1,423 models · 1,213 open weights · 210 API-only · refreshed nightly
Models that run on Mac M3 · 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 Mac M3 · 24 GB |
|---|---|---|---|---|---|---|
| 01 | all-MiniLM-L6-v2 | 20 M | 512 | ✓ apache-2.0 | 177.6 M | 0.6 GB |
| 02 | bge-small-en-v1.5 | 30 M | 512 | ✓ mit | 47.6 M | 0.7 GB |
| 03 | gpt2 | 140 M | — | ✓ mit | 31.8 M | 1.1 GB |
| 04 | paraphrase-multilingual-MiniLM-L12-v2 | 120 M | 512 | ✓ apache-2.0 | 27.1 M | 1.0 GB |
| 05 | t5-small | 60 M | — | ✓ apache-2.0 | 21.6 M | 0.8 GB |
| 06 | Qwen3-0.6B | 750 M | 41 K | ✓ apache-2.0 | 20.7 M | 2.3 GB |
| 07 | all-mpnet-base-v2 | 110 M | 512 | ✓ apache-2.0 | 20.5 M | 1.0 GB |
| 08 | vit-base-patch16-224 | 90 M | — | ✓ apache-2.0 | 15.0 M | 0.9 GB |
| 09 | bge-reranker-v2-m3 | 570 M | 8 K | ✓ apache-2.0 | 14.8 M | 3.1 GB |
| 10 | mobilenetv3_small_100.lamb_in1k | 2.6 M | — | ✓ apache-2.0 | 12.7 M | 0.5 GB |
| 11 | Kokoro-82M | 82 M | — | ✓ apache-2.0 | 12.5 M | 0.7 GB |
| 12 | nomic-embed-text-v1.5 | 140 M | 2 K | ✓ apache-2.0 | 11.9 M | 1.1 GB |
| 13 | Florence-2-base | 230 M | — | ✓ mit | 11.7 M | 1.0 GB |
| 14 | multilingual-e5-small | 120 M | 512 | ✓ mit | 9.4 M | 1.0 GB |
| 15 | Qwen3-Embedding-0.6B | 600 M | 33 K | ✓ apache-2.0 | 9.1 M | 1.9 GB |
| 16 | paraphrase-multilingual-mpnet-base-v2 | 280 M | 512 | ✓ apache-2.0 | 9.1 M | 1.8 GB |
| 17 | audio.cpp-gguf | — | — | other | 8.9 M | 1.6 GB |
| 18 | bge-base-en-v1.5 | 110 M | 512 | ✓ mit | 8.3 M | 1.0 GB |
| 19 | bge-large-en-v1.5 | 340 M | 512 | ✓ mit | 8.2 M | 2.0 GB |
| 20 | Gender-Classifier-Mini | 93 M | — | ✓ apache-2.0 | 8.1 M | 1.7 GB |
| 21 | clap-htsat-fused | 150 M | — | ✓ apache-2.0 | 7.3 M | 1.2 GB |
| 22 | multilingual-e5-large | 560 M | 512 | ✓ mit | 7.1 M | 3.0 GB |
| 23 | granite-embedding-small-english-r2 | 50 M | 8 K | ✓ apache-2.0 | 6.9 M | 0.6 GB |
| 24 | Ornith-1.5-9B-GGUF | — | — | ✓ mit | 5.8 M | 6.9 GB |
| 25 | Unlimited-OCR | 3.3 B | 33 K | ✓ mit | 5.4 M | 15.7 GB |
| 26 | Qwen3.5-4B | 4.7 B | — | ✓ apache-2.0 | 5.3 M | 11.5 GB |
| 27 | whisper-large-v3-turbo | 810 M | — | ✓ mit | 5.2 M | 2.4 GB |
| 28 | Qwen2.5-1.5B-Instruct | 1.5 B | 33 K | ✓ apache-2.0 | 5.0 M | 4.1 GB |
| 29 | Ornith-1.0-9B-GGUF | — | — | ✓ mit | 4.9 M | 6.7 GB |
| 30 | multilingual-e5-base | 280 M | 512 | ✓ mit | 4.9 M | 1.8 GB |
| 31 | opt-125m | 125 M | 2 K | other | 4.7 M | 0.8 GB |
| 32 | roberta-base-go_emotions | 120 M | 512 | ✓ mit | 4.7 M | 1.1 GB |
| 33 | whisper-base | 70 M | — | ✓ apache-2.0 | 4.6 M | 0.8 GB |
| 34 | Qwen2.5-0.5B-Instruct | 490 M | 33 K | ✓ apache-2.0 | 4.5 M | 1.7 GB |
| 35 | all-MiniLM-L6-v2 | 20 M | 512 | ✓ apache-2.0 | 4.5 M | 0.5 GB |
| 36 | whisper-small | 240 M | — | ✓ apache-2.0 | 4.4 M | 1.6 GB |
| 37 | Qwen3-4B | 4.0 B | 41 K | ✓ apache-2.0 | 4.0 M | 10.0 GB |
| 38 | Huihui-Qwen3.8-27B-abliterated-GGUF | 27.0 B | — | ✓ apache-2.0 | 3.9 M | 16.5 GB |
| 39 | Qwen3-VL-4B-Instruct | 4.4 B | — | ✓ apache-2.0 | 3.7 M | 10.9 GB |
| 40 | Qwen3.5-2B | 2.3 B | — | ✓ apache-2.0 | 3.7 M | 5.8 GB |
| 41 | Qwen3-1.7B | 2.0 B | 41 K | ✓ apache-2.0 | 3.7 M | 5.3 GB |
| 42 | tf_efficientnetv2_s.in21k_ft_in1k | 20 M | — | ✓ apache-2.0 | 3.6 M | 0.6 GB |
| 43 | indonesian-roberta-base-posp-tagger | 120 M | 512 | ✓ mit | 3.6 M | 1.1 GB |
| 44 | snowflake-arctic-embed-l-v2.0 | 570 M | 8 K | ✓ apache-2.0 | 3.6 M | 3.1 GB |
| 45 | Qwen3.5-0.8B | 870 M | — | ✓ apache-2.0 | 3.5 M | 2.6 GB |
| 46 | OmniVoice | 610 M | — | unknown | 3.5 M | 4.2 GB |
| 47 | whisper-large-v3 | 1.5 B | — | ✓ apache-2.0 | 3.5 M | 10.9 GB |
| 48 | pythia-160m | 210 M | 2 K | ✓ apache-2.0 | 3.5 M | 0.9 GB |
| 49 | Bangla-twoclass-Sentiment-Analyzer | 280 M | 512 | ✓ mit | 3.4 M | 1.8 GB |
| 50 | finbert | 110 M | 512 | ✗ cc-by-nc-sa-4.0 | 3.3 M | 1.0 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.