HUGGING FACE MODEL INDEXSearch and compare Hugging Face models.
272,508 public models indexed from the Hugging Face Hub, with independent VRAM estimates and license signals.
image-text-to-text
DavidAU/Qwen3.5-9B-Cold-Fusion-GAIN-v1.0-Uncensored-Heretic-NEO-MAX-Imatrix-GGUF is a image text to text model indexed for deployment research. Estimated minimum GPU memory is 8 GB. It is publicly listed on Hugging Face.
↓ 37,323♡ 24
9.0B8 GB+ VRAMapache-2.0
Deployment details →
general AI
realrebelai/KREA-2_GGUFs is a AI workload model indexed for deployment research. Estimated minimum GPU memory is 8 GB. It is publicly listed on Hugging Face.
↓ 37,174♡ 53
Unknown8 GB+ VRAMother
Deployment details →
image-text-to-text
Jackrong/Qwen3.5-27B-Claude-4.6-Opus-Reasoning-Distilled-GGUF is a image text to text model indexed for deployment research. Estimated minimum GPU memory is 24 GB. It is publicly listed on Hugging Face.
↓ 37,134♡ 679
27.0B24 GB+ VRAMapache-2.0
Deployment details →
text-classification
soleimanian/financial-roberta-large-sentiment is a text classification model indexed for deployment research. Estimated minimum GPU memory is 8 GB. It is publicly listed on Hugging Face.
↓ 37,049♡ 58
Unknown8 GB+ VRAMapache-2.0
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general AI
RubixYT/Zeptonic_1.1 is a AI workload model indexed for deployment research. Estimated minimum GPU memory is 8 GB. It is publicly listed on Hugging Face.
↓ 37,012♡ 1
Unknown8 GB+ VRAMLicense unknown
Deployment details →
text-to-image
LoliRimuru/moeFussion is a text to image model indexed for deployment research. Estimated minimum GPU memory is 12 GB. It is publicly listed on Hugging Face.
↓ 36,850♡ 295
Unknown12 GB+ VRAMcreativeml-openrail-m
Deployment details →
image-text-to-text
unsloth/gemma-4-26B-A4B-it 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.
↓ 36,837♡ 28
26.0B64 GB+ VRAMapache-2.0
Deployment details →
general AI
mradermacher/Qwen3.8-27B-heretic-ara-GGUF is a AI workload model indexed for deployment research. Estimated minimum GPU memory is 24 GB. It is publicly listed on Hugging Face.
↓ 36,784♡ 10
27.0B24 GB+ VRAMapache-2.0
Deployment details →
general AI
mradermacher/Qwen3.8-27B-heretic-ara-i1-GGUF is a AI workload model indexed for deployment research. Estimated minimum GPU memory is 24 GB. It is publicly listed on Hugging Face.
↓ 36,693♡ 21
27.0B24 GB+ VRAMapache-2.0
Deployment details →
text-generation
kingjones777/Qwen3.8-Flash-Next-Uncensored-ROCmFP4-FAST-GGUF is a text generation model indexed for deployment research. Estimated minimum GPU memory is 8 GB. It is publicly listed on Hugging Face.
↓ 36,384♡ 3
Unknown8 GB+ VRAMother
Deployment details →
image-text-to-text
q-future/Q-ReAlign-Lite-4B is a image text to text model indexed for deployment research. Estimated minimum GPU memory is 12 GB. It is publicly listed on Hugging Face.
↓ 36,300♡ 2
4.0B12 GB+ VRAMapache-2.0
Deployment details →
general AI
unsloth/DeepSeek-V4-Flash-GGUF is a AI workload model indexed for deployment research. Estimated minimum GPU memory is 8 GB. It is publicly listed on Hugging Face.
↓ 36,248♡ 249
Unknown8 GB+ VRAMmit
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general AI
lmstudio-community/Laguna-S-2.1-GGUF is a AI workload model indexed for deployment research. Estimated minimum GPU memory is 8 GB. It is publicly listed on Hugging Face.
↓ 36,214♡ 2
Unknown8 GB+ VRAMopenmdw-1.1
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text-generation
openbmb/MiniCPM5-1B-GGUF is a text generation model indexed for deployment research. Estimated minimum GPU memory is 4 GB. It is publicly listed on Hugging Face.
↓ 36,206♡ 248
1.0B4 GB+ VRAMapache-2.0
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text-generation
neuralcrew/neutrino-instruct is a text generation model indexed for deployment research. Estimated minimum GPU memory is 8 GB. It is publicly listed on Hugging Face.
↓ 36,200♡ 7
Unknown8 GB+ VRAMapache-2.0
Deployment details →
general AI
cyankiwi/Devstral-Small-2-24B-Instruct-2512-AWQ-4bit is a AI workload model indexed for deployment research. Estimated minimum GPU memory is 24 GB. It is publicly listed on Hugging Face.
↓ 36,182♡ 14
24.0B24 GB+ VRAMapache-2.0
Deployment details →
image-text-to-text
LibertAIDAI/GLM-5.3-Flash-NVFP4 is a image text to text model indexed for deployment research. Estimated minimum GPU memory is 8 GB. It is publicly listed on Hugging Face.
↓ 36,081♡ 61
Unknown8 GB+ VRAMmit
Deployment details →
tabular-classification
google/tabfm-1.0.0-pytorch is a tabular classification model indexed for deployment research. Estimated minimum GPU memory is 8 GB. It is publicly listed on Hugging Face.
↓ 35,919♡ 465
Unknown8 GB+ VRAMother
Deployment details →
general AI
optimum-intel-internal-testing/tiny-random-ltx2 is a AI workload model indexed for deployment research. Estimated minimum GPU memory is 8 GB. It is publicly listed on Hugging Face.
↓ 35,866♡ 0
Unknown8 GB+ VRAMLicense unknown
Deployment details →
image-text-to-text
llmfan46/Qwen3.8-27B-Ultra-Uncensored-Heretic-Native-MTP-Preserved-GGUF is a image text to text model indexed for deployment research. Estimated minimum GPU memory is 24 GB. It is publicly listed on Hugging Face.
↓ 35,776♡ 19
27.0B24 GB+ VRAMapache-2.0
Deployment details →
any-to-any
unsloth/gemma-4-E2B-it-qat-mobile-GGUF is a any to any model indexed for deployment research. Estimated minimum GPU memory is 8 GB. It is publicly listed on Hugging Face.
↓ 35,297♡ 41
Unknown8 GB+ VRAMapache-2.0
Deployment details →
text-generation
kingjones777/Qwen3.8-27B-ROCmFP4-STRIX-MTP-GGUF is a text generation model indexed for deployment research. Estimated minimum GPU memory is 24 GB. It is publicly listed on Hugging Face.
↓ 35,207♡ 34
27.0B24 GB+ VRAMapache-2.0
Deployment details →
text-generation
hotdogs/Qwen3.8-27B-abliterated-MTP-GGUF is a text generation model indexed for deployment research. Estimated minimum GPU memory is 24 GB. It is publicly listed on Hugging Face.
↓ 35,096♡ 17
27.0B24 GB+ VRAMapache-2.0
Deployment details →
image-to-image
mayocream/RORem-mixed-GGUF is a image to image model indexed for deployment research. Estimated minimum GPU memory is 12 GB. It is publicly listed on Hugging Face.
↓ 34,986♡ 5
Unknown12 GB+ VRAMopenrail++
Deployment details →