Model routing, fallbacks and cost controls
