1,011 models · refreshed nightly

Models that run on Mac M3 · 24 GB

Every model in the catalog with its licence, estimated VRAM and daily-tracked downloads. Filters update the URL — share any view.

All text-generation 400 text-to-image 150 ASR 89 image-text-to-text 82 sentence-similarity 55 feature-extraction 47 translation 44 text-classification 39 image-classification 32 token-classification 22 text-to-speech 16 audio-classification 12 image-segmentation 8 object-detection 8 summarization 7

Any RTX 3060 · 12 GB RTX 4070 · 16 GB RTX 4090 · 24 GB 2 × 24 GB Mac M3 · 24 GB Mac M4 Max · 64 GB

571 models

#	Model	Params	Context	Commercial use	30d	On Mac M3 · 24 GB
01	all-MiniLM-L6-v2 sentence-transformers · sentence-similarity	20 M	512	✓ apache-2.0	257.8 M	0.6 GB
02	bge-small-en-v1.5 BAAI · feature-extraction	30 M	512	✓ mit	72.4 M	0.7 GB
03	paraphrase-multilingual-MiniLM-L12-v2 sentence-transformers · sentence-similarity	120 M	512	✓ apache-2.0	59.4 M	1.0 GB
04	Qwen3-0.6B Qwen · text-generation	750 M	41 K	✓ apache-2.0	29.7 M	2.3 GB
05	all-mpnet-base-v2 sentence-transformers · sentence-similarity	110 M	512	✓ apache-2.0	25.2 M	1.0 GB
06	t5-small google-t5 · translation	60 M	—	✓ apache-2.0	24.7 M	0.8 GB
07	bge-reranker-v2-m3 BAAI · text-classification	570 M	8 K	✓ apache-2.0	19.2 M	3.1 GB
08	mobilenetv3_small_100.lamb_in1k timm · image-classification	0 M	—	✓ apache-2.0	18.5 M	0.5 GB
09	nomic-embed-text-v1.5 nomic-ai · sentence-similarity	140 M	2 K	✓ apache-2.0	15.7 M	1.1 GB
10	multilingual-e5-small intfloat · sentence-similarity	120 M	512	✓ mit	15.6 M	1.0 GB
11	Qwen2.5-1.5B-Instruct Qwen · text-generation	1.5 B	33 K	✓ apache-2.0	14.0 M	4.1 GB
12	gpt2 openai-community · text-generation	140 M	—	✓ mit	13.7 M	1.1 GB
13	bge-large-en-v1.5 BAAI · feature-extraction	340 M	512	✓ mit	13.1 M	2.0 GB
14	paraphrase-multilingual-mpnet-base-v2 sentence-transformers · sentence-similarity	280 M	512	✓ apache-2.0	11.5 M	1.8 GB
15	Llama-3.2-1B-Instruct meta-llama · text-generation · gated	1.2 B	—	⚠ llama3.2	10.4 M	3.4 GB
16	bge-base-en-v1.5 BAAI · feature-extraction	110 M	512	✓ mit	10.0 M	1.0 GB
17	Qwen3-Embedding-0.6B Qwen · feature-extraction	600 M	33 K	✓ apache-2.0	9.8 M	1.9 GB
18	whisper-large-v3-turbo openai · ASR	810 M	—	✓ mit	8.7 M	2.4 GB
19	Qwen2.5-VL-3B-Instruct Qwen · image-text-to-text	3.8 B	128 K	unknown	8.2 M	9.3 GB
20	Qwen3-1.7B Qwen · text-generation	2.0 B	41 K	✓ apache-2.0	7.8 M	5.3 GB
21	multilingual-e5-large intfloat · feature-extraction	560 M	512	✓ mit	7.5 M	3.0 GB
22	multilingual-e5-base intfloat · sentence-similarity	280 M	512	✓ mit	7.2 M	1.8 GB
23	clap-htsat-fused laion · audio-classification	150 M	—	✓ apache-2.0	6.9 M	1.2 GB
24	Qwen3.5-4B Qwen · image-text-to-text	4.7 B	—	✓ apache-2.0	6.7 M	11.5 GB
25	Qwen2.5-0.5B-Instruct Qwen · text-generation	490 M	33 K	✓ apache-2.0	6.6 M	1.7 GB
26	Qwen2.5-3B-Instruct Qwen · text-generation	3.1 B	33 K	other	6.0 M	7.8 GB
27	whisper-large-v3 openai · ASR	1.5 B	—	✓ apache-2.0	5.5 M	10.9 GB
28	nsfw_image_detection Falconsai · image-classification	90 M	—	✓ apache-2.0	5.4 M	0.9 GB
29	nomic-embed-text-v1 nomic-ai · sentence-similarity	140 M	8 K	✓ apache-2.0	5.1 M	1.1 GB
30	Ornith-1.0-9B-GGUF deepreinforce-ai · text-generation	—	—	✓ mit	4.9 M	6.7 GB
31	Ornith-1.0-9B-GGUF ornith-ai · text-generation	—	—	✓ mit	4.9 M	6.7 GB
32	mxbai-embed-large-v1 mixedbread-ai · feature-extraction	340 M	512	✓ apache-2.0	4.9 M	1.3 GB
33	whisper-base openai · ASR	70 M	—	✓ apache-2.0	4.8 M	0.8 GB
34	bge-small-zh-v1.5 BAAI · feature-extraction	20 M	512	✓ mit	4.8 M	0.6 GB
35	gemma-3-1b-it google · text-generation · gated	1.0 B	—	⚠ gemma	4.7 M	2.8 GB
36	Qwen3-Coder-30B-A3B-Instruct-GGUF unsloth · text-generation	—	—	✓ apache-2.0	4.7 M	12.9 GB
37	vit-base-patch16-224 google · image-classification	90 M	—	✓ apache-2.0	4.7 M	0.9 GB
38	Qwen2.5-7B-Instruct-AWQ Qwen · text-generation	7.6 B	33 K	✓ apache-2.0	4.6 M	7.8 GB
39	Qwen3-4B Qwen · text-generation	4.0 B	41 K	✓ apache-2.0	4.6 M	10.0 GB
40	bge-reranker-base BAAI · text-classification	280 M	512	✓ mit	4.6 M	1.8 GB
41	Prompt-Guard-86M meta-llama · text-classification · gated	280 M	—	⚠ llama3.1	4.5 M	1.8 GB
42	Qwen3-ASR-0.6B Qwen · ASR	940 M	—	✓ apache-2.0	4.3 M	2.7 GB
43	Qwen3-VL-4B-Instruct Qwen · image-text-to-text	4.4 B	—	✓ apache-2.0	4.0 M	10.9 GB
44	granite-embedding-small-english-r2 ibm-granite · feature-extraction	50 M	8 K	✓ apache-2.0	3.8 M	0.6 GB
45	GLM-OCR zai-org · image-text-to-text	1.3 B	—	✓ mit	3.8 M	3.6 GB
46	distilbert-base-uncased-finetuned-sst-2-english distilbert · text-classification	70 M	512	✓ apache-2.0	3.7 M	0.8 GB
47	all-MiniLM-L12-v2 sentence-transformers · sentence-similarity	30 M	512	✓ apache-2.0	3.5 M	0.7 GB
48	Qwen3-Embedding-4B Qwen · feature-extraction	4.0 B	41 K	✓ apache-2.0	3.4 M	10.0 GB
49	jina-embeddings-v3 jinaai · feature-extraction	570 M	8 K	✗ cc-by-nc-4.0	3.2 M	1.8 GB
50	Qwen3-4B-Instruct-2507 Qwen · text-generation	4.0 B	262 K	✓ apache-2.0	3.2 M	10.0 GB

VRAM figures are estimates for the smallest available quantization at 8K context — see /methodology. Downloads refresh nightly from the Hugging Face API.