1,213 models · 1,213 open weights · 210 API-only · refreshed nightly
Open-weights models
Models whose weights are published on Hugging Face — download them and run them on your own hardware. Many are also served by hosted providers; those carry an "Also via API" badge with live prices.
| # | Model | Params | Context | Commercial use | 30d | On RTX 3060 · 12 GB |
|---|---|---|---|---|---|---|
| 101 | nsfw_image_detection | 90 M | — | ✓ apache-2.0 | 1.6 M | 0.9 GB |
| 102 | Qwen-Image-2.1-GGUF | 7.1 B | — | other | 1.6 M | 4.3 GB |
| 103 | Qwen3-8B-AWQ | 8.2 B | 41 K | ✓ apache-2.0 | 1.6 M | 8.4 GB |
| 104 | Swift-1.5-Qwen3.8-27B-GSQ-RCO-GGUF | 27.0 B | — | other | 1.6 M | 4.6 GB |
| 105 | kokoro-inno-clone-tuner | 9.7 M | — | ✓ apache-2.0 | 1.6 M | 0.5 GB |
| 106 | Qwen3.5-4B-GGUF | — | — | ✓ apache-2.0 | 1.5 M | 2.8 GB |
| 107 | paraphrase-MiniLM-L6-v2 | 20 M | 512 | ✓ apache-2.0 | 1.5 M | 0.6 GB |
| 108 | Qwen3-4B-Instruct-2507-FP8 | 4.4 B | 262 K | ✓ apache-2.0 | 1.5 M | 6.9 GB |
| 109 | distilgpt2 | 90 M | — | ✓ apache-2.0 | 1.5 M | 0.9 GB |
| 110 | jina-embeddings-v3 | 570 M | 8 K | ✗ cc-by-nc-4.0 | 1.5 M | 1.8 GB |
| 111 | multi-qa-mpnet-base-dot-v1 | 110 M | 512 | unknown | 1.5 M | 1.0 GB |
| 112 | SapBERT-from-PubMedBERT-fulltext | 110 M | 512 | ✓ apache-2.0 | 1.4 M | 1.0 GB |
| 113 | Qwen3-TTS-12Hz-1.7B-CustomVoice | 1.9 B | — | ✓ apache-2.0 | 1.4 M | 5.8 GB |
| 114 | Qwen2.5-3B-Instruct-AWQ | 3.4 B | 33 K | other | 1.4 M | 4.0 GB |
| 115 | wav2vec2-xls-r-300m-cs-250 | 320 M | — | ✓ apache-2.0 | 1.4 M | 1.9 GB |
| 116 | rtdetr_r101vd_coco_o365 | 80 M | — | ✓ apache-2.0 | 1.4 M | 0.9 GB |
| 117 | Qwen3.8-27B-GSQ-RCO-GGUF | — | — | ✓ apache-2.0 | 1.4 M | 1.5 GB |
| 118 | Qwen-Image-2.1-Turbo-GGUF | — | — | other | 1.4 M | 3.2 GB |
| 119 | gender-classification | 90 M | — | unknown | 1.3 M | 0.9 GB |
| 120 | Llama-3.2-1B-Instruct | 1.2 B | — | ⚠ llama3.2 | 1.3 M | 3.4 GB |
| 121 | ko-sroberta-multitask | 110 M | 512 | unknown | 1.3 M | 1.0 GB |
| 122 | w2v-bert-2.0 | 580 M | — | ✓ mit | 1.3 M | 3.1 GB |
| 123 | Qwen2.5-VL-7B-Instruct-AWQ | 8.3 B | 128 K | ✓ apache-2.0 | 1.3 M | 9.4 GB |
| 124 | wav2vec2-large-voxrex-swedish | 320 M | — | ✓ cc0-1.0 | 1.3 M | 1.9 GB |
| 125 | table-transformer-structure-recognition | 30 M | 1 K | ✓ mit | 1.3 M | 0.6 GB |
| 126 | F5-TTS | — | — | ✗ cc-by-nc-4.0 | 1.3 M | 5.0 GB |
| 127 | Ornith-1.5-397B-GGUF | — | — | ✓ mit | 1.3 M | 1.5 GB |
| 128 | jina-embeddings-v2-small-en | 30 M | 8 K | ✓ apache-2.0 | 1.3 M | 0.6 GB |
| 129 | efficientvit_l2.r288_in1k | 64 M | — | ✓ apache-2.0 | 1.3 M | 0.8 GB |
| 130 | Qwen3-ASR-1.7B-gguf | 1.7 B | — | ✓ apache-2.0 | 1.2 M | 2.2 GB |
| 131 | cohere-transcribe-03-2026-gguf | 2.1 B | — | ✓ apache-2.0 | 1.2 M | 2.5 GB |
| 132 | Qwen2.5-VL-7B-Instruct-NVFP4 | 5.0 B | 128 K | other | 1.2 M | 9.2 GB |
| 133 | Llama-3.2-1B-Instruct | 1.2 B | 131 K | ⚠ llama3.2 | 1.2 M | 3.4 GB |
| 134 | Qwen3-TTS-GGUF | — | — | ✓ apache-2.0 | 1.2 M | 1.8 GB |
| 135 | romanian-wav2vec2 | 320 M | — | ✓ apache-2.0 | 1.2 M | 1.9 GB |
| 136 | Qwen2.5-0.5B | 490 M | 33 K | ✓ apache-2.0 | 1.2 M | 1.7 GB |
| 137 | Ternary-Bonsai-2-9B-gguf | 9.0 B | — | ✓ apache-2.0 | 1.2 M | 2.9 GB |
| 138 | embeddinggemma-300m | 300 M | — | ⚠ gemma | 1.2 M | 1.9 GB |
| 139 | parakeet-tdt-0.6b-v3-gguf | 600 M | — | ✓ cc-by-4.0 | 1.1 M | 1.1 GB |
| 140 | wav2vec2-large-xlsr-korean | 320 M | — | ✓ apache-2.0 | 1.1 M | 1.9 GB |
| 141 | Qwen3-0.6B | 752 M | 41 K | ✓ apache-2.0 | 1.1 M | 2.3 GB |
| 142 | Higgs-Audio-v3-Studio | — | — | other | 1.1 M | 5.0 GB |
| 143 | Swift-1.5-Qwen3.8-27B-heretic-GSQ-RCO-GGUF | 27.0 B | — | other | 1.1 M | 5.6 GB |
| 144 | Ornith-1.5-9B-NVFP4 | 6.7 B | — | ✓ mit | 1.1 M | 11.2 GB |
| 145 | wav2vec2-xls-r-300m-mixed | 300 M | — | unknown | 1.1 M | 1.2 GB |
| 146 | USER2-base | 149 M | 8 K | ✓ apache-2.0 | 1.1 M | 1.2 GB |
| 147 | filipino-wav2vec2-l-xls-r-300m-official | 300 M | — | ✓ apache-2.0 | 1.1 M | 1.2 GB |
| 148 | Qwen3-VL-2B-Instruct | 2.1 B | — | ✓ apache-2.0 | 1.1 M | 5.5 GB |
| 149 | wav2vec2-large-xls-r-300m-Urdu | 320 M | — | ✓ apache-2.0 | 1.1 M | 1.9 GB |
| 150 | bart-large-cnn | 410 M | 1 K | ✓ mit | 1.1 M | 2.3 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.