1,423 models · 1,213 open weights · 210 API-only · refreshed nightly
Models that run on RTX 3060 · 12 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 3060 · 12 GB |
|---|---|---|---|---|---|---|
| 151 | MiniCPM5-2B | 2.5 B | 131 K | ✓ apache-2.0 | 1.1 M | 6.4 GB |
| 152 | bert-base-NER | 110 M | 512 | ✓ mit | 1.1 M | 1.0 GB |
| 153 | Qwen3.8-Flash-Next-Gyro-abliterated-Huihui-GGUF | — | — | other | 1.1 M | 3.5 GB |
| 154 | turn-detector | 130 M | 8 K | other | 1.1 M | 1.1 GB |
| 155 | Breeze-TTS-2.cpp | — | — | other | 1.0 M | 3.3 GB |
| 156 | wav2vec2-xls-r-parlaspeech-hr | 320 M | — | unknown | 1.0 M | 1.9 GB |
| 157 | Qwen2-VL-2B-Instruct | 2.2 B | 33 K | ✓ apache-2.0 | 1.0 M | 5.7 GB |
| 158 | BiRefNet | 220 M | — | ✓ mit | 1.0 M | 1.0 GB |
| 159 | Ternary-Bonsai-27B-mlx-2bit | 2.6 B | — | ✓ apache-2.0 | 1.0 M | 10.2 GB |
| 160 | jina-embeddings-v5-omni-small | 1.6 B | — | ✗ cc-by-nc-4.0 | 1.0 M | 4.5 GB |
| 161 | e5-base-v2 | 110 M | 512 | ✓ mit | 1.0 M | 1.0 GB |
| 162 | UAE-Large-V1 | 340 M | 512 | ✓ mit | 1.0 M | 2.0 GB |
| 163 | gemma-3-4b-it | 4.3 B | — | ⚠ gemma | 1.0 M | 10.6 GB |
| 164 | Bonsai-27B-mlx-1bit | 1.7 B | — | ✓ apache-2.0 | 1.0 M | 6.4 GB |
| 165 | Qwen3.8-27B-GGUF | 27.0 B | — | ✓ apache-2.0 | 1.0 M | 6.4 GB |
| 166 | wav2vec2-xls-r-300m-hebrew | 320 M | — | unknown | 1.0 M | 1.9 GB |
| 167 | parakeet-ultra-gguf | — | — | ✓ cc-by-4.0 | 1,000 K | 1.0 GB |
| 168 | Ternary-Bonsai-2-2B-gguf | 2.0 B | — | ✓ apache-2.0 | 994 K | 1.2 GB |
| 169 | wav2vec2-xls-r-300m-cv7-turkish | 300 M | — | ✓ cc-by-4.0 | 991 K | 1.2 GB |
| 170 | VoxCPM2 | 2.3 B | — | ✓ apache-2.0 | 987 K | 5.9 GB |
| 171 | e5-small-v2 | 30 M | 512 | ✓ mit | 986 K | 0.7 GB |
| 172 | MiMo-V2.6-Distill-Qwen-9B-GGUF | 9.0 B | — | unknown | 984 K | 5.7 GB |
| 173 | sup-SimCSE-VietNamese-phobert-base | 140 M | 256 | unknown | 978 K | 1.1 GB |
| 174 | surya-ocr-2 | 690 M | — | ⚠ openrail | 975 K | 2.1 GB |
| 175 | vietnamese-bi-encoder | 130 M | 256 | ✓ apache-2.0 | 968 K | 1.1 GB |
| 176 | LaBSE | 470 M | 512 | ✓ apache-2.0 | 965 K | 2.6 GB |
| 177 | InternVL2-1B | 940 M | — | ✓ mit | 964 K | 2.7 GB |
| 178 | Z-Image-Turbo-GGUF | 6.2 B | — | ✓ apache-2.0 | 963 K | 4.0 GB |
| 179 | 1 | — | 2 K | unknown | 963 K | 0.5 GB |
| 180 | e5-base | 110 M | 512 | ✓ mit | 953 K | 1.0 GB |
| 181 | Tess-4.5-27B-GGUF | 27.0 B | — | ✓ apache-2.0 | 952 K | 5.6 GB |
| 182 | nb-wav2vec2-1b-bokmaal-v2 | 960 M | — | ✓ apache-2.0 | 947 K | 4.9 GB |
| 183 | TinyLlama-1.1B-Chat-v1.0 | 1.1 B | 2 K | ✓ apache-2.0 | 944 K | 3.1 GB |
| 184 | PP-DocLayoutV3_safetensors | 33 M | — | ✓ apache-2.0 | 937 K | 0.7 GB |
| 185 | Wav2Vec2-large-xlsr-hindi | 316 M | — | unknown | 932 K | 1.9 GB |
| 186 | nllb-200-distilled-600M | 600 M | 1 K | ✗ cc-by-nc-4.0 | 932 K | 1.9 GB |
| 187 | paraphrase-MiniLM-L3-v2 | 20 M | 512 | ✓ apache-2.0 | 919 K | 0.6 GB |
| 188 | gpt2-large | 810 M | — | ✓ mit | 908 K | 4.2 GB |
| 189 | llmlingua-2-bert-base-multilingual-cased-meetingbank | 180 M | 512 | ✓ apache-2.0 | 905 K | 1.3 GB |
| 190 | dreamshaper-7 | 860 M | — | ⚠ creativeml-openrail-m | 902 K | 9.7 GB |
| 191 | JiRackUltra_1b | 1.8 B | 131 K | ✓ mit | 891 K | 1.8 GB |
| 192 | wav2vec2-xls-r-300m-ftspeech | 320 M | — | other | 888 K | 1.9 GB |
| 193 | gte-multilingual-base | 310 M | 8 K | ✓ apache-2.0 | 883 K | 1.2 GB |
| 194 | distiluse-base-multilingual-cased-v2 | 130 M | 512 | ✓ apache-2.0 | 879 K | 1.1 GB |
| 195 | Sharp-Spark-X2.5-4B-GGUF | 4.0 B | — | ✓ apache-2.0 | 874 K | 1.1 GB |
| 196 | Llama-3.2-3B-Instruct | 3.2 B | — | ⚠ llama3.2 | 872 K | 8.0 GB |
| 197 | stsb-bert-tiny-safetensors | <0.1 M | 512 | unknown | 860 K | 0.5 GB |
| 198 | rorshark-vit-base | 90 M | — | ✓ apache-2.0 | 860 K | 0.9 GB |
| 199 | text2vec-base-chinese | 100 M | 512 | ✓ apache-2.0 | 855 K | 1.0 GB |
| 200 | bge-small-en-v1.5 | 30 M | 512 | unknown | 855 K | 0.6 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.