1,011 models · refreshed nightly
Models that run on RTX 4070 · 16 GB
Every model in the catalog with its licence, estimated VRAM and daily-tracked downloads. Filters update the URL — share any view.
| # | Model | Params | Context | Commercial use | 30d | On RTX 4070 · 16 GB |
|---|---|---|---|---|---|---|
| 201 | wav2vec2-large-xls-r-300m-Urdu | 320 M | — | ✓ apache-2.0 | 867 K | 1.9 GB |
| 202 | Qwen2.5-1.5B | 1.5 B | 131 K | ✓ apache-2.0 | 863 K | 4.1 GB |
| 203 | mamba-130m-hf | 130 M | — | unknown | 846 K | 1.1 GB |
| 204 | Qwen2.5-1.5B-quantized.w8a8 | 1.8 B | 33 K | ✓ apache-2.0 | 839 K | 3.2 GB |
| 205 | llama-nemotron-embed-1b-v2 | 1.2 B | 131 K | other | 828 K | 3.4 GB |
| 206 | text2vec-base-chinese | 100 M | 512 | ✓ apache-2.0 | 824 K | 1.0 GB |
| 207 | gte-small | 30 M | 512 | ✓ mit | 823 K | 0.6 GB |
| 208 | PP-DocLayoutV3_safetensors | 30 M | — | ✓ apache-2.0 | 822 K | 0.7 GB |
| 209 | Llama-3.2-1B-Instruct-FP8 | 1.5 B | 131 K | ⚠ llama3.2 | 799 K | 3.0 GB |
| 210 | Kimi-K3-DSpark | 2.3 B | 1.0 M | unknown | 798 K | 5.8 GB |
| 211 | mimi | 100 M | 8 K | ✓ cc-by-4.0 | 798 K | 0.9 GB |
| 212 | Flux2-Klein-9B-True-V2 | — | — | other | 792 K | 6.8 GB |
| 213 | vntl-llama3-8b-v2-gguf | — | — | ⚠ llama3 | 774 K | 6.8 GB |
| 214 | phi-2 | 2.8 B | 2 K | ✓ mit | 771 K | 7.0 GB |
| 215 | F5-TTS | — | — | ✗ cc-by-nc-4.0 | 770 K | 5.0 GB |
| 216 | pythia-70m-deduped | 100 M | 2 K | ✓ apache-2.0 | 769 K | 0.7 GB |
| 217 | LaBSE | 470 M | 512 | ✓ apache-2.0 | 764 K | 2.6 GB |
| 218 | w2v-xls-r-uk | 320 M | — | ✓ apache-2.0 | 764 K | 1.9 GB |
| 219 | Ternary-Bonsai-27B-gguf | — | — | ✓ apache-2.0 | 761 K | 1.2 GB |
| 220 | wav2vec2-xls-r-300m-hebrew | 320 M | — | unknown | 757 K | 1.9 GB |
| 221 | wav2vec2-large-robust-12-ft-emotion-msp-dim | 170 M | — | ✗ cc-by-nc-sa-4.0 | 751 K | 1.3 GB |
| 222 | Qwen3-0.6B-Base | 600 M | 33 K | ✓ apache-2.0 | 749 K | 1.9 GB |
| 223 | yolos-small | 30 M | — | ✓ apache-2.0 | 746 K | 0.6 GB |
| 224 | e5-small-v2 | 30 M | 512 | ✓ mit | 739 K | 0.7 GB |
| 225 | NVIDIA-Nemotron-3-Nano-4B-BF16 | 4.0 B | 262 K | other | 739 K | 9.8 GB |
| 226 | bert-base-multilingual-uncased-sentiment | 170 M | 512 | ✓ mit | 735 K | 1.3 GB |
| 227 | Qwen2.5-Coder-1.5B-Instruct | 1.5 B | 33 K | ✓ apache-2.0 | 728 K | 4.1 GB |
| 228 | Qwen3-4B-Base | 4.0 B | 33 K | ✓ apache-2.0 | 722 K | 10.0 GB |
| 229 | sd-turbo | 870 M | — | unknown | 722 K | 14.9 GB |
| 230 | BiRefNet | 220 M | — | ✓ mit | 715 K | 1.0 GB |
| 231 | RMBG-2.0 | 220 M | — | other | 702 K | 1.5 GB |
| 232 | bert-large-cased-finetuned-conll03-english | 330 M | 512 | unknown | 699 K | 2.0 GB |
| 233 | ruri-v3-310m | 310 M | 8 K | ✓ apache-2.0 | 695 K | 1.9 GB |
| 234 | nb-wav2vec2-1b-nynorsk | 960 M | — | ✓ apache-2.0 | 693 K | 4.9 GB |
| 235 | turn-detector | 130 M | 8 K | other | 690 K | 1.1 GB |
| 236 | vit_tiny_patch16_224.augreg_in21k_ft_in1k | 10 M | — | ✓ apache-2.0 | 689 K | 0.5 GB |
| 237 | xlm-roberta-base-language-detection | 280 M | 512 | ✓ mit | 687 K | 1.8 GB |
| 238 | vit_base_patch8_224.augreg2_in21k_ft_in1k | 90 M | — | ✓ apache-2.0 | 679 K | 0.9 GB |
| 239 | repvgg_a0.rvgg_in1k | 10 M | — | ✓ mit | 669 K | 0.5 GB |
| 240 | vit-base-nsfw-detector | 90 M | — | ✓ apache-2.0 | 660 K | 0.9 GB |
| 241 | VibeVoice-Realtime-0.5B | 1.0 B | — | ✓ mit | 657 K | 2.9 GB |
| 242 | bloom-560m | 560 M | — | ⚠ bigscience-bloom-rail-1.0 | 628 K | 1.8 GB |
| 243 | wav2vec2-large-xlsr-53-gender-recognition-librispeech | 320 M | — | ✓ apache-2.0 | 626 K | 1.9 GB |
| 244 | mask2former-swin-large-ade-semantic | 220 M | — | other | 625 K | 1.5 GB |
| 245 | DeepSeek-R1-Distill-Qwen-1.5B | 1.8 B | 131 K | ✓ mit | 619 K | 4.7 GB |
| 246 | OLMo-2-0425-1B | 1.5 B | 4 K | ✓ apache-2.0 | 618 K | 7.3 GB |
| 247 | parakeet-tdt-0.6b-v3-gguf | — | — | ✓ cc-by-4.0 | 606 K | 1.0 GB |
| 248 | Qwen2.5-Coder-7B-Instruct-AWQ | 7.6 B | 33 K | ✓ apache-2.0 | 604 K | 7.9 GB |
| 249 | cryptobert | 120 M | 512 | ✓ mit | 602 K | 1.1 GB |
| 250 | VLM2Vec-Full | 4.2 B | 131 K | ✓ apache-2.0 | 599 K | 10.2 GB |
VRAM figures are estimates for the smallest available quantization at 8K context — see /methodology. Downloads refresh nightly from the Hugging Face API.