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Muse Glimmer 30B

Meta 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...

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data quality56

Updated 5 h ago · first seen 11 Sept 2026

model_01M294AJ5VTF5XBGJHX7C7ADBR

Overview

Identity

Identity block not returned by the API for this entity.

Openness

Openness not classified yet — no sourced evidence to place this model in the ontology.

Key facts

Release date

Source:OpenRouter public model & pricing listingT2observed 12 h agomedium

Openrouter id

Source:OpenRouter public model & pricing listingT2observed 12 h agomedium

Architecture

Hugging Face repo

Source:OpenRouter public model & pricing listingT2observed 12 h agomedium

Capabilities

Modalities

Modalities
imagetext
Input
imagetext
Output
text

Capabilities

  • Tool calling

    Yes

    OpenRouter public model & pricing listing · T2

  • Structured output

    Yes

    OpenRouter public model & pricing listing · T2

  • Reasoning

    Yes

    OpenRouter public model & pricing listing · T2

  • Vision

    Yes

    OpenRouter public model & pricing listing · T2

  • Audio

    Unavailable

  • Fine-tuning available

    Unavailable

Context window

Source:OpenRouter public model & pricing listingT2observed 12 h agomedium

Max output

Source:OpenRouter public model & pricing listingT2observed 12 h agomedium

Benchmarks7

Compare with another model →

Comparable same task and conditions · Partially comparable same task, conditions differ (effort, temperature, judge) · Not comparable different variant or metric

No benchmark results recorded

Results appear when a tier 1–3 source publishes them; we never copy scores without a source.

Providers & Pricing4

All offers in the price terminal →
Current prices per 1M tokens
ProviderInput / 1MOutput / 1MCached inBatch in / outContextObservedSource
OpenRoutermeta/muse-glimmer-30b:batch$0.175$0.75$0.02—131.1K3 h agoopenrouter.aiT2
OpenRoutermeta/muse-glimmer-30b$0.30$1.1$0.04—131.1K3 h agoopenrouter.aiT2
Fireworks AIfireworks/muse-glimmer-30b$0.35$1.5$0.04——5 h agoapp.fireworks.aiT1
Together AImuse-glimmer$0.35$1.5$0.04$0.35 / $1.5—10 h agotogether.aiT1

USD per 1M tokens as published by each provider (USD). Rows are append-only: every change is kept in the history below.

Price history

Step lines per provider; amber markers are recorded changes. Click a marker or a row for the evidence behind that price.

Output price · USD / 1M tokens 3 providers

Output price history of Muse Glimmer 30B$0$0.50$1$1.5$2Sept 26Sept 26Sept 26Fireworks AI: first observed → $1.5 · 11 Sept 2026OpenRouter: first observed → $1.1 · 11 Sept 2026OpenRouter: $1.1 → $0.75 · 11 Sept 2026Together AI: first observed → $1.5 · 11 Sept 2026
  • Fireworks AI
  • OpenRouter
  • Together AI
  • Together AIfirst observed $1.511 Sept 2026
  • OpenRouter$1.1 → $0.7511 Sept 2026
  • OpenRouterfirst observed $1.111 Sept 2026
  • Fireworks AIfirst observed $1.511 Sept 2026

Input price · USD / 1M tokens 3 providers

Input price history of Muse Glimmer 30B$0$0.10$0.20$0.30$0.40$0.50Sept 26Sept 26Sept 26Fireworks AI: first observed → $0.35 · 11 Sept 2026OpenRouter: first observed → $0.30 · 11 Sept 2026OpenRouter: $0.30 → $0.175 · 11 Sept 2026Together AI: first observed → $0.35 · 11 Sept 2026
  • Fireworks AI
  • OpenRouter
  • Together AI
  • Together AIfirst observed $0.3511 Sept 2026
  • OpenRouter$0.30 → $0.17511 Sept 2026
  • OpenRouterfirst observed $0.3011 Sept 2026
  • Fireworks AIfirst observed $0.3511 Sept 2026

Timeline12

Full timeline →

Change history14

Temporal, append-only claims: a new observation closes the previous claim instead of overwriting it. Rewind the record with the as-of picker.

Viewing AI Atlas as of 12 Aug 2026 — attributes exactly as the atlas knew them on that day; later corrections are not shown.

Back to today →

Muse Glimmer 30B was not yet in AI Atlas on 12 Aug 2026

First seen 11 Sept 2026. Nothing is inferred backwards: no attribute is shown for dates before the first observation.
14 claims · 14 properties

Release daterelease_date1

Claim history for Release date
ValueValid from → toStatusSourceConfidenceExtractor
9 Aug 2026 → currentcurrentOpenRouter public model & pricing listingT2mediumdeterministic

Context windowcontext_length1

Claim history for Context window
ValueValid from → toStatusSourceConfidenceExtractor
131.1K tokens → currentcurrentOpenRouter public model & pricing listingT2mediumdeterministic

Max outputmax_output_tokens1

Claim history for Max output
ValueValid from → toStatusSourceConfidenceExtractor
118K tokens → currentcurrentOpenRouter public model & pricing listingT2mediumdeterministic

Modalitiesmodalities1

Claim history for Modalities
ValueValid from → toStatusSourceConfidenceExtractor
image, text → currentcurrentOpenRouter public model & pricing listingT2mediumdeterministic

Input modalitiesmodalities_input1

Claim history for Input modalities
ValueValid from → toStatusSourceConfidenceExtractor
image, text → currentcurrentOpenRouter public model & pricing listingT2mediumdeterministic

Output modalitiesmodalities_output1

Claim history for Output modalities
ValueValid from → toStatusSourceConfidenceExtractor
text → currentcurrentOpenRouter public model & pricing listingT2mediumdeterministic

Hugging Face repohf_repo1

Claim history for Hugging Face repo
ValueValid from → toStatusSourceConfidenceExtractor
meta-models/Muse-Glimmer-30B → currentcurrentOpenRouter public model & pricing listingT2mediumdeterministic

Descriptiondescription1

Claim history for Description
ValueValid from → toStatusSourceConfidenceExtractor
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... → currentcurrentOpenRouter public model & pricing listingT2mediumdeterministic

Openrouter idopenrouter_id1

Claim history for Openrouter id
ValueValid from → toStatusSourceConfidenceExtractor
meta/muse-glimmer-30b → currentcurrentOpenRouter public model & pricing listingT2mediumdeterministic

Reasoningreasoning1

Claim history for Reasoning
ValueValid from → toStatusSourceConfidenceExtractor
Yes → currentcurrentOpenRouter public model & pricing listingT2mediumdeterministic

Structured outputstructured_output1

Claim history for Structured output
ValueValid from → toStatusSourceConfidenceExtractor
Yes → currentcurrentOpenRouter public model & pricing listingT2mediumdeterministic

Supported parameterssupported_parameters1

Claim history for Supported parameters
ValueValid from → toStatusSourceConfidenceExtractor
frequency_penalty, include_reasoning, logit_bias, logprobs, max_tokens, min_p, presence_penalty, reasoning, reasoning_effort, repetition_penalty, response_format, seed, stop, structured_outputs, temperature, tool_choice, tools, top_k, top_logprobs, top_p → currentcurrentOpenRouter public model & pricing listingT2mediumdeterministic

Tool callingtool_calling1

Claim history for Tool calling
ValueValid from → toStatusSourceConfidenceExtractor
Yes → currentcurrentOpenRouter public model & pricing listingT2mediumdeterministic

Visionvision1

Claim history for Vision
ValueValid from → toStatusSourceConfidenceExtractor
Yes → currentcurrentOpenRouter public model & pricing listingT2mediumdeterministic

Claims are temporal and append-only: a new observation closes the previous claim (valid_to) instead of overwriting it. Conflicting claims from different sources are kept side by side and flagged — never averaged. Methodology →

Provenance

Attributed facts

17

Source tiers

T217

Freshest observation

5 h ago

Conflicts

None

Source documents 4

Source documents
SourceDocumentTypeTierLast observedSnapshots
Fireworks AI — pricingdocs.fireworks.ai/serverless/pricing.md pricingT1· Official5 h ago2
Together AI — pricingtogether.ai/pricing pricingT1· Official5 h ago1
OpenRouter public model & pricing listingopenrouter.ai/api/v1/models catalogueT2· Quality secondary3 h ago7
Artificial Analysisartificialanalysis.ai/leaderboards/models leaderboardT2· Quality secondary10 h ago1

Tier 1 = official/primary, 2 = quality secondary, 3 = community, 4 = unverified. Every snapshot is archived; see all sources and the methodology.

Data quality (56/100) measures how well AI Atlas knows this entity — completeness, primary-source ratio, freshness, conflicts — never how good the model is. Methodology →