1,000 models · refreshed nightly
Models that run on RTX 4090 · 24 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 4090 · 24 GB |
|---|---|---|---|---|---|---|
| 251 | Qwen3.8-4B-Distill-GGUF | — | — | ✓ apache-2.0 | 793 K | 3.6 GB |
| 252 | Qwen3-8B-FP8 | 8.2 B | 41 K | ✓ apache-2.0 | 780 K | 12.1 GB |
| 253 | rorshark-vit-base | 90 M | — | ✓ apache-2.0 | 777 K | 0.9 GB |
| 254 | Qwen3.8-2B-Distill-GGUF | — | — | ✓ apache-2.0 | 772 K | 1.9 GB |
| 255 | efficientnet_b0.ra_in1k | 10 M | — | ✓ apache-2.0 | 761 K | 0.5 GB |
| 256 | yolos-small | 30 M | — | ✓ apache-2.0 | 760 K | 0.6 GB |
| 257 | pythia-6.9b | 7.0 B | 2 K | ✓ apache-2.0 | 754 K | 16.8 GB |
| 258 | nemotron-3.5-asr-streaming-0.6b | 640 M | — | other | 752 K | 1.4 GB |
| 259 | gemma-2-9b-it | 9.2 B | — | ⚠ gemma | 745 K | 22.2 GB |
| 260 | VibeVoice-ASR | 8.7 B | — | ✓ mit | 738 K | 20.9 GB |
| 261 | LaBSE | 470 M | 512 | ✓ apache-2.0 | 734 K | 2.6 GB |
| 262 | bloomz-560m | 560 M | — | ⚠ bigscience-bloom-rail-1.0 | 724 K | 1.8 GB |
| 263 | Kokoro-82M-v1.0-ONNX | 82 M | — | ✓ apache-2.0 | 720 K | 0.7 GB |
| 264 | ast-finetuned-audioset-10-10-0.4593 | 90 M | — | ✓ bsd-3-clause | 719 K | 0.9 GB |
| 265 | deepseek-coder-7b-instruct-v1.5 | 6.9 B | 4 K | other | 718 K | 16.7 GB |
| 266 | Qwen3-14B-NVFP4 | 8.2 B | 41 K | ✓ apache-2.0 | 713 K | 13.3 GB |
| 267 | wav2vec2-large-robust-12-ft-emotion-msp-dim | 170 M | — | ✗ cc-by-nc-sa-4.0 | 713 K | 1.3 GB |
| 268 | Qwen2-0.5B | 490 M | 131 K | ✓ apache-2.0 | 709 K | 1.7 GB |
| 269 | resnet50.ram_in1k | 30 M | — | ✓ apache-2.0 | 709 K | 0.6 GB |
| 270 | gemma-4-12B-agentic-fable5-composer2.5-v2-3.5x-tau2-GGUF | — | — | ✓ apache-2.0 | 708 K | 1.4 GB |
| 271 | Qwen2.5-Coder-7B | 7.6 B | 33 K | ✓ apache-2.0 | 706 K | 18.4 GB |
| 272 | e5-base | 110 M | 512 | ✓ mit | 701 K | 1.0 GB |
| 273 | Qwen3.8-27B-DFlash2-GGUF | — | — | ✓ apache-2.0 | 696 K | 1.8 GB |
| 274 | Giga-Embeddings-instruct | 3.5 B | — | ✓ mit | 695 K | 16.2 GB |
| 275 | Qwen3.8-9B-Distill-GGUF | — | — | ✓ apache-2.0 | 693 K | 6.9 GB |
| 276 | bert-base-multilingual-uncased-sentiment | 170 M | 512 | ✓ mit | 689 K | 1.3 GB |
| 277 | Qwen2.5-7B | 7.6 B | 131 K | ✓ apache-2.0 | 687 K | 18.4 GB |
| 278 | LaBSE | 471 M | 512 | ✓ apache-2.0 | 687 K | 2.6 GB |
| 279 | wav2vec2-large-xlsr-53-gender-recognition-librispeech | 320 M | — | ✓ apache-2.0 | 676 K | 1.9 GB |
| 280 | paraphrase-multilingual-MiniLM-L12-v2 | 120 M | 512 | unknown | 675 K | 0.8 GB |
| 281 | wikineural-multilingual-ner | 180 M | 512 | ✗ cc-by-nc-sa-4.0 | 675 K | 1.3 GB |
| 282 | parakeet-ctc-1.1b | 1.1 B | — | ✓ cc-by-4.0 | 672 K | 2.0 GB |
| 283 | paraphrase-MiniLM-L3-v2 | 20 M | 512 | ✓ apache-2.0 | 668 K | 0.6 GB |
| 284 | gte-Qwen2-1.5B-instruct | 1.8 B | 131 K | ✓ apache-2.0 | 665 K | 8.6 GB |
| 285 | gemma-2-2b-it | 2.6 B | — | ⚠ gemma | 663 K | 6.6 GB |
| 286 | Ternary-Bonsai-27B-gguf | — | — | ✓ apache-2.0 | 663 K | 1.2 GB |
| 287 | Qwen3-TTS-12Hz-0.6B-Base | 910 M | — | ✓ apache-2.0 | 655 K | 3.4 GB |
| 288 | stable-diffusion-v1-4 | 860 M | — | ⚠ creativeml-openrail-m | 650 K | 13.5 GB |
| 289 | audiobox-aesthetics | 100 M | — | ✓ cc-by-4.0 | 637 K | 1.0 GB |
| 290 | nli-mpnet-base-v2 | 110 M | 512 | ✓ apache-2.0 | 635 K | 1.0 GB |
| 291 | Nemotron-3-Embed-1B-BF16 | 1.1 B | 262 K | other | 633 K | 3.2 GB |
| 292 | all-roberta-large-v1 | 360 M | 512 | ✓ apache-2.0 | 632 K | 2.1 GB |
| 293 | Qwen2.5-Coder-7B-Instruct-AWQ | 7.6 B | 33 K | ✓ apache-2.0 | 623 K | 7.9 GB |
| 294 | RMBG-2.0 | 220 M | — | other | 622 K | 1.5 GB |
| 295 | MiniCPM-SALA-AWQ-8bit | 3.1 B | 524 K | ✓ apache-2.0 | 616 K | 12.7 GB |
| 296 | gte-large | 340 M | 512 | ✓ mit | 616 K | 1.3 GB |
| 297 | SmolLM3-3B-Base | 3.1 B | 66 K | ✓ apache-2.0 | 615 K | 7.7 GB |
| 298 | SmolLM3-3B | 3.1 B | 66 K | ✓ apache-2.0 | 614 K | 7.7 GB |
| 299 | EXAONE-3.5-7.8B-Instruct-AWQ | 7.8 B | 33 K | other | 614 K | 7.5 GB |
| 300 | MiniCPM5-1B | 1.1 B | 131 K | ✓ apache-2.0 | 611 K | 3.0 GB |
VRAM figures are estimates for the smallest available quantization at 8K context — see /methodology. Downloads refresh nightly from the Hugging Face API.