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About

Muse Glimmer is a 30-billion-parameter open-weights model from Meta Superintelligence Labs, optimized for always-on local agent workflows. Small enough to run on a Mac or PC with a single consumer GPU, it is designed for local agents, function calling, coding, and LLM-as-a-judge evaluation without depending on cloud infrastructure or network access. The model combines long-horizon execution, precise tool calling, multimodal understanding, long-context memory, and instruction following. It can complete end-to-end agentic tasks, sustain multi-step reasoning across extended workflows, recover from failed or unexpected tool calls, and accept interleaved text and images through a dedicated perception encoder for interpreting screenshots, charts, and documents. Muse Glimmer works with OpenClaw and other agentic orchestration patterns, supports controllable reasoning effort, and is trained on data from more than 100 languages.

About

Overmind is a model training and deployment platform for teams building AI agents. It ingests production traces through OpenTelemetry and creates datasets from trace data, file uploads, and connectors for Langfuse, LangSmith, Braintrust, and Galileo. Teams can inspect agent context and runtime behavior, prepare and score datasets, evaluate prompts and models against their own examples, and optimize agent behavior through scored changes. The platform supports LoRA and full fine-tuning of open-weight models, benchmarking with configured evaluators, and deployment through an OpenAI-compatible endpoint; trained weights can also be downloaded. Users can work in the hosted console or run the platform on their own infrastructure with Docker Compose. It is designed for AI engineering and product teams operating agents in production that want to test, improve, or specialize models using their own data.

Platforms Supported

Windows Not Supported
Mac Not Supported
Linux Not Supported
Cloud Supported
On-Premises Not Supported
iPhone Not Supported
iPad Not Supported
Android Not Supported
Chromebook Not Supported

Platforms Supported

Windows Not Supported
Mac Not Supported
Linux Not Supported
Cloud Supported
On-Premises Supported
iPhone Not Supported
iPad Not Supported
Android Not Supported
Chromebook Not Supported

Audience

Developers building private, always-on AI agents that need strong reasoning, tool use, and multimodal capabilities on local hardware

Audience

AI product teams and ML engineers running LLM agents in production who want a cheaper specialised model they own

Support

Phone Support Not Supported
24/7 Live Support Not Supported
Online Supported

Support

Phone Support Not Supported
24/7 Live Support Not Supported
Online Not Supported

API

Offers API Supported

API

Offers API Supported

Screenshots and Videos

Screenshots and Videos

Pricing

Free
Free Version Not Supported
Free Trial Supported

Pricing

Free
Free plan: $0/month, with fair-use OTLP ingest, up to 10 optimization runs, 5 evaluation runs, 2 training jobs, and 2 deployment jobs per month, plus 5 projects and a $40 one-time credit. Pro: $120/month with higher limits, unlimited projects, optimization runs, evaluation runs, training jobs, and deployment jobs. Enterprise pricing is custom.
Free Version Supported
Free Trial Not Supported

Reviews/Ratings

Overall 5.0 / 5

Reviews/Ratings

Overall 0.0 / 5
ease 0.0 / 5
features 0.0 / 5
design 0.0 / 5
support 0.0 / 5

This software hasn't been reviewed yet. Be the first to provide a review:

Review this Software

Pros & Cons from Real Users

Pros

  • Muse Glimmer is exciting because it brings serious AI capability closer to the device. An open-weight model that can run on a laptop or desktop is a big deal for developers, builders, and AI power users who want more control. I like that it is focused on agentic tasks, not just basic chat. If it can handle reasoning, coding help, workflow automation, and local experimentation well, it could be really useful for private projects and always-on agents. The open-weight angle is the biggest win. Being able to download, modify, and run the model locally makes Muse Glimmer feel much more flexible than a closed API-only model.

Cons

  • I would still want to test it hard before trusting it for serious work. Smaller local models can be impressive, but they still need to prove themselves on coding, tool use, long tasks, and messy real-world prompts. Running locally also means the experience depends on your hardware. Even if it works on consumer devices, performance, speed, and setup may vary a lot.

Training

Documentation Supported
Webinars Not Supported
Live Online Not Supported
In Person Not Supported

Training

Documentation Not Supported
Webinars Not Supported
Live Online Not Supported
In Person Not Supported

Company Information

Meta
Founded: 2004
United States
meta.ai/

Company Information

Overmind
Founded: 2025
United Kingdom
www.overmindlab.ai

Alternatives

Grok 4.6

Grok 4.6

SpaceXAI

Alternatives

No Alternatives

Categories

Categories

AI Fine-Tuning Supported

Integrations

Braintrust Not Supported
Claude Code Not Supported
Cursor Not Supported
ExecuTorch Supported
Galileo Not Supported
Hermes Agent Supported
Hugging Face Supported
LM Studio Supported
LangSmith Not Supported
Langfuse Not Supported
Meta AI Supported
Model Context Protocol (MCP) Not Supported
Muse Code Supported
Ollama Supported
OpenAI Codex Not Supported
OpenClaw Supported
OpenCode Supported
Unsloth Supported

Integrations

Braintrust Supported
Claude Code Supported
Cursor Supported
ExecuTorch Not Supported
Galileo Supported
Hermes Agent Not Supported
Hugging Face Not Supported
LM Studio Not Supported
LangSmith Supported
Langfuse Supported
Meta AI Not Supported
Model Context Protocol (MCP) Supported
Muse Code Not Supported
Ollama Not Supported
OpenAI Codex Supported
OpenClaw Not Supported
OpenCode Not Supported
Unsloth Not Supported
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