coolthor/Sulphur-2-distilled-NVFP4
text-to-video model by coolthor
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From the publisher
Model card & documentation
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NVFP4 (TensorCore block-scaled FP4) weight-only quantization of the distilled Sulphur 2 model — an uncensored text-to-video + audio diffusion transformer built on LTX-2.3. The text encoder is Gemma-3-12B. This is a single-file ComfyUI checkpoint (sulphurdistilnvfp4.safetensors, 19 GB) bundled with the standalone full LTX VAE and a validated t2v API workflow. 📝 Full write-up, benchmarks & the gotchas in detail: NVFP4 video on a DGX Spark — with zero speed gain (ai-muninn.com · DGX Spark Part 34) 1. NVFP4 here is a SIZE play, not a speed play. Video diffusion is compute-bound, not bandwidth-bound. So NVFP4 does not make this faster than FP8 — on the hardware tested it runs no faster than FP8 (in fact a reproducible 6%% slower — see the speed note below), it just takes 32%% less disk and VRAM. The win is "fits a 32 GB GPU," not "generates faster." If you have the VRAM for…
Read the full model card ↗ · Preview checked 2026-10-28T23:40:45.585Z
Inside the original model card — Document outline
- Sulphur 2 (distilled) — NVFP4
- What this is
- Honest caveats (read these)
- Files
- Usage (ComfyUI)
- Validation
- Credits
- License
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Model overview
coolthor/Sulphur-2-distilled-NVFP4 is a text-to-video model repository published by coolthor on Hugging Face. The source reports the diffusers library.
This page summarizes Hub metadata. For intended use, training data, evaluation results and limitations, consult the original model card.
Model facts
- Task
- text-to-video
- Library
- diffusers
- Recent downloads (30 days)
- 3,032
- Cumulative likes
- 4
- Hugging Face trending score
- 0
- Reported safetensors parameters
- Not reported
- Architecture
- Not reported
- License
- other
- Access
- Not gated by Hugging Face
- Created
- 2026-06-01T12:23:44.000Z
- Last modified
- 2026-06-02T09:03:58.000Z
Compatibility and lineage
Language coverage was not reported.
Reported base models: SulphurAI/Sulphur-2-base
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.
Use and evaluate
Check license terms and access requirements first. Review the model card’s documented loading instructions, evaluations and safety limitations. Benchmark scores are not imported by this directory, and popularity is not an accuracy ranking.
No model weights are downloaded or executed by AltAPIs. Never enable remote model code without reviewing it.
Source and freshness
Source: Hugging Face Hub. Metadata observed 2026-09-22T06:37:20.256Z. Daily imports are snapshots, not real-time monitoring.
Popularity and source listings do not establish security, suitability, licensing rights or benchmark performance.
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