Run Local Agentic AI Workflows with Meta’s Muse Glimmer on NVIDIA

Summary

Meta has released Muse Glimmer, a 30B open-weight dense model with a 120K+ context window aimed at local agentic AI workflows. The model uses a dense architecture that activates every parameter per token, avoiding routing overhead and targeting reliable instruction following, long-context coherence, and predictable latency for multi-step agent tasks. On NVIDIA Blackwell Ultra hardware, Muse Glimmer reports over 20K tokens/sec/GPU at BF16/NVF4 precision, with the full model fitting in a single GPU's VRAM. Deployment options span NVIDIA GeForce RTX 5090, DGX Spark, DGX Station, and Jetson edge devices, supported by vLLM, SGLang, and NVIDIA NIM containers. Fine-tuning is available through NVIDIA NeMo AutoModel for SFT and LoRA, with NeMo RL for reinforcement learning, and the NemoClaw harness enables long-running assistants in a sandboxed environment.

Takeaways

1. 1

   Muse Glimmer is a 30B dense open-weight model with a 120K+ context window, designed for agentic workloads rather than chat, and avoids MoE routing overhead by activating every parameter per token.

2. 2

   On NVIDIA Blackwell Ultra, the model delivers over 20K tokens/sec/GPU at BF16/NVF4 precision and fits entirely in a single GPU's VRAM, enabling local inference without sharding or CPU offloading.

3. 3

   Deployment spans GeForce RTX 5090, DGX Spark, DGX Station, and Jetson edge devices using vLLM, SGLang, or NVIDIA NIM containers, with fine-tuning support via NeMo AutoModel (SFT and LoRA) and NeMo RL, plus the NemoClaw harness for long-running assistants.