AIArchiveInfo/Muse-Glimmer-30B-ExecuTorch-PTE

image-text-to-text model by AIArchiveInfo

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Authors: Meta Superintelligence Lab Model Release Date: August 2026 License: Apache 2.0 Muse Glimmer is a 30-billion-parameter causal language model with a dedicated perception encoder, distilled from Muse Spark and purpose-built for autonomous agentic tasks on consumer hardware. The model integrates multi-step reasoning, reliable tool use, multimodal understanding, and failure recovery into a single model that runs locally without requiring cloud infrastructure or network access. Why an export, rather than a per-backend port. Local runtimes usually reimplement a model by hand for each target they support. That holds up for a plain text transformer; it does not hold up for a novel architecture with multimodal input and block-diffusion speculative decoding, where every backend would need its own rewrite of all three. ExecuTorch inverts that: the model and its decoding strategy are written once in PyTorch, and torch.export lowers the whole graph ahead of time — Triton on CUDA, MLX-native and…

AIArchiveInfo/Muse-Glimmer-30B-ExecuTorch-PTE on Hugging Face A short preview, not the full document.

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Inside the original model card — Document outline
  1. Muse Glimmer 30B — ExecuTorch PTE
  2. ⚠️ Read this before you download
  3. What's in this repo
  4. What each directory contains
  5. Shared files at the repo root
  6. Download sizes (per directory, .pte + .ptd + posembed.bin)
  7. Pick a variant
  8. Download one variant
  9. Build the runner
  10. Serve
  11. CUDA (sm80+ptx) — both --model-path and --data-path
  12. Metal — self-contained .pte, no --data-path

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Documentation belongs to its respective authors. Reported project/model license: apache-2.0. A listing is not a grant of reuse or training rights. Confirm the document’s own terms at the source.

Model overview

AIArchiveInfo/Muse-Glimmer-30B-ExecuTorch-PTE is a image-text-to-text model repository published by AIArchiveInfo on Hugging Face. A library was not reported.

This page summarizes Hub metadata. For intended use, training data, evaluation results and limitations, consult the original model card.

Model facts

Task
image-text-to-text
Library
Not reported
Recent downloads (30 days)
0
Cumulative likes
0
Hugging Face trending score
0
Reported safetensors parameters
Not reported
Architecture
Not reported
License
apache-2.0
Access
Not gated by Hugging Face
Created
2026-09-21T06:31:54.000Z
Last modified
2026-09-21T06:31:55.000Z

Compatibility and lineage

Language coverage was not reported.

Reported base models: meta-models/Muse-Glimmer-30B

Parameter count is not a RAM/VRAM requirement. Check precision, quantization, context length and runtime compatibility in the model card; no hardware or API-cost claim is inferred here.

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Model card and usage instructions

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Source: Hugging Face Hub. Metadata observed 2026-09-21T06:36:48.800Z. Daily imports are snapshots, not real-time monitoring.

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