by Meta AI
Meta: Muse Glimmer 30B.
multimodal
closed
131K ctx
Cheapest input
$0.35/M
on Together AI
Cheapest output
$1.5/M
on Together AI
Hosted equiv.
~$0.54/hr
@ 100 tok/s on Together AI
Muse Glimmer 30B is a dense, open-weight multimodal model from Meta Superintelligence Labs, distilled from Muse Spark and optimized for autonomous agents on consumer hardware. It is suited for long-horizon...
Hosted API only
No self-host path — closed weights.
Meta: Muse Glimmer 30B's weights aren't published. Use it via the access providers below.
Where to use it
Cheapest hosted endpoints.
FAQ
Frequently asked.
How do I run Meta: Muse Glimmer 30B?
Meta: Muse Glimmer 30B is a closed-source API model. The cheapest way to access it is through the API providers listed on this page (direct API, aggregators, and hosted chat UIs).
Where can I access Meta: Muse Glimmer 30B?
Meta: Muse Glimmer 30B is available via Together AI, OpenRouter. Each access option lists its own pricing (per million tokens or hourly hosting).
How much does it cost to run Meta: Muse Glimmer 30B?
API pricing starts at $0.35/M input tokens and $1.5/M output tokens. Self-hosting cost depends on the GPU you rent — see the Run It Yourself tab.
Is Meta: Muse Glimmer 30B open-source or proprietary?
Meta: Muse Glimmer 30B is a proprietary model from Meta AI. Access is API-only — there are no public weights to download.
API pricing
Per provider
What it costs per month across providers.
Estimate your monthly bill for Meta: Muse Glimmer 30B across every host that publishes per-token pricing. Slide your token volumes; the chart + table re-rank cheapest-first.
Cheapest
$6.5
Together AI
$/M input
$0.35
per million tokens
$/M output
$1.5
per million tokens
Providers
2
with priced rows
Monthly bill
Cheapest provider on the left.
Total monthly cost — input + output tokens combined.
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Bill breakdown.
Full calculator
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Context window
How much it can remember.
131K tokens
≈ 98,304 English words
4K
32K
128K
1M
Capabilities
What it can do.
·
Vision input
·
Audio input
·
Video input
·
Function calling
·
Tool use
·
JSON mode
✓
Streaming
·
Fine-tuning