HUGGING FACE MODEL INDEX

Search and compare Hugging Face models.

2,659,847 public models indexed from the Hugging Face Hub, with independent VRAM estimates and license signals.

automatic-speech-recognition

ibm-granite/granite-speech-3.2-8b

ibm-granite/granite-speech-3.2-8b is a automatic speech recognition model indexed for deployment research. Estimated minimum GPU memory is 24 GB. It is publicly listed on Hugging Face.

↓ 48,404♡ 88
8.0B24 GB+ VRAMapache-2.0
Deployment details →
fill-mask

Synthyra/ESMplusplus_small

Synthyra/ESMplusplus_small is a fill mask model indexed for deployment research. Estimated minimum GPU memory is 8 GB. It is publicly listed on Hugging Face.

↓ 48,388♡ 18
Unknown8 GB+ VRAMmit
Deployment details →
text-generation

MaziyarPanahi/WizardLM-2-7B-GGUF

MaziyarPanahi/WizardLM-2-7B-GGUF is a text generation model indexed for deployment research. Estimated minimum GPU memory is 8 GB. It is publicly listed on Hugging Face.

↓ 48,190♡ 83
7.0B8 GB+ VRAMapache-2.0
Deployment details →
text-generation

Cactus-Compute/needle2

Cactus-Compute/needle2 is a text generation model indexed for deployment research. Estimated minimum GPU memory is 8 GB. It is publicly listed on Hugging Face.

↓ 48,155♡ 270
Unknown8 GB+ VRAMapache-2.0
Deployment details →
text-to-image

diroverflo/FLux_Klein_9B_NSFW

diroverflo/FLux_Klein_9B_NSFW is a text to image model indexed for deployment research. Estimated minimum GPU memory is 24 GB. It is publicly listed on Hugging Face.

↓ 48,055♡ 64
9.0B24 GB+ VRAMapache-2.0
Deployment details →
general AI

KittenML/kitten-tts-nano-0.8-int8

KittenML/kitten-tts-nano-0.8-int8 is a AI workload model indexed for deployment research. Estimated minimum GPU memory is 8 GB. It is publicly listed on Hugging Face.

↓ 47,969♡ 33
Unknown8 GB+ VRAMapache-2.0
Deployment details →
text-generation

lmstudio-community/Qwen3-32B-MLX-8bit

lmstudio-community/Qwen3-32B-MLX-8bit is a text generation model indexed for deployment research. Estimated minimum GPU memory is 48 GB. It is publicly listed on Hugging Face.

↓ 47,853♡ 2
32.0B48 GB+ VRAMapache-2.0
Deployment details →
image-text-to-text

neroued/Qwen3.8-27B-nvfp4-NInfer

neroued/Qwen3.8-27B-nvfp4-NInfer is a image text to text model indexed for deployment research. Estimated minimum GPU memory is 64 GB. It is publicly listed on Hugging Face.

↓ 47,784♡ 45
27.0B64 GB+ VRAMapache-2.0
Deployment details →
sentence-similarity

sentence-transformers/gtr-t5-large

sentence-transformers/gtr-t5-large is a sentence similarity model indexed for deployment research. Estimated minimum GPU memory is 4 GB. It is publicly listed on Hugging Face.

↓ 47,667♡ 40
Unknown4 GB+ VRAMapache-2.0
Deployment details →
zero-shot-image-classification

StanfordAIMI/CheXficient

StanfordAIMI/CheXficient is a zero shot image classification model indexed for deployment research. Estimated minimum GPU memory is 8 GB. It is publicly listed on Hugging Face.

↓ 47,607♡ 3
Unknown8 GB+ VRAMmit
Deployment details →
any-to-any

ggml-org/gemma-4-12B-it-GGUF

ggml-org/gemma-4-12B-it-GGUF is a any to any model indexed for deployment research. Estimated minimum GPU memory is 12 GB. It is publicly listed on Hugging Face.

↓ 47,530♡ 85
12.0B12 GB+ VRAMapache-2.0
Deployment details →
text-generation

bloomer010/Ling-3.0-flash-GGUF

bloomer010/Ling-3.0-flash-GGUF is a text generation model indexed for deployment research. Estimated minimum GPU memory is 8 GB. It is publicly listed on Hugging Face.

↓ 47,209♡ 27
Unknown8 GB+ VRAMmit
Deployment details →
text-generation

ByteDance-Seed/Seed-OSS-36B-Base

ByteDance-Seed/Seed-OSS-36B-Base is a text generation model indexed for deployment research. Estimated minimum GPU memory is 80 GB. It is publicly listed on Hugging Face.

↓ 47,129♡ 68
36.0B80 GB+ VRAMapache-2.0
Deployment details →
token-classification

saattrupdan/nbailab-base-ner-scandi

saattrupdan/nbailab-base-ner-scandi is a token classification model indexed for deployment research. Estimated minimum GPU memory is 8 GB. It is publicly listed on Hugging Face.

↓ 47,064♡ 25
Unknown8 GB+ VRAMmit
Deployment details →