1,011 models · refreshed nightly
All models
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 | Min VRAM |
|---|---|---|---|---|---|---|
| 01 | all-MiniLM-L6-v2 | 20 M | 512 | ✓ apache-2.0 | 257.8 M | from 0.6 GB |
| 02 | bge-small-en-v1.5 | 30 M | 512 | ✓ mit | 72.4 M | from 0.7 GB |
| 03 | paraphrase-multilingual-MiniLM-L12-v2 | 120 M | 512 | ✓ apache-2.0 | 59.4 M | from 1.0 GB |
| 04 | bge-m3 | — | 8 K | ✓ mit | 35.0 M | — |
| 05 | Qwen3-0.6B | 750 M | 41 K | ✓ apache-2.0 | 29.7 M | from 2.3 GB |
| 06 | all-mpnet-base-v2 | 110 M | 512 | ✓ apache-2.0 | 25.2 M | from 1.0 GB |
| 07 | t5-small | 60 M | — | ✓ apache-2.0 | 24.7 M | from 0.8 GB |
| 08 | bge-reranker-v2-m3 | 570 M | 8 K | ✓ apache-2.0 | 19.2 M | from 3.1 GB |
| 09 | opt-125m | — | 2 K | other | 18.5 M | — |
| 10 | mobilenetv3_small_100.lamb_in1k | 0 M | — | ✓ apache-2.0 | 18.5 M | from 0.5 GB |
| 11 | Qwen3-8B | 8.2 B | 41 K | ✓ apache-2.0 | 16.3 M | from 19.7 GB |
| 12 | nomic-embed-text-v1.5 | 140 M | 2 K | ✓ apache-2.0 | 15.7 M | from 1.1 GB |
| 13 | multilingual-e5-small | 120 M | 512 | ✓ mit | 15.6 M | from 1.0 GB |
| 14 | Qwen2.5-1.5B-Instruct | 1.5 B | 33 K | ✓ apache-2.0 | 14.0 M | from 4.1 GB |
| 15 | gpt2 | 140 M | — | ✓ mit | 13.7 M | from 1.1 GB |
| 16 | bge-large-en-v1.5 | 340 M | 512 | ✓ mit | 13.1 M | from 2.0 GB |
| 17 | Qwen3.5-9B | 9.7 B | — | ✓ apache-2.0 | 12.4 M | from 23.2 GB |
| 18 | Qwen2.5-7B-Instruct | 7.6 B | 33 K | ✓ apache-2.0 | 12.1 M | from 18.4 GB |
| 19 | Kokoro-82M | — | — | ✓ apache-2.0 | 12.0 M | — |
| 20 | gemma-4-31B-it | 32.7 B | — | ✓ apache-2.0 | 11.9 M | from 74.2 GB |
| 21 | gemma-4-26B-A4B-it | 26.5 B | — | ✓ apache-2.0 | 11.7 M | from 61.3 GB |
| 22 | paraphrase-multilingual-mpnet-base-v2 | 280 M | 512 | ✓ apache-2.0 | 11.5 M | from 1.8 GB |
| 23 | Qwen3.6-35B-A3B-NVFP4 | 18.7 B | — | ✓ apache-2.0 | 11.3 M | from 29.1 GB |
| 24 | Llama-3.2-1B-Instruct | 1.2 B | — | ⚠ llama3.2 | 10.4 M | from 3.4 GB |
| 25 | bge-base-en-v1.5 | 110 M | 512 | ✓ mit | 10.0 M | from 1.0 GB |
| 26 | DeepSeek-R1 | 684.5 B | 164 K | ✓ mit | 9.9 M | from 860.6 GB |
| 27 | Qwen3-Embedding-0.6B | 600 M | 33 K | ✓ apache-2.0 | 9.8 M | from 1.9 GB |
| 28 | Qwen2.5-VL-7B-Instruct | 8.3 B | 128 K | ✓ apache-2.0 | 9.3 M | from 20.0 GB |
| 29 | XTTS-v2 | — | — | other | 9.2 M | — |
| 30 | Qwen3.6-35B-A3B-FP8 | 36.0 B | — | ✓ apache-2.0 | 8.9 M | from 47.1 GB |
| 31 | speaker-diarization-3.1 | — | — | ✓ mit | 8.9 M | — |
| 32 | whisper-large-v3-turbo | 810 M | — | ✓ mit | 8.7 M | from 2.4 GB |
| 33 | gpt-oss-20b | 21.5 B | 131 K | ✓ apache-2.0 | 8.6 M | from 34.0 GB |
| 34 | Qwen3-32B | 32.8 B | 41 K | ✓ apache-2.0 | 8.3 M | from 77.5 GB |
| 35 | whisperkit-coreml | — | — | unknown | 8.3 M | — |
| 36 | Qwen2.5-VL-3B-Instruct | 3.8 B | 128 K | unknown | 8.2 M | from 9.3 GB |
| 37 | Llama-3.1-8B-Instruct | 8.0 B | — | ⚠ llama3.1 | 8.0 M | from 19.4 GB |
| 38 | Qwen3.6-27B-FP8 | 27.8 B | — | ✓ apache-2.0 | 7.8 M | from 38.6 GB |
| 39 | Qwen3-1.7B | 2.0 B | 41 K | ✓ apache-2.0 | 7.8 M | from 5.3 GB |
| 40 | multilingual-e5-large | 560 M | 512 | ✓ mit | 7.5 M | from 3.0 GB |
| 41 | multilingual-e5-base | 280 M | 512 | ✓ mit | 7.2 M | from 1.8 GB |
| 42 | Qwen3.6-27B | 27.8 B | — | ✓ apache-2.0 | 7.0 M | from 65.8 GB |
| 43 | clap-htsat-fused | 150 M | — | ✓ apache-2.0 | 6.9 M | from 1.2 GB |
| 44 | Qwen3.5-4B | 4.7 B | — | ✓ apache-2.0 | 6.7 M | from 11.5 GB |
| 45 | Qwen2.5-0.5B-Instruct | 490 M | 33 K | ✓ apache-2.0 | 6.6 M | from 1.7 GB |
| 46 | Qwen2.5-3B-Instruct | 3.1 B | 33 K | other | 6.0 M | from 7.8 GB |
| 47 | Qwen3.6-35B-A3B | 36.0 B | — | ✓ apache-2.0 | 5.9 M | from 85.0 GB |
| 48 | finbert | — | 512 | unknown | 5.6 M | — |
| 49 | whisper-large-v3 | 1.5 B | — | ✓ apache-2.0 | 5.5 M | from 10.9 GB |
| 50 | nsfw_image_detection | 90 M | — | ✓ apache-2.0 | 5.4 M | from 0.9 GB |
VRAM figures are estimates for the smallest available quantization at 8K context — see /methodology. Downloads refresh nightly from the Hugging Face API.