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Winnougan/Sulphur-2-base-INT8
Sulphur-2-base-INT8 is a machine learning model from Winnougan. Use it for the machine learning task on the model card, and read the license before you ship it in a product. The card lists the license as apache-2.0.
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Updated Jun 29, 2026
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From the Hugging Face model README

INT8 row-wise quantized versions of Sulphur 2, an uncensored video generation model based on LTX 2.3, supporting both T2V and I2V natively along with all other LTX 2.3 formats.
These are community quantizations of the original Sulphur 2 release — full credit to the original authors. This repo provides faster, smaller INT8 variants for users running on lower-VRAM GPUs (tested on an 24GB on a RTX 4090).
All credit for the base model, training, and architecture goes to the original Sulphur 2 authors. This repo only provides INT8 quantized derivatives for faster local inference.
| File | Source | Quantization |
|---|---|---|
sulphur_dev_int8mixed_tensorwise.safetensors | Dev (bf16) | INT8, tensor-wise, LTX2 layer filtering |
sulphur_distil_int8mixed_tensorwise.safetensors | Distilled (bf16) | INT8, tensor-wise, LTX2 layer filtering |
Both were converted using convert_to_quant with the --ltxv2 model filter, which keeps sensitive layers (VAE, vocoder, embedding/connector blocks, and select transformer blocks) in their original precision while quantizing the rest of the transformer to INT8.
--ltxv2 filter excludes the layers most sensitive to quantization lossFollow the same setup as the original Sulphur 2 release:
Sulphur 2 ships with a prompt enhancer. The easiest way to run it is through LM Studio:
Sulphur, then a subfolder inside it named promptenhancer.There's no system prompt required — just send the text (and optionally an image) you'd like enhanced.