1,054 models · refreshed nightly

Models that run on RTX 4070 · 16 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 410 text-to-image 153 ASR 92 image-text-to-text 89 sentence-similarity 61 feature-extraction 47 translation 47 text-classification 42 image-classification 34 token-classification 27 text-to-speech 12 audio-classification 11 object-detection 11 summarization 9 image-segmentation 9

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

620 models

#	Model	Params	Context	Commercial use	30d	On RTX 4070 · 16 GB
01	all-MiniLM-L6-v2 sentence-transformers · sentence-similarity	20 M	512	✓ apache-2.0	254.1 M	0.6 GB
02	bge-small-en-v1.5 BAAI · feature-extraction	30 M	512	✓ mit	64.5 M	0.7 GB
03	paraphrase-multilingual-MiniLM-L12-v2 sentence-transformers · sentence-similarity	120 M	512	✓ apache-2.0	45.9 M	1.0 GB
04	t5-small google-t5 · translation	60 M	—	✓ apache-2.0	24.9 M	0.8 GB
05	Qwen3-0.6B Qwen · text-generation	750 M	41 K	✓ apache-2.0	23.0 M	2.3 GB
06	all-mpnet-base-v2 sentence-transformers · sentence-similarity	110 M	512	✓ apache-2.0	22.6 M	1.0 GB
07	mobilenetv3_small_100.lamb_in1k timm · image-classification	<0.1 M	—	✓ apache-2.0	18.0 M	0.5 GB
08	bge-reranker-v2-m3 BAAI · text-classification	570 M	8 K	✓ apache-2.0	17.6 M	3.1 GB
09	gpt2 openai-community · text-generation	140 M	—	✓ mit	15.4 M	1.1 GB
10	nomic-embed-text-v1.5 nomic-ai · sentence-similarity	140 M	2 K	✓ apache-2.0	14.7 M	1.1 GB
11	Qwen3-Coder-30B-A3B-Instruct-GGUF unsloth · text-generation	—	—	✓ apache-2.0	12.7 M	12.9 GB
12	efficientnet_b3.ra2_in1k timm · image-classification	10 M	—	✓ apache-2.0	12.7 M	0.6 GB
13	multilingual-e5-small intfloat · sentence-similarity	120 M	512	✓ mit	12.3 M	1.0 GB
14	Kokoro-82M hexgrad · text-to-speech	82 M	—	✓ apache-2.0	11.6 M	0.7 GB
15	bge-large-en-v1.5 BAAI · feature-extraction	340 M	512	✓ mit	11.4 M	2.0 GB
16	bge-base-en-v1.5 BAAI · feature-extraction	110 M	512	✓ mit	10.5 M	1.0 GB
17	paraphrase-multilingual-mpnet-base-v2 sentence-transformers · sentence-similarity	280 M	512	✓ apache-2.0	9.9 M	1.8 GB
18	Qwen3-Embedding-0.6B Qwen · feature-extraction	600 M	33 K	✓ apache-2.0	8.6 M	1.9 GB
19	Qwen2.5-0.5B-Instruct Qwen · text-generation	490 M	33 K	✓ apache-2.0	8.5 M	1.7 GB
20	clap-htsat-fused laion · audio-classification	150 M	—	✓ apache-2.0	8.2 M	1.2 GB
21	multilingual-e5-base intfloat · sentence-similarity	280 M	512	✓ mit	7.6 M	1.8 GB
22	opt-125m facebook · text-generation	125 M	2 K	other	7.4 M	0.8 GB
23	Qwen2.5-1.5B-Instruct Qwen · text-generation	1.5 B	33 K	✓ apache-2.0	7.2 M	4.1 GB
24	vit-base-patch16-224 google · image-classification	90 M	—	✓ apache-2.0	7.2 M	0.9 GB
25	multilingual-e5-large intfloat · feature-extraction	560 M	512	✓ mit	7.2 M	3.0 GB
26	Qwen3-4B Qwen · text-generation	4.0 B	41 K	✓ apache-2.0	7.1 M	10.0 GB
27	Llama-3.2-1B-Instruct meta-llama · text-generation · gated	1.2 B	—	⚠ llama3.2	7.0 M	3.4 GB
28	Qwen3.5-4B Qwen · image-text-to-text	4.7 B	—	✓ apache-2.0	6.9 M	11.5 GB
29	whisper-large-v3-turbo openai · ASR	810 M	—	✓ mit	6.8 M	2.4 GB
30	granite-embedding-small-english-r2 ibm-granite · feature-extraction	50 M	8 K	✓ apache-2.0	6.3 M	0.6 GB
31	Ornith-1.5-9B-GGUF ornith-ai · text-generation	—	—	✓ mit	5.8 M	6.9 GB
32	bge-small-zh-v1.5 BAAI · feature-extraction	20 M	512	✓ mit	5.1 M	0.6 GB
33	Qwen2.5-3B-Instruct Qwen · text-generation	3.1 B	33 K	other	5.1 M	7.8 GB
34	Ornith-1.0-9B-GGUF deepreinforce-ai · text-generation	—	—	✓ mit	4.9 M	6.7 GB
35	Qwen3.5-2B Qwen · image-text-to-text	2.3 B	—	✓ apache-2.0	4.8 M	5.8 GB
36	whisper-large-v3 openai · ASR	1.5 B	—	✓ apache-2.0	4.7 M	10.9 GB
37	Prompt-Guard-86M meta-llama · text-classification · gated	280 M	—	⚠ llama3.1	4.4 M	1.8 GB
38	audio.cpp-gguf audio-cpp · text-to-speech	—	—	other	4.3 M	1.4 GB
39	bge-base-en-v1.5-course-recommender-v5 datasocietyco · sentence-similarity	110 M	512	unknown	4.2 M	1.0 GB
40	all-MiniLM-L12-v2 sentence-transformers · sentence-similarity	30 M	512	✓ apache-2.0	4.2 M	0.7 GB
41	bge-reranker-base BAAI · text-classification	280 M	512	✓ mit	4.0 M	1.8 GB
42	Qwen3-4B-Instruct-2507 Qwen · text-generation	4.0 B	262 K	✓ apache-2.0	4.0 M	10.0 GB
43	Qwen3-1.7B Qwen · text-generation	2.0 B	41 K	✓ apache-2.0	3.8 M	5.3 GB
44	Qwen3-VL-4B-Instruct Qwen · image-text-to-text	4.4 B	—	✓ apache-2.0	3.7 M	10.9 GB
45	distilbert-base-uncased-finetuned-sst-2-english distilbert · text-classification	70 M	512	✓ apache-2.0	3.7 M	0.8 GB
46	Kimi-K3-DSpark RadixArk · text-generation	2.3 B	1.0 M	unknown	3.6 M	5.8 GB
47	Qwen2.5-7B-Instruct-AWQ Qwen · text-generation	7.6 B	33 K	✓ apache-2.0	3.5 M	7.8 GB
48	NVIDIA-Nemotron-3-Nano-4B-BF16 nvidia · text-generation	4.0 B	262 K	other	3.5 M	9.8 GB
49	pythia-160m EleutherAI · text-generation	210 M	2 K	✓ apache-2.0	3.5 M	0.9 GB
50	bert-large-cased-finetuned-conll03-english dbmdz · token-classification	330 M	512	unknown	3.4 M	2.0 GB

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