1,011 models · refreshed nightly
Models that run on RTX 3060 · 12 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 3060 · 12 GB |
|---|---|---|---|---|---|---|
| 101 | tf_efficientnetv2_s.in21k_ft_in1k | 20 M | — | ✓ apache-2.0 | 1.6 M | 0.6 GB |
| 102 | t5-base | 220 M | — | ✓ apache-2.0 | 1.6 M | 1.5 GB |
| 103 | SapBERT-from-PubMedBERT-fulltext | 110 M | 512 | ✓ apache-2.0 | 1.6 M | 1.0 GB |
| 104 | paraphrase-mpnet-base-v2 | 110 M | 512 | ✓ apache-2.0 | 1.6 M | 1.0 GB |
| 105 | Qwen3-TTS-12Hz-0.6B-CustomVoice | 910 M | — | ✓ apache-2.0 | 1.6 M | 3.4 GB |
| 106 | Qwen3-0.6B-FP8 | 750 M | 41 K | ✓ apache-2.0 | 1.6 M | 1.8 GB |
| 107 | bge-small-en | 30 M | 512 | ✓ mit | 1.6 M | 0.7 GB |
| 108 | bart-large-cnn | 410 M | 1 K | ✓ mit | 1.6 M | 2.3 GB |
| 109 | gender-classification | 90 M | — | unknown | 1.5 M | 0.9 GB |
| 110 | nomic-embed-text-v2-moe | 480 M | — | ✓ apache-2.0 | 1.5 M | 2.7 GB |
| 111 | OpenELM-1_1B-Instruct | 1.1 B | — | apple-amlr | 1.5 M | 3.0 GB |
| 112 | SmolLM-1.7B-Instruct-quantized.w4a16 | 1.8 B | 2 K | ✓ apache-2.0 | 1.5 M | 2.7 GB |
| 113 | Llama-3.2-1B-Instruct-FP8-dynamic | 1.5 B | 131 K | ⚠ llama3.2 | 1.5 M | 3.0 GB |
| 114 | gpt2-large | 810 M | — | ✓ mit | 1.5 M | 4.2 GB |
| 115 | table-transformer-structure-recognition | 30 M | 1 K | ✓ mit | 1.5 M | 0.6 GB |
| 116 | Llama-3.2-3B-Instruct | 3.2 B | — | ⚠ llama3.2 | 1.5 M | 8.0 GB |
| 117 | InternVL2-2B | 2.2 B | — | ✓ mit | 1.5 M | 5.7 GB |
| 118 | parakeet-tdt-0.6b-v3 | 630 M | — | ✓ cc-by-4.0 | 1.4 M | 3.4 GB |
| 119 | snowflake-arctic-embed-l-v2.0 | 570 M | 8 K | ✓ apache-2.0 | 1.4 M | 3.1 GB |
| 120 | gemma-4-26B-A4B-it-GGUF | — | — | ✓ apache-2.0 | 1.4 M | 11.4 GB |
| 121 | wav2vec2-xls-r-300m-cs-250 | 320 M | — | ✓ apache-2.0 | 1.4 M | 1.9 GB |
| 122 | w2v-bert-2.0 | 580 M | — | ✓ mit | 1.4 M | 3.1 GB |
| 123 | Qwen3-VL-Embedding-2B | 2.1 B | — | ✓ apache-2.0 | 1.4 M | 5.5 GB |
| 124 | Phi-3.5-vision-instruct | 4.2 B | 131 K | ✓ mit | 1.3 M | 10.2 GB |
| 125 | bert-base-NER | 110 M | 512 | ✓ mit | 1.3 M | 1.0 GB |
| 126 | h2ovl-mississippi-800m | 830 M | — | ✓ apache-2.0 | 1.3 M | 2.4 GB |
| 127 | efficientnet_b0.ra_in1k | 10 M | — | ✓ apache-2.0 | 1.3 M | 0.5 GB |
| 128 | h2ovl-mississippi-2b | 2.2 B | — | ✓ apache-2.0 | 1.3 M | 5.6 GB |
| 129 | deepseek-vl2-tiny | 3.4 B | — | other | 1.3 M | 8.4 GB |
| 130 | gte-multilingual-base | 310 M | 8 K | ✓ apache-2.0 | 1.2 M | 1.2 GB |
| 131 | romanian-wav2vec2 | 320 M | — | ✓ apache-2.0 | 1.2 M | 1.9 GB |
| 132 | table-transformer-detection | 30 M | 1 K | ✓ mit | 1.2 M | 0.6 GB |
| 133 | ast-finetuned-audioset-10-10-0.4593 | 90 M | — | ✓ bsd-3-clause | 1.2 M | 0.9 GB |
| 134 | Qwen3.5-4B-GGUF | — | — | ✓ apache-2.0 | 1.2 M | 2.8 GB |
| 135 | gte-Qwen2-1.5B-instruct | 1.8 B | 131 K | ✓ apache-2.0 | 1.2 M | 8.6 GB |
| 136 | bloomz-560m | 560 M | — | ⚠ bigscience-bloom-rail-1.0 | 1.2 M | 1.8 GB |
| 137 | resnet-50 | 30 M | — | ✓ apache-2.0 | 1.2 M | 0.6 GB |
| 138 | Qwen3-4B-Instruct-2507-FP8 | 4.4 B | 262 K | ✓ apache-2.0 | 1.2 M | 6.9 GB |
| 139 | SmolVLM2-500M-Video-Instruct | 510 M | — | ✓ apache-2.0 | 1.2 M | 2.8 GB |
| 140 | surya-ocr-2 | 690 M | — | ⚠ openrail | 1.2 M | 2.1 GB |
| 141 | Qwen3-8B-AWQ | 8.2 B | 41 K | ✓ apache-2.0 | 1.1 M | 8.4 GB |
| 142 | e5-base-v2 | 110 M | 512 | ✓ mit | 1.1 M | 1.0 GB |
| 143 | bge-micro-v2 | 20 M | 512 | ✓ mit | 1.1 M | 0.5 GB |
| 144 | Phi-3.5-mini-instruct | 3.8 B | 131 K | ✓ mit | 1.1 M | 9.5 GB |
| 145 | Wav2Vec2-large-xlsr-hindi | 320 M | — | unknown | 1.1 M | 1.9 GB |
| 146 | clipseg-rd64-refined | 150 M | — | ✓ apache-2.0 | 1.1 M | 1.2 GB |
| 147 | all-roberta-large-v1 | 360 M | 512 | ✓ apache-2.0 | 1.1 M | 2.1 GB |
| 148 | SmolVLM-256M-Instruct | 260 M | — | ✓ apache-2.0 | 1.1 M | 1.1 GB |
| 149 | 1 | — | 2 K | unknown | 1.1 M | 0.5 GB |
| 150 | TinyLlama-1.1B-Chat-v0.3-GPTQ | 1.1 B | 2 K | ✓ apache-2.0 | 1.1 M | 1.5 GB |
VRAM figures are estimates for the smallest available quantization at 8K context — see /methodology. Downloads refresh nightly from the Hugging Face API.