1,423 models · 1,213 open weights · 210 API-only · refreshed nightly
Models that run on RTX 4090 · 24 GB
Every model in the catalog — open weights you can self-host and API-only models — with licence or API price, estimated VRAM and daily-tracked downloads. Filters update the URL — share any view.
| # | Model | Params | Context | Commercial use | 30d | On RTX 4090 · 24 GB |
|---|---|---|---|---|---|---|
| 201 | Bonsai-27B-mlx-1bit | 1.7 B | — | ✓ apache-2.0 | 1.0 M | 6.4 GB |
| 202 | Qwen3.8-27B-GGUF | 27.0 B | — | ✓ apache-2.0 | 1.0 M | 6.4 GB |
| 203 | wav2vec2-xls-r-300m-hebrew | 320 M | — | unknown | 1.0 M | 1.9 GB |
| 204 | parakeet-ultra-gguf | — | — | ✓ cc-by-4.0 | 1,000 K | 1.0 GB |
| 205 | Ternary-Bonsai-2-2B-gguf | 2.0 B | — | ✓ apache-2.0 | 994 K | 1.2 GB |
| 206 | Cyber-Tiel-Coder-35B-A3B-GGUF-MTP | 35.0 B | — | ✓ mit | 992 K | 19.7 GB |
| 207 | wav2vec2-xls-r-300m-cv7-turkish | 300 M | — | ✓ cc-by-4.0 | 991 K | 1.2 GB |
| 208 | VoxCPM2 | 2.3 B | — | ✓ apache-2.0 | 987 K | 5.9 GB |
| 209 | e5-small-v2 | 30 M | 512 | ✓ mit | 986 K | 0.7 GB |
| 210 | MiMo-V2.6-Distill-Qwen-9B-GGUF | 9.0 B | — | unknown | 984 K | 5.7 GB |
| 211 | sup-SimCSE-VietNamese-phobert-base | 140 M | 256 | unknown | 978 K | 1.1 GB |
| 212 | surya-ocr-2 | 690 M | — | ⚠ openrail | 975 K | 2.1 GB |
| 213 | vietnamese-bi-encoder | 130 M | 256 | ✓ apache-2.0 | 968 K | 1.1 GB |
| 214 | LaBSE | 470 M | 512 | ✓ apache-2.0 | 965 K | 2.6 GB |
| 215 | InternVL2-1B | 940 M | — | ✓ mit | 964 K | 2.7 GB |
| 216 | Z-Image-Turbo-GGUF | 6.2 B | — | ✓ apache-2.0 | 963 K | 4.0 GB |
| 217 | 1 | — | 2 K | unknown | 963 K | 0.5 GB |
| 218 | e5-base | 110 M | 512 | ✓ mit | 953 K | 1.0 GB |
| 219 | Tess-4.5-27B-GGUF | 27.0 B | — | ✓ apache-2.0 | 952 K | 5.6 GB |
| 220 | nb-wav2vec2-1b-bokmaal-v2 | 960 M | — | ✓ apache-2.0 | 947 K | 4.9 GB |
| 221 | TinyLlama-1.1B-Chat-v1.0 | 1.1 B | 2 K | ✓ apache-2.0 | 944 K | 3.1 GB |
| 222 | PP-DocLayoutV3_safetensors | 33 M | — | ✓ apache-2.0 | 937 K | 0.7 GB |
| 223 | Wav2Vec2-large-xlsr-hindi | 316 M | — | unknown | 932 K | 1.9 GB |
| 224 | nllb-200-distilled-600M | 600 M | 1 K | ✗ cc-by-nc-4.0 | 932 K | 1.9 GB |
| 225 | Qwen3.8-27B-AP-GGUF | 27.0 B | — | ✓ apache-2.0 | 923 K | 15.1 GB |
| 226 | ThinkingCap-Qwen3.8-27B-GGUF | 27.0 B | — | other | 923 K | 21.6 GB |
| 227 | paraphrase-MiniLM-L3-v2 | 20 M | 512 | ✓ apache-2.0 | 919 K | 0.6 GB |
| 228 | gpt2-large | 810 M | — | ✓ mit | 908 K | 4.2 GB |
| 229 | llmlingua-2-bert-base-multilingual-cased-meetingbank | 180 M | 512 | ✓ apache-2.0 | 905 K | 1.3 GB |
| 230 | dreamshaper-7 | 860 M | — | ⚠ creativeml-openrail-m | 902 K | 9.7 GB |
| 231 | JiRackUltra_1b | 1.8 B | 131 K | ✓ mit | 891 K | 1.8 GB |
| 232 | wav2vec2-xls-r-300m-ftspeech | 320 M | — | other | 888 K | 1.9 GB |
| 233 | gte-multilingual-base | 310 M | 8 K | ✓ apache-2.0 | 883 K | 1.2 GB |
| 234 | LFM2.5-24B-A2B-Turbo-Brilliance-50X-NEO-MAX-Imatrix-GGUF | 24.0 B | 131 K | other | 881 K | 15.7 GB |
| 235 | distiluse-base-multilingual-cased-v2 | 130 M | 512 | ✓ apache-2.0 | 879 K | 1.1 GB |
| 236 | Sharp-Spark-X2.5-4B-GGUF | 4.0 B | — | ✓ apache-2.0 | 874 K | 1.1 GB |
| 237 | Llama-3.2-3B-Instruct | 3.2 B | — | ⚠ llama3.2 | 872 K | 8.0 GB |
| 238 | stsb-bert-tiny-safetensors | <0.1 M | 512 | unknown | 860 K | 0.5 GB |
| 239 | rorshark-vit-base | 90 M | — | ✓ apache-2.0 | 860 K | 0.9 GB |
| 240 | text2vec-base-chinese | 100 M | 512 | ✓ apache-2.0 | 855 K | 1.0 GB |
| 241 | bge-small-en-v1.5 | 30 M | 512 | unknown | 855 K | 0.6 GB |
| 242 | pubmedbert-base-embeddings | 110 M | 512 | ✓ apache-2.0 | 848 K | 1.0 GB |
| 243 | SmolLM2-135M-Instruct | 130 M | 8 K | ✓ apache-2.0 | 847 K | 0.8 GB |
| 244 | w2v-xls-r-uk | 320 M | — | ✓ apache-2.0 | 844 K | 1.9 GB |
| 245 | Qwen3-TTS-12Hz-0.6B-Base | 910 M | — | ✓ apache-2.0 | 842 K | 3.4 GB |
| 246 | nomic-embed-text-v1 | 140 M | 8 K | ✓ apache-2.0 | 836 K | 1.1 GB |
| 247 | wav2vec2-large-xlsr-53-gender-recognition-librispeech | 320 M | — | ✓ apache-2.0 | 835 K | 1.9 GB |
| 248 | Qwen3-8B-GGUF | — | — | ✓ apache-2.0 | 826 K | 6.0 GB |
| 249 | parakeet-tdt-0.6b-v2 | 620 M | — | ✓ cc-by-4.0 | 815 K | 3.3 GB |
| 250 | Ornith-1.0-9B | <0.1 M | — | ✓ mit | 814 K | 21.2 GB |
VRAM figures are estimates for the smallest available quantization at 8K context — see /methodology. Downloads refresh nightly from the Hugging Face API; API prices (blended 3:1 input:output per 1M tokens) and Artificial Analysis indices from OpenRouter.