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Model Library
/Meta/Muse Glimmer 30B
Meta Mark

Muse Glimmer 30B

Ready
model path:accounts/fireworks/models/muse-glimmer-30b

Muse Glimmer 30B is a dense causal language model distilled from Muse Spark and purpose-built for autonomous agentic work. It combines multi-step reasoning, reliable schema-based tool calling, and failure recovery with multimodal understanding via a ~1.8B ViT-G/14 perception encoder, supporting interleaved text and image input, a 131K+ context window, and selectable reasoning strength (low through xhigh). Trained on data from over 100 languages, Muse Glimmer performs strongly for its size class on agentic benchmarks including MCP Atlas, DeepSearch QA, Gaia2 and SWE-Bench Pro, and is released under Apache 2.0.

Muse Glimmer 30B API Features

Fine-tuning

Docs

Muse Glimmer 30B can be customized with your data to improve responses. Fireworks uses LoRA to efficiently train and deploy your personalized model

On-demand Deployment

Docs

On-demand deployments allow you to use Muse Glimmer 30B on dedicated GPUs with Fireworks' high-performance serving stack with high reliability and no rate limits.

Muse Glimmer 30B FAQs

Is Muse Glimmer 30B being deprecated on Fireworks?

Only on serverless, starting on September 25, 2026. On-demand deployment will continue to be available. Migrate serverless workloads to Nemotron Lightning 3.5 30B A3B.

Metadata

State
Ready
Created on
8/10/2026
Kind
Base model
Provider
Meta

Specification

Calibrated
No
Mixture-of-Experts
No
Parameters
29.7B

Supported Functionality

Fine-tuning
Supported
Serverless
Not supported
Context Length
131k tokens
Function Calling
Supported
Embeddings
Not supported
Rerankers
Not supported
Support image input
Supported