Muse Glimmer 30B
Muse Glimmer 30B (August 10, 2026) is Meta Superintelligence Labs’ first open model under the Apache 2.0 license, running without an EU exclusion clause for local deployment. The dense 29.6-billion-parameter model with an additional 1.8-billion-parameter vision encoder processes text and images in a 131,072-token context and delivers up to 233 tokens/second on a consumer GPU via DFlash Speculative Decoder — Workstation-class with genuine Desktop capability.
- Open Weights
- Desktop
- vLLM
- Text
- Vision
- Long Context
- Unusable
Sovereign Risk: LOW Meta is a US company and subject to the CLOUD Act. However, Muse Glimmer 30B is released as fully open weights under the Apache 2.0 license — Meta’s first model ever under this license. When running entirely locally on your own hardware, any dependency on US cloud infrastructure is eliminated, which is why the risk is rated as low despite US jurisdiction.
Key metrics
Score · Latency · Cost · Quality
- Total Score Silver
- 71.56
- Routine
- 43.59
- Reasoning
- 27.97
- LLM Judge Avg
- 3.51 / 5
- 100 Coverage
- Avg Task Duration
- 190.4s
- Unusable
- Token Rate
- 10.59tok/s
- Output Rate
- P95 Latency
- 392.46s
- Top 5 %
- Total Tokens
- 124900
- Output Volume
- Cost per 1K
- $0
- USD / 1K Requests
- Benchmark Cost
- $0
- Total · 124900 tok
Benchmark modules
10 modules · weighted · vs. model median & top performer
Token efficiency & latency
Consumption per module vs. model median
Token consumption per module
Performance profile
Key metrics – legend
Score
- Total Score
- Overall score derived from Routine and Reasoning scores. Basis for the fleet rank and tier assignment (Gold / Silver / Bronze).
- Routine
- Score for standard tasks: code generation, text transformation, structured outputs. Weighted by task complexity.
- Reasoning
- Score for analytical and logical tasks: multi-step problem solving, mathematical reasoning, structured argumentation.
- Rank
- Position in the fleet comparison, sorted by Total Score. Refers to the snapshot at the time of testing.
LLM Judge
- LLM Judge Ø
- Average quality rating by an independent judge model on a scale of 1–5.
- Coverage
- Share of tasks for which a judge rating is available. 100% means all responses were evaluated.
Latency & speed
- Avg. Task Duration
- Average time per task from the first to the last token of the response, measured across all benchmark tasks.
- Token Rate
- Output speed in tokens per second. Relevant for interactive applications and real-time streaming.
- P95 Latency
- 95th percentile of response times — shows outliers. Lower values mean fewer long wait times in edge cases.
Cost
- Cost per 1K
- API price per 1,000 output tokens in US dollars. Basis for cost calculation in production use.
- Benchmark Cost
- Total cost for the complete benchmark run of this model.