Muse Glimmer
Meta’s Apache-2.0 ~30B open multimodal agent model for on-device and single-GPU local agents.
Meta Superintelligence Labs’ Muse Glimmer — Apache-2.0 ~30B dense multimodal agent model for on-device and single-GPU local agents. Sibling to closed Muse Spark; distinct from Llama 4.
Why Muse Glimmer matters
Glimmer is Meta’s open Muse checkpoint for local agents—not Llama 4 and not closed Muse Spark. Use it when you want Apache-2.0 weights, consumer-GPU deployability, and agentic/tool loops without a Meta API. Escalate to Spark/Llama/frontier APIs when you need 1M context, hosted SLA, or harder open MoE capability.
Vision · Tool calling · Thinking · MCP · Coding
Last reviewed: 25 August 2026
When to choose Muse Glimmer
Decision guidance for architects—not a feature list.
Best for
- On-device / single-GPU personal agents
- Privacy-sensitive local coding and tool use
- Offline multimodal assistants (image+text)
- Local LLM-as-judge and eval harnesses
Avoid if
- You need frontier open MoE scale (prefer Kimi K3 / DeepSeek V4)
- You require Meta-hosted API SLAs (prefer Muse Spark)
- You want the broadest Llama Hub fine-tune ecosystem
Strengths
Qualitative snapshot for architects—not a public ranking.
- License (Apache-2.0)★★★★★
- On-device / single-GPU fit★★★★★
- Agentic mid-size quality★★★★☆
- Frontier open MoE scale★★☆☆☆
- Hosted Meta API★☆☆☆☆
Ecosystem
Built by
- Meta
Muse Glimmer is Meta Superintelligence Labs’ open on-device agent model.
Competes with
Works with
Recommended for
- Llama Models
Clarify Llama vs Muse Spark vs Muse Glimmer when evaluating Meta stacks.
- AI Agents
Designed for local agent scaffolds, tool use, and always-on personal agents.
Often paired with
- Muse Spark
Spark is the closed Meta Model API / Muse Code path; Glimmer is the Apache-2.0 local weights path.
- Llama 4
Llama remains Meta’s general open-weight family; Glimmer is the Muse-line local agent checkpoint.
How Muse Glimmer evolved
Key moments in chronological order.
- Open source
Apache-2.0 ~30B dense multimodal agent model for on-device / single-GPU use; Hugging Face meta-models/Muse-Glimmer-30B. Distinct from closed Muse Spark and from Llama 4.
- Platform
Weights + quantizations on Hugging Face
BF16 full weights, 4-bit variants for 24/32 GB GPUs, perception encoder, and DFlash drafter head published under Apache-2.0.
- Partnership
Meta points developers to llama.cpp, MLX, ExecuTorch, Ollama, LM Studio, vLLM, SGLang, and hosts like Together / Fireworks / OpenRouter as integrations land.
- Model
Muse Spark 1.2 sibling context
Closed Muse Spark 1.2 / Muse Code beta ship days earlier as the paid Meta Model API path; Glimmer is the open local counterpart.
Overview
Capabilities
- Vision: Yes
- Audio: No
- Tool calling: Yes
- Thinking: Yes
- MCP: Yes
- Coding: Yes
- Structured output: Yes
Technical specifications
- Provider
- Meta
- License
- Apache-2.0
- Context window
- 131K
- Parameters
- ~29.6B dense (+ ~1.8B vision encoder)
- Architecture
- Dense Transformer + Perception Encoder
- Release
- 2026-08
- Modalities
- Text, Image
- Vision
- Yes
- Audio
- No
- Tool calling
- Yes
- Thinking
- Yes
- MCP
- Yes
- Open weights
- Yes
- API
- No
- Pricing (input)
- Self-host / third-party hosts (no Meta API for Glimmer at launch)
- Pricing (output)
- Self-host / third-party hosts
Supported modalities
Text · Image
Context window
131K (131,072 tokens)
Pricing
Weights on Hugging Face under Apache-2.0. Hosted pricing depends on providers (Together, Fireworks, OpenRouter, etc.).
Availability
Download meta-models/Muse-Glimmer-30B (BF16 + 4-bit). Local: llama.cpp / MLX / ExecuTorch / Ollama / LM Studio as support lands. Serve with vLLM / SGLang.
Use cases
- On-device / single-GPU personal agents
- Local coding and tool-calling loops
- Privacy-sensitive multimodal assistants
- LLM-as-judge and offline eval harnesses
Strengths
- Apache-2.0 (more permissive than Llama Community License)
- Sized for one consumer GPU (24–32 GB class with quantization)
- Strong agentic mid-size results vs Gemma/Qwen peers per Meta evals
- Native image+text input for local multimodal agents
Limitations
- Not a frontier MoE — below Kimi K3 / DeepSeek V4 on hardest open tasks
- No Meta-hosted API at launch (self-host or third-party only)
- Newer ecosystem than Llama Hub fine-tunes and tooling
- 131K context class — shorter than Spark’s 1M API path
Related guides
Related benchmarks
Related research
- Introducing Muse Glimmer: An Open Agentic Model That Runs on Your Device
Original Paper
- Muse Glimmer 30B (Hugging Face)
Original Paper
Related GitHub
Related tools
Related rankings
Companies
Explore more models
- Llama 4MetaMeta’s Llama 4 family — open-weight multimodal models designed for research and commercial use under Meta’s community license.
- Muse SparkMetaMeta Superintelligence Labs’ Muse Spark 1.2 — closed multimodal reasoning model with a coding-focused upgrade, co-trained with Muse Code, for agentic tasks, long-horizon coding, computer use, and 1M-context workflows via the Meta Model API.
- DeepSeek V4DeepSeekDeepSeek’s V4 generation — deepseek-v4-pro (V4-Pro-0813 GA) and deepseek-v4-flash (Flash-0731) with 1M context, thinking effort low/high/max, native Responses API, and strong agentic coding. Experimental multimodal API: deepseek-v4-flash-vision-exp (2026-08-21).
- Kimi K3Moonshot AIMoonshot’s Kimi K3 — 2.8T MoE (104B active) open-weight multimodal agentic model with 1M context, native vision, and strong long-horizon coding. Weights on Hugging Face under the Kimi K3 License.
- Qwen3AlibabaAlibaba’s Qwen3 family spanning Qwen3.8-Max (2.4T MoE / 95B active), open Qwen3.8-27B (dense VLM, Apache-2.0), and Qwen3.8-Flash-Next (125B / 6B active multimodal MoE + 51B n-gram embeddings)—a Qwen4 architecture preview for cost-efficient agentic coding. Production Qwen3.8-Flash on QwenCloud adds 1M-default context and built-in tools atop the Flash-Next design.
- Claude FableAnthropicAnthropic’s Claude Fable 5 — the most capable widely released Claude for long-horizon agents, deep reasoning, and demanding coding workflows. Mythos 5 is the limited-access peer for Project Glasswing.