Muse Glimmer 30B
Not tested yet
Language modelOpen source
Muse Glimmer 30B
Meta
- Released
- August 10, 2026
- Data date
- September 8, 2026
- Intelligence
- Overall score
- Speed
- 105.6 tokens/sOutput throughput
- Price
- Input · Output / 1M tokens
- Input
- Text, Image
- Output
- Text
No published category-wide ranking is available for this model.
Entries 1-12 of 32. Page 1 of 3.
Measurements without matching peer values
These measurements have no matching peer values under the same test conditions. Their original values and sources remain available here.
MCP Atlas (Show measurement, test conditions, and source)
- Source value
- 75.5
- Score
- 75.5
- Metric
- percent
- Unit
- %
- Direction
- Higher is better
- Comparison cohort
- research:meta-muse-glimmer-30b:0
- Source type
- vendor-reported
- Evaluator
- Meta Muse Glimmer model card
- Status
- active
- Retrieved at
- 2026-09-08
- Methodology
- Vendor-reported result. Muse benchmark table; configuration as reported by card
DeepSearch QA (Show measurement, test conditions, and source)
- Source value
- 74.6
- Score
- 74.6
- Metric
- percent
- Unit
- %
- Direction
- Higher is better
- Comparison cohort
- research:meta-muse-glimmer-30b:1
- Source type
- vendor-reported
- Evaluator
- Meta Muse Glimmer model card
- Status
- active
- Retrieved at
- 2026-09-08
- Methodology
- Vendor-reported result. Muse benchmark table; configuration as reported by card
tau3 Banking (Show measurement, test conditions, and source)
- Source value
- 23.5
- Score
- 23.5
- Metric
- percent
- Unit
- %
- Direction
- Higher is better
- Comparison cohort
- research:meta-muse-glimmer-30b:2
- Source type
- vendor-reported
- Evaluator
- Meta Muse Glimmer model card
- Status
- active
- Retrieved at
- 2026-09-08
- Methodology
- Vendor-reported result. Muse benchmark table; configuration as reported by card
WildClaw (Show measurement, test conditions, and source)
- Source value
- 47.6
- Score
- 47.6
- Metric
- percent
- Unit
- %
- Direction
- Higher is better
- Comparison cohort
- research:meta-muse-glimmer-30b:3
- Source type
- vendor-reported
- Evaluator
- Meta Muse Glimmer model card
- Status
- active
- Retrieved at
- 2026-09-08
- Methodology
- Vendor-reported result. Muse benchmark table; configuration as reported by card
Gaia2 (Show measurement, test conditions, and source)
- Source value
- 43.3
- Score
- 43.3
- Metric
- percent
- Unit
- %
- Direction
- Higher is better
- Comparison cohort
- research:meta-muse-glimmer-30b:5
- Source type
- vendor-reported
- Evaluator
- Meta Muse Glimmer model card
- Status
- active
- Retrieved at
- 2026-09-08
- Methodology
- Vendor-reported result. Muse benchmark table; configuration as reported by card
SkillsBench (Show measurement, test conditions, and source)
- Source value
- 44.3
- Score
- 44.3
- Metric
- percent
- Unit
- %
- Direction
- Higher is better
- Comparison cohort
- research:meta-muse-glimmer-30b:6
- Source type
- vendor-reported
- Evaluator
- Meta Muse Glimmer model card
- Status
- active
- Retrieved at
- 2026-09-08
- Methodology
- Vendor-reported result. Muse benchmark table; configuration as reported by card
OSWorld Verified (Show measurement, test conditions, and source)
- Source value
- 65.9
- Score
- 65.9
- Metric
- percent
- Unit
- %
- Direction
- Higher is better
- Comparison cohort
- research:meta-muse-glimmer-30b:7
- Source type
- vendor-reported
- Evaluator
- Meta Muse Glimmer model card
- Status
- active
- Retrieved at
- 2026-09-08
- Methodology
- Vendor-reported result. Muse benchmark table; configuration as reported by card
SWE-Bench Pro (Show measurement, test conditions, and source)
- Source value
- 51.2
- Score
- 51.2
- Metric
- percent
- Unit
- %
- Direction
- Higher is better
- Comparison cohort
- research:meta-muse-glimmer-30b:8
- Source type
- vendor-reported
- Evaluator
- Meta Muse Glimmer model card
- Status
- active
- Retrieved at
- 2026-09-08
- Methodology
- Vendor-reported result. Muse benchmark table; configuration as reported by card
SWE Verified (Show measurement, test conditions, and source)
- Source value
- 76
- Score
- 76
- Metric
- percent
- Unit
- %
- Direction
- Higher is better
- Comparison cohort
- research:meta-muse-glimmer-30b:9
- Source type
- vendor-reported
- Evaluator
- Meta Muse Glimmer model card
- Status
- active
- Retrieved at
- 2026-09-08
- Methodology
- Vendor-reported result. Muse benchmark table; configuration as reported by card
TerminalBench 2.1 (Show measurement, test conditions, and source)
- Source value
- 51.7
- Score
- 51.7
- Metric
- percent
- Unit
- %
- Direction
- Higher is better
- Comparison cohort
- research:meta-muse-glimmer-30b:10
- Source type
- vendor-reported
- Evaluator
- Meta Muse Glimmer model card
- Status
- active
- Retrieved at
- 2026-09-08
- Methodology
- Vendor-reported result. Muse benchmark table; configuration as reported by card
SciCode (Show measurement, test conditions, and source)
- Source value
- 43.6
- Score
- 43.6
- Metric
- percent
- Unit
- %
- Direction
- Higher is better
- Comparison cohort
- research:meta-muse-glimmer-30b:11
- Source type
- vendor-reported
- Evaluator
- Meta Muse Glimmer model card
- Status
- active
- Retrieved at
- 2026-09-08
- Methodology
- Vendor-reported result. Muse benchmark table; configuration as reported by card
Charxiv (Show measurement, test conditions, and source)
- Source value
- 78.8
- Score
- 78.8
- Metric
- percent
- Unit
- %
- Direction
- Higher is better
- Comparison cohort
- research:meta-muse-glimmer-30b:12
- Source type
- vendor-reported
- Evaluator
- Meta Muse Glimmer model card
- Status
- active
- Retrieved at
- 2026-09-08
- Methodology
- Vendor-reported result. Muse benchmark table; configuration as reported by card
Our model tests
Community tests you can inspect
Compare how the models respond to the same prompt. Each test shows the first attempt, with no subsequent fixes to the generated code. These results do not contribute to an overall score.
Pelican on a bicycle
A community classic for free-form SVG drawing.
Prompt and test conditions
Generate an SVG of a pelican riding a bicycle
Token limit including reasoning: 8,192 tokens
Task origin (Simon Willison)Profile
Specifications and access
Published information about this model. Existing estimates are explicitly labeled.
Additional source observations
Dated documentation and model-card observations. Provider limits, native context and extended context can differ. Configuration notes retain the source wording.
- License
- Apache-2.0Source
- Release
- 2026-08Source
- Parameters
- 29.6 BSource
- Active parameters
- 29.6 BSource
- Architecture
- dense causal transformer with approximately 1.8B ViT perception moduleSource
- Context window
- 131,072 tokensSource
- Input
- Text, ImageSource
- Output
- TextSource
- Languages
- >100Source
- Knowledge cutoff
- 2026-01-04Source
Pricing
Published prices
Prices apply to the stated unit. Resolution, output length, and provider can change the cost.
Cost example
100 API requests
$0.085
100 requests with 1,000 input and 500 output tokens each calculate to $0.085. Input accounts for $0.03; output accounts for $0.055.
- Input price
- $0.3 / 1M tokensBase tier for each request
- Output price
- $1.1 / 1M tokensBase tier for each request
The calculation uses documented token prices and no cache discount. It excludes extra tools, tax, reasoning tokens, and further hidden output tokens.
Open sourceHead-to-head comparisons
Compare this model
Each matchup compares this model with exactly one other model from the same category.
There are no published direct comparisons for this model yet.
More models
Models from the same selection
All AI models
Evidence
Sources and data date
Every statement links to its underlying documentation or leaderboard.
- Speed
Median across serving providers, High effort. Output speed after the first streaming chunk, not total response time. Retrieved September 8, 2026.
- Price
Base API prices without caching or batch discounts. Higher context tiers and other rates are listed under Costs.
- Input
Documented modalities. Retrieved September 8, 2026.
- Output
Documented modalities. Retrieved September 8, 2026.
Research date September 8, 2026. 2 source URLs checked. This documents the inspected sources, not an exhaustive inventory of every publication.
Open evidence questions and research notes (original wording)
Not found in the inspected sources
max-output-tokens. No model-specific maximum output in the checked card.
Not found in the inspected sources
api-model-id. The checked card does not publish a stable API model identifier.