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Open-weight model

pig-clip

by GGUF gguf-org/pig-clip

pig-clip is an open-weight model from GGUF, released under MIT License. Its published files total 8.8 GB. It draws 3.9k downloads a month.

natively trained multipurpose clip for gk engine - low vram alternative/substitute of t5xxl, umt5xxl, etc.

Parameters—
Context—
Weights8.8 GB
Licensemit
AccessOpen weights
Monthly Downloads3.9k

Model Card

By GGUF, published under mit, revision 996a5593e1b1.

natively trained multipurpose clip for gk engine - low vram alternative/substitute of t5xxl, umt5xxl, etc. - 80-90% smaller, more efficient and cost effective (hopefully) since LLM in diffusion model basically serves as text encoder, which means its primary goal/function is delivering a prompt to the generator precisely, no talk, no deep reasoning, no long response, make it as simple as possible we stop the training when similarity reaches.95 or over 20k cycles and similarity no less than.75 simply replace --t5xxl t5xxl.gguf with --llm pigclip-nvfp4.gguf --llm-adapter pigt5adapter-f16.gguf test it with pixart test it with sd-lite test it with wan2.1 or wan2.2 test it with krea2 test it with…

Read GGUF's full model card

pig architecture gguf clip

  • natively trained multipurpose clip for gk engine
  • low vram alternative/substitute of t5xxl, umt5xxl, etc.
  • 80-90% smaller, more efficient and cost effective (hopefully)

rationale

since LLM in diffusion model basically serves as text encoder, which means its primary goal/function is delivering a prompt to the generator precisely, no talk, no deep reasoning, no long response, make it as simple as possible

limitation/cutoff

we stop the training when similarity reaches .95 or over 20k cycles and similarity no less than .75

adapter stock pig-clip delta
t5 0.7872 0.7913 +0.0040
t5 (20k) 0.7913 0.8080 +0.0167
umt5 0.7533 0.7634 +0.0100
qwen3 0.9649 0.9671 +0.0022
qwen3vl 0.9296 0.9378 +0.0082
qwen3vl 8b 0.9385 0.9431 +0.0046
qwen3vl (layerwise) 0.9475 0.9504 +0.0029
llada 0.9502 0.9651 +0.0149

how it works

simply replace --t5xxl t5xxl.gguf with --llm pig_clip-nvfp4.gguf --llm-adapter pig_t5_adapter-f16.gguf

examples

test it with pixart

ggk diffuser engine -- --diffusion-model pixart-nvfp4.gguf --vae pig_pixart_vae_fp16-f16.gguf --llm pig_clip-nvfp4.gguf --llm-adapter pig_t5_adapter-f16.gguf -p "close-up portrait of dog" --diffusion-fa -v -o out.png

test it with sd-lite

ggk diffuser engine -- --diffusion-model model.gguf --vae vae.gguf --clip_l clip_l.gguf --clip_g clip_g.gguf --llm pig_clip-nvfp4.gguf --llm-adapter pig_t5_adapter-f16.gguf -p "close-up portrait of dog" --steps 8 --cfg-scale 1 --sampling-method euler --clip-on-cpu --diffusion-fa -v -o out.png

umt5 adapter

test it with wan2.1 or wan2.2

ggk diffuser engine -- -M vid_gen --diffusion-model wan2.1_t2v_1.3b-q4_0.gguf --vae pig_wan_vae_fp32-f16.gguf --llm pig_clip-nvfp4.gguf --llm-adapter pig_umt5_adapter-f16.gguf -p "a pig moving quickly in a beautiful winter scenery nature trees sunset tracking camera" --cfg-scale 6.0 --sampling-method euler -v -n "blurry ugly bad" -W 480 -H 480 --diffusion-fa --offload-to-cpu --video-frames 14 -o out.avi

qwen3vl-layerwise adapter

test it with krea2

ggk diffuser engine -- --diffusion-model krea2_turbo-q2_k.gguf --vae pig_wan_vae_fp32-f16.gguf --llm pig_clip-nvfp4.gguf --llm-adapter pig_qwen3vl_layerwise_adapter-f16.gguf -p "a lovely pig holding a sign says Hi" --cfg-scale 1.00 --steps 8 --offload-to-cpu --diffusion-fa -v -o out.png

qwen3-4b adapter

test it with x-image

ggk diffuser engine -- --diffusion-model  x_image-nvfp4.gguf --vae pig_flux_vae_fp32-f16.gguf --llm pig_clip-nvfp4.gguf --llm-adapter pig_qwen3_4b_adapter-f16.gguf -p "cute anime style girl with pinky messy long hair blue eyes wearing a maid outfit with a long black gold leaf pattern dress and a white apron, it is a postcard held by a hand in front of a beautiful realistic city at sunset and there is cursive writing that says PIG" --cfg-scale 1.0 --steps 8 --offload-to-cpu --diffusion-fa -v -o out.png

qwen3vl-4b adapter

test it with mageflow

ggk diffuser engine -- --diffusion-model mageflow-edit-turbo-nvfp4.gguf --vae pig_mageflow_vae_fp32-f16.gguf --llm pig_clip-nvfp4.gguf --llm-adapter pig_qwen3vl_4b_adapter-f16.gguf --llm_vision mmproj-qwen3vl-4b-it-f16.gguf --ref-image sheep.png -p "a sheep in sunglasses" --cfg-scale 1.00 --steps 4 --sampling-method euler --diffusion-fa -v -o out.png

qwen3vl-8b adapter

test it with qwen-image2.1

ggk diffuser engine -- --diffusion-model qwen-image-2.1-nvfp4.gguf --vae pig_qwen_image_2.1_vae_fp32-f16.gguf --llm pig_clip-f16.gguf --llm-adapter pig_qwen3vl_8b_adapter-f16.gguf -p "an anime pig holding a sign says GGUF" -W 512 -H 512 --sampling-method euler -v -o out.png

edit image with vision clip (optional)

ggk diffuser engine -- --diffusion-model qwen-image-2.1-nvfp4.gguf --vae pig_qwen_image_2.1_vae_fp32-f16.gguf --llm pig_clip-f16.gguf --llm-adapter pig_qwen3vl_8b_adapter-f16.gguf --llm_vision mmproj-qwen3vl-8b-it-q8_0.gguf --ref-image sheep.png -p "a sheep in sunglasses" --cfg-scale 1.00 --steps 8 --sampling-method euler --diffusion-fa -v -o out.png

llada adapter

test it with llada

ggk diffuser engine -- --diffusion-model LLaDA-image-turbo-nvfp4.gguf --vae pig_flux2_vae_fp32-f16.gguf --llm pig_clip-q8_0.gguf --llm-adapter pig_llada_adapter-q8_0.gguf -p "a pig in sunglasses" --cfg-scale 1.00 --steps 4 --sampling-method euler --diffusion-fa -v -o out.png

edit image with vision clip (optional)

ggk diffuser engine -- --diffusion-model LLaDA-image-turbo-nvfp4.gguf --vae pig_flux2_vae_fp32-f16.gguf --llm pig_clip-q4_k_m.gguf --llm-adapter pig_llada_adapter-f16.gguf --llm_vision pig_llada_sigvq-q4_0.gguf --ref-image sheep.png -p "a sheep in sunglasses" --cfg-scale 1.00 --steps 4 --sampling-method euler --diffusion-fa -v -o out.png

Reference

pig engine - the new gguf compute kernels (gk)

gguf trainer - how to train your own adapter

Identity and Version

Repository
gguf-org/pig-clip
Publisher
GGUF
Task
Not stated by the source
Modality
Other
Library
Not stated by the source
Parameters
Not stated by the source
Languages
Not stated by the source
Revision
996a5593e1b1de269b47d6dea1eb8fdc443ae3f9
First published
2026-08-22
Last updated
2026-09-21

Files and Weights

38 files, 8.8 GB in total. The weights are 36 files totalling 8.8 GB in gguf.

Weights36 files · 8.8 GB
Documentation1 file · 5.9 KB
Repository1 file · 3.8 KB
Every file
FileTypeSizeSHA-256
pig_clip-int16.ggufWeights780.0 MB 16bc2499f3f8
pig_clip-int8.ggufWeights624.4 MB 3d20835afa1f
pig_clip-iq2_xxs.ggufWeights241.5 MB 9e8181ee1fdc
pig_clip-iq3_xxs.ggufWeights251.5 MB bd3fd9a0dd07
pig_clip-iq4_nl.ggufWeights335.5 MB 531c7de4a58e
pig_clip-iq4_xs.ggufWeights316.9 MB 65a23db61b8e
pig_clip-nvfp4.ggufWeights335.5 MB 7bf8f58943f2
pig_clip-q2_0.ggufWeights251.8 MB 620b704a2547
pig_clip-q2_k.ggufWeights272.4 MB 31df5d9fe8fc
pig_clip-q4_0.ggufWeights335.5 MB a4b5c38497d8
pig_clip-q4_1.ggufWeights372.8 MB 6b1253ec5496
pig_clip-q4_k_m.ggufWeights335.5 MB 62b45ce9348c
pig_clip-q5_k_m.ggufWeights410.0 MB e283aa31d521
pig_clip-q6_k.ggufWeights489.2 MB 4425aba506c6
pig_clip-q8_0.ggufWeights633.5 MB 8a42251cc5be
pig_llada_adapter-f16.ggufWeights210.3 MB 7186f396dcf5
pig_llada_adapter-q4_0.ggufWeights59.4 MB 3eebbf26dd13
pig_llada_adapter-q8_0.ggufWeights111.7 MB 029b042a1b03
pig_qwen3_4b_adapter-f16.ggufWeights113.5 MB 39ba1a2bba7d
pig_qwen3_4b_adapter-q4_0.ggufWeights32.1 MB 13ec86a804f0
pig_qwen3_4b_adapter-q8_0.ggufWeights60.4 MB 67d0dc220360
pig_qwen3vl_4b_adapter-f16.ggufWeights129.2 MB c8321fefbe1a
pig_qwen3vl_4b_adapter-q4_0.ggufWeights35.1 MB 6ddc4c00a226
pig_qwen3vl_4b_adapter-q8_0.ggufWeights66.0 MB 17955575e87a
pig_qwen3vl_8b_adapter-f16.ggufWeights145.0 MB f4e39ab6006e
pig_qwen3vl_8b_adapter-q4_0.ggufWeights38.6 MB 91ce6a75a813
pig_qwen3vl_8b_adapter-q8_0.ggufWeights72.7 MB 148bf01b2899
pig_qwen3vl_layerwise_adapter-f16.ggufWeights229.1 MB 47e5d8ecf4ef
pig_qwen3vl_layerwise_adapter-q4_0.ggufWeights64.8 MB c1cfa4e44e86
pig_qwen3vl_layerwise_adapter-q8_0.ggufWeights121.9 MB 413596887a9d
pig_t5_adapter-f16.ggufWeights278.7 MB c4d5d220ed6e
pig_t5_adapter-q8_0.ggufWeights148.2 MB efd5563c7925
pig_t5_adapter_20k-f16.ggufWeights278.7 MB b0edc2cecd51
pig_t5_adapter_20k-q8_0.ggufWeights148.2 MB 2e7e9fe24eb4
pig_umt5_adapter-f16.ggufWeights280.4 MB 0b687390e0a4
pig_umt5_adapter-q8_0.ggufWeights148.6 MB 23c2132736cd
README.mdDocumentation5.9 KB —
.gitattributesRepository3.8 KB —

License and Download

License
mit
Access
Open weights, no gate
Download size
8.8 GB
Download from GGUF

Released by GGUF through its official repository on Hugging Face. Read the license.

Memory Requirements

PrecisionWeights in memory
As published8.8 GB

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

Questions About pig-clip

Can I use pig-clip commercially?

Yes. pig-clip is released under MIT License. The MIT License is a short permissive license. It permits commercial use, modification and redistribution, provided the copyright notice and permission notice are included.