HUGGING FACE MODEL INDEX

Search and compare Hugging Face models.

2,756,622 public models indexed from the Hugging Face Hub, with independent VRAM estimates and license signals.

text-generation

Chun121/Qwen3-4B-RPG-Roleplay-V2

Chun121/Qwen3-4B-RPG-Roleplay-V2 is a text generation model indexed for deployment research. Estimated minimum GPU memory is 6 GB. It is publicly listed on Hugging Face.

↓ 18,795♡ 77
4.0B6 GB+ VRAMmit
Deployment details →
text-generation

cyankiwi/Qwen3-Coder-Next-AWQ-4bit

cyankiwi/Qwen3-Coder-Next-AWQ-4bit is a text generation model indexed for deployment research. Estimated minimum GPU memory is 8 GB. It is publicly listed on Hugging Face.

↓ 18,742♡ 31
Unknown8 GB+ VRAMapache-2.0
Deployment details →
visual-document-retrieval

vidore/colpali-v1.3

vidore/colpali-v1.3 is a visual document retrieval model indexed for deployment research. Estimated minimum GPU memory is 8 GB. It is publicly listed on Hugging Face.

↓ 18,723♡ 100
Unknown8 GB+ VRAMmit
Deployment details →
token-classification

EmergentMethods/gliner_medium_news-v2.1

EmergentMethods/gliner_medium_news-v2.1 is a token classification model indexed for deployment research. Estimated minimum GPU memory is 8 GB. It is publicly listed on Hugging Face.

↓ 18,709♡ 82
Unknown8 GB+ VRAMapache-2.0
Deployment details →
zero-shot-classification

microsoft/LLM2CLIP-Openai-L-14-336

microsoft/LLM2CLIP-Openai-L-14-336 is a zero shot classification model indexed for deployment research. Estimated minimum GPU memory is 8 GB. It is publicly listed on Hugging Face.

↓ 18,672♡ 47
Unknown8 GB+ VRAMapache-2.0
Deployment details →
object-detection

Aryn/deformable-detr-DocLayNet

Aryn/deformable-detr-DocLayNet is a object detection model indexed for deployment research. Estimated minimum GPU memory is 8 GB. It is publicly listed on Hugging Face.

↓ 18,662♡ 51
Unknown8 GB+ VRAMapache-2.0
Deployment details →
image-classification

timm/tf_efficientnet_b5.ns_jft_in1k

timm/tf_efficientnet_b5.ns_jft_in1k is a image classification model indexed for deployment research. Estimated minimum GPU memory is 8 GB. It is publicly listed on Hugging Face.

↓ 18,657♡ 1
Unknown8 GB+ VRAMapache-2.0
Deployment details →
text-generation

microsoft/Phi-3-medium-4k-instruct

microsoft/Phi-3-medium-4k-instruct is a text generation model indexed for deployment research. Estimated minimum GPU memory is 8 GB. It is publicly listed on Hugging Face.

↓ 18,641♡ 225
Unknown8 GB+ VRAMmit
Deployment details →
text-generation

zed-industries/zeta-2.1

zed-industries/zeta-2.1 is a text generation model indexed for deployment research. Estimated minimum GPU memory is 8 GB. It is publicly listed on Hugging Face.

↓ 18,585♡ 121
Unknown8 GB+ VRAMapache-2.0
Deployment details →
image-to-video

robbyant/lingbot-world-fast

robbyant/lingbot-world-fast is a image to video model indexed for deployment research. Estimated minimum GPU memory is 8 GB. It is publicly listed on Hugging Face.

↓ 18,535♡ 22
Unknown8 GB+ VRAMapache-2.0
Deployment details →
general AI

eagle618/deepseek-v3-random

eagle618/deepseek-v3-random is a AI workload model indexed for deployment research. Estimated minimum GPU memory is 8 GB. It is publicly listed on Hugging Face.

↓ 18,531♡ 0
Unknown8 GB+ VRAMapache-2.0
Deployment details →
fill-mask

sbintuitions/modernbert-ja-30m

sbintuitions/modernbert-ja-30m is a fill mask model indexed for deployment research. Estimated minimum GPU memory is 8 GB. It is publicly listed on Hugging Face.

↓ 18,499♡ 8
Unknown8 GB+ VRAMmit
Deployment details →
text-generation

openbmb/MiniCPM-SALA

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

↓ 18,490♡ 685
Unknown8 GB+ VRAMapache-2.0
Deployment details →
reinforcement-learning

mradermacher/Tifa-Deepsex-14b-CoT-GGUF

mradermacher/Tifa-Deepsex-14b-CoT-GGUF is a reinforcement learning model indexed for deployment research. Estimated minimum GPU memory is 12 GB. It is publicly listed on Hugging Face.

↓ 18,469♡ 27
14.0B12 GB+ VRAMapache-2.0
Deployment details →