Unsloth AI
@UnslothAI
You can now fine-tune Meta Muse Glimmer 30B for free! 🔥 Our free notebook also supports GRPO RL training. Unsloth trains Muse Glimmer 1.5× faster with 50% less VRAM vs FA2 setups. Train locally with 24GB VRAM. Guide: unsloth.ai/docs/models/mu… Notebooks: unsloth.ai/docs/models/mu…
X post · Local & open models★ Pick· ♥ 631
Sumanth
@Sumanth_077
Run and fine-tune Meta's Muse Glimmer locally! Meta released Muse Glimmer, a 30B dense vision model designed for local agentic and coding workflows. The first open model from Meta Superintelligence Labs, released under Apache 2.0. The model runs locally at different memory
X post · Local & open models· ♥ 26
merve
@mervenoyann
I shipped a fine-tuning tutorial for Muse Glimmer 30B on AI2's MolmoWeb dataset with TRL github.com/merveenoyan/sm… > but merve, this model is sota on ScreenSpot-Pro? yes, but it doesn't work well with ambiguous prompts of MolmoWeb that are close to how you interact with computer,
X post · Local & open models· ♥ 109
Resource · Local & open models· ♥ 6
DFlash2 drafter for Muse Glimmer 30B fine-tuned on long-horizon, on-policy software-engineering traces to speed up coding workloads.
Resource · Local & open models· ♥ 1
Muse Glimmer 30B fine-tuned on agentic coding traces and chat distilled from Claude Fable 5, merged bf16 and drop-in for the base.
Resource · Local & open models· ♥ 3
Tested SGLang and vLLM launch recipes for an NVFP4 export of a Hermes-agentic fine-tune of Muse-Glimmer-30B on NVIDIA DGX Spark (GB10).
GitHub · Local & open models
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A Muse Glimmer fine-tune that writes, tunes and translates detection rules (Sigma to KQL and SPL, YARA, Wazuh) and runs 4-bit on a single 24 GB card.
Resource · Local & open models
merve
@mervenoyann
Meta released Muse Glimmer 30B: multimodal model for your Claw/Pi setups 🔥 we tested and fine-tuned the model for you, and shipped day-0 support in transformers and llama.cpp, including DFlash for 2-4x speed-ups 🥵 read our blog huggingface.co/blog/muse-glim…
X post · Local & open models· ♥ 398
NVIDIA's technical blog reports Muse Glimmer serving over 20K tokens/sec on a single Blackwell Ultra GPU and covers RTX 5090, DGX Spark, DGX Station and Jetson deployments.
Resource · Local & open models
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
Your product
Sponsored
Put your logo, a line of copy and an image right here, between the builds Muse developers come to read. Same size as a post.
Shown every 12 builds · on every catalog page
A DPO fine-tune of Muse Glimmer focused on prose quality and humanlike characters, trained on roughly one-third writing and two-thirds roleplay data.
Resource · Local & open models· ♥ 2
A static Space showing a Hermes-agentic fine-tune of Muse Glimmer 30B proposing one or two tool calls or answering directly; the model card reports 16/20 on a simulated loop gate.
Site · Local & open models
Resource · Local & open models· ♥ 14
sequelbox's Tachibana-Agent fine-tune of Muse Glimmer 30B, part of a series also released for Gemma 4 12B and Qwen3.6 27B.
Resource · Local & open models· ♥ 4
Fine-tune of Muse Glimmer 30B for Hermes Agent and agentic tool work that teaches the model to call one or two tools and stop.
Resource · Local & open models· ♥ 2
A deliberately overengineered parody that 'gives you the Zuck', with a deterministic Oracle edition, a prompted Muse Glimmer edition and an MLX QLoRA fine-tune of Muse Glimmer 30B for Apple Silicon.
GitHub · Content & creative
Sediment's fine-tune of Muse Glimmer 30B that answers factual questions when confident and says "I don't know" otherwise, calibrated for the AA-Omniscience setting.
Resource · Local & open models· ♥ 1
A project that fine-tunes a DSpark speculator for Muse Glimmer 30B on on-policy coding and agentic traces to raise acceptance length on agentic workloads, evaluated with Terminal-Bench.
GitHub · Local & open models
A coding-specialised speculative-decoding drafter for Muse Glimmer 30B, fine-tuned on software-engineering traces. It raises mean acceptance length to about 6.9 versus 4.0 for the community DSpark, for about 3.8x over no speculation.
Resource · Local & open models· ♥ 1
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