SAVRN
Search Contact SAVRN

Open-weight model · Text to video

Sulphur-2-base-GGUF

by Jay Abiray/Sulphur-2-base-GGUF

This repository contains GGUF format model files for SulphurAI's Sulphur-2-base. The following quantization tiers are provided to accommodate different hardware capabilities and VRAM constraints.

Parameters
Context
Weights191.0 GB
License
AccessOpen weights
Monthly Downloads95.9k

Model Card

This repository contains GGUF format model files for SulphurAI's Sulphur-2-base. The following quantization tiers are provided to accommodate different hardware capabilities and VRAM constraints.

Excerpt from the card by Jay.

Identity and Version

Repository
Abiray/Sulphur-2-base-GGUF
Publisher
Jay
Task
Text to video
Modality
Video
Library
gguf
Parameters
Not stated by the source
Languages
Not stated by the source
Revision
2f3c86a0099a35e2afe8b9f6e6f255900d4fd67b
First published
2026-05-10
Last updated
2026-05-30

Files and Weights

13 files, 191.0 GB in total. The weights are 11 files totalling 191.0 GB in gguf.

Weights11 files · 191.0 GB
Documentation1 file · 1.9 KB
Repository1 file · 2.2 KB
Every file
FileTypeSizeSHA-256
sulphur_dev-Q3_K_M.ggufWeights11.1 GB 18b7ffd9ffdc
sulphur_dev-Q3_K_S.ggufWeights10.3 GB 15fd9504c8d5
sulphur_dev-Q4_0.ggufWeights13.0 GB e49d0cb53ae5
sulphur_dev-Q4_K_M.ggufWeights14.3 GB b1cb48491adc
sulphur_dev-Q4_K_S.ggufWeights13.2 GB 58da6213181d
sulphur_dev-Q5_0.ggufWeights15.3 GB 4395136317f1
sulphur_dev-Q5_K_M.ggufWeights16.1 GB 872dc44e4cb5
sulphur_dev-Q5_K_S.ggufWeights15.0 GB d89f029e45e8
sulphur_dev-Q6_K.ggufWeights17.8 GB 28a1b0babaa2
sulphur_dev-Q8_0.ggufWeights22.8 GB d2135493ce42
sulphur_dev_bf16.ggufWeights42.0 GB c055c6cf22ff
README.mdDocumentation1.9 KB
.gitattributesRepository2.2 KB

License and Download

License
Not stated by the source
Access
Open weights, no gate
Download size
191.0 GB
Download from Jay

Released by Jay through its official repository on Hugging Face.

Built From

Memory Requirements

PrecisionWeights in memory
As published191.0 GB

Weights only, from the published parameter count; the key-value cache and runtime add to this.

Similar Models

Model · Text to video

Wan2.2-T2V-A14B-GGUF

QuantStack

This GGUF file is a direct conversion of Wan-AI/Wan2.2-T2V-A14B Since this is a quantized model, all original licensing terms and usage restrictions remain in effect. Usage The model can be used with the ComfyUI custom node ComfyUI-GGUF by city96 Place model files in ComfyUI/models/unet see the GitHub readme for further installation instructions.

Open weights apache-2.0 gguf

Model · Text to video

MiniMax-H3-Turbo-Lora

Larryvrh

A LoRA for MiniMax-H3 that renders joint video + synchronized stereo audio in as few as 4 sampling steps instead of the usual ~20 — a ~5× sampling speedup — and keeps getting better as you add steps. For most work, use minimaxh3turbov4step600ema.safetensors. It's the markedly better micro-detail (faces, fingers, fine texture), and the over-sharpening / plastic look of the earlier v1 (~850) line is fully resolved. v4 introduced a static-frame enhancement — a big win for static and small-motion content. The one trade-off shows up only at 4 steps with large, fast motion, where v4 can produce motion-smear / trailing ghosting (we're actively fixing this). Two things address it: - Use 6–8 steps.…

Open weights apache-2.0 minimax-h3

Model · Text to video

MiniMax-H3-Turbo-Lora-ComfyUI

DRBAPH

This repository contains MiniMax-H3 Turbo LoRAs converted and optimized for ComfyUI: These LoRAs accelerate MiniMax-H3 video and synchronized-audio generation by reducing the required number of sampling steps. Newly added LoRA, located in the experimental/ folder: Manual recommended sigmas: 3-step 1.0, 0.961165, 0.853333, 0.0 4-step 1.0, 0.970874, 0.907249, 0.640000, 0.0 Three LoRAs extracted from VDN-H3 8 step: The main 8-step LoRA works on both FL2VA and Ref2VA. If you are running a pruned base, choose the pruned version that corresponds to your base — the pruned versions need their own matching pruned base. Three dynamically resized BF16 LoRAs are now included. Their source weights were…

Open weights apache-2.0 minimax-h3

Model · Text to video

Sulphur-2-base

Sulphur

Sulphur 2 An uncensored video generation model based on LTX 2.3 supporting both t2v and i2v natively, as well as all of the other ltx 2.3 formats. Follow us on X Join our Discord Support the next version of the project, even just a few dollars would go a long way: Kofi To get started with the model, I recommend downloading either of the dev versions, (fp8mixed or bf16) and downloading the distill lora provided. By the way, I'm aware the workflows contain sulphurfinal right now, just use the lora or use the full models, don't use both at the same time. This model contains a prompt enhancer. The easiest way to get started with the prompt enhancer is by using it on lmstudio. The way to…

Open weights diffusers

Model · Text to video

Wan2.1-VACE-1.3B-GGUF

Sam

Wan2.1 is an open-source suite of video foundation models, compatible with consumer-grade GPUs, that excels in various video generation tasks like text-to-video, image-to-video, and video editing, even supporting visual text generation. Download models using huggingface-cli: You can also download directly from this page. This model is a derivative work of the original model licensed under the Apache 2.0 License, and is therefore distributed under the terms of the same license. Thanks to Patrick Gillespie for creating the ASCII text art tool used in this project https://patorjk.com/software/taag/ Wan-AI for the Wan model https://huggingface.co/Wan-AI/Wan2.1-VACE-1.3B…

Open weights apache-2.0 diffusers

Model · Text to video

Wan2.1-T2V-1.3B-GGUF

Sam

Wan2.1 is an open-source suite of video foundation models, compatible with consumer-grade GPUs, that excels in various video generation tasks like text-to-video, image-to-video, and video editing, even supporting visual text generation. Download models using huggingface-cli: You can also download directly from this page. This model is a derivative work of the original model licensed under the Apache 2.0 License, and is therefore distributed under the terms of the same license. Thanks to Patrick Gillespie for creating the ASCII text art tool used in this project https://patorjk.com/software/taag/ Wan-AI for the Wan model https://huggingface.co/Wan-AI/Wan2.1-T2V-1.3B…

Open weights apache-2.0 diffusers