Catalog / Type

Resources

About 115 Muse resources: Meta docs, Muse Glimmer model weights and quants, independent reviews, benchmark write-ups and setup tutorials.

5 builds · page 1 of 1

research.meta.ai

research.meta.ai

Meta's engineering write-up on Muse security: isolated VMs, a separate Sentinel permission authority, credential surrogation and layered prompt-injection defenses, with bug bounties up to $300,000.

Resource · Benchmarks & research★ Pick

How Meta built safety into Muse

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pytorch.org

pytorch.org

PyTorch added end-to-end Muse Glimmer support to ExecuTorch; on an M5 Pro, DFlash speculative decoding lifts image+text decode from 21.6 to 33.0 tok/s, and it powers the Pi coding agent locally.

Resource · Local & open models★ Pick

Muse Glimmer on ExecuTorch: DFlash on Macs and NVIDIA GPUs

huggingface.co

huggingface.co

Hugging Face's launch post covers day-0 transformers, llama.cpp and vLLM support, Inference Endpoints, speculative decoding, TRL fine-tuning and agent demos for Muse Glimmer.

Resource · Local & open models★ Pick

Hugging Face: Muse Glimmer is local, agentic and open

unsloth

unsloth

Unsloth Dynamic 2.0 GGUF quants of Muse Glimmer 30B with a companion run guide and thinking toggles.

Resource · Local & open models★ Pick· ♥ 548

Unsloth Dynamic 2.0 GGUF of Muse Glimmer

datacamp.com

datacamp.com

DataCamp's Josep Ferrer ran Muse Spark 1.3 on three real coding tasks. Two used 23–32% fewer completion tokens, but a refactor used 70% more, for a net 12% cost increase.

Resource · Benchmarks & research★ Pick

Muse Spark 1.3 tutorial: testing Meta's efficiency claims

About this shelf

Resources are reference material rather than builds, and there are about 115 of them. They include Meta's own developer posts, model files on Hugging Face and write-ups from independent reviewers.

Meta's posts cover building with Muse Spark on the Model API, running Muse Glimmer on one GPU and Muse Code leaving beta. Many entries are Muse Glimmer weights and quants, including the official GGUF, Unsloth and bartowski builds, Red Hat AI's FP8 and INT4 versions, and the DFlash drafters.

Reviews and tutorials fill out the rest. eesel covers what Muse can and can't do, Lenny's Newsletter reviews the consumer agent UX, Artificial Analysis publishes its benchmark pages, and HolaClaw tests whether base M3 and M4 Macs can run Glimmer. RuntimeWire runs head-to-head evals of Muse Spark 1.1 against Claude Opus 4.8 and GLM 5.2, and even reverse-engineered the Muse Code binary. KGP Talkie compares Glimmer with Qwen and Nemotron on one RTX 5090. Third-party claims are the authors' own.

Frequently asked

+Where is the official Muse Spark API documentation?

Meta's developer docs are at dev.meta.ai, and the Build with Muse Spark guide on this shelf covers first calls and agentic patterns. The API base URL is https://api.meta.ai/v1.

+Which Muse Glimmer quant should I download?

It depends on your hardware. Meta publishes an official GGUF, Unsloth lists a 17GB 4-bit build, and there are MLX builds for Apple Silicon and FP8 or NVFP4 builds for vLLM. Compare the entries here against your memory budget.

+Is there an independent review of the Muse agent?

Yes. eesel AI's hands-on review covers the Secure VM, security model and pricing tiers, and Lenny's Newsletter reviews the consumer experience.