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1,423 models · 1,213 open weights · 210 API-only · refreshed nightly

Feature extraction models

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.

Type
All 1,423 Open weights (self-host) 1,213 API-only 210
Task
All text-generation 735 text-to-image 165 image-text-to-text 110 ASR 82 sentence-similarity 63 text-classification 50 translation 50 feature-extraction 46 image-classification 41 text-to-speech 23 token-classification 22 summarization 9 audio-classification 9 image-segmentation 9 object-detection 7 audio-text-to-text 1 any-to-any 1
Runs on
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
Licence
Size
$
46 models
#ModelParamsContextCommercial use30dMin VRAM
01 bge-small-en-v1.5 BAAI · feature-extraction Open weights 30 M 512 ✓ mit 47.6 M from 0.7 GB
02 Qwen3-Embedding-0.6B Qwen · feature-extraction Open weights 600 M 33 K ✓ apache-2.0 9.1 M from 1.9 GB
03 bge-base-en-v1.5 BAAI · feature-extraction Open weights 110 M 512 ✓ mit 8.3 M from 1.0 GB
04 bge-large-en-v1.5 BAAI · feature-extraction Open weights 340 M 512 ✓ mit 8.2 M from 2.0 GB
05 multilingual-e5-large intfloat · feature-extraction Open weights 560 M 512 ✓ mit 7.1 M from 3.0 GB
06 granite-embedding-small-english-r2 ibm-granite · feature-extraction Open weights 50 M 8 K ✓ apache-2.0 6.9 M from 0.6 GB
07 all-MiniLM-L6-v2 Xenova · feature-extraction Open weights 20 M 512 ✓ apache-2.0 4.5 M from 0.5 GB
08 bge-small-zh-v1.5 BAAI · feature-extraction Open weights 20 M 512 ✓ mit 3.1 M from 0.6 GB
09 bge-base-en BAAI · feature-extraction Open weights 110 M 512 ✓ mit 2.7 M from 1.0 GB
10 bge-base-en-v1.5 Xenova · feature-extraction Open weights 110 M 512 ✓ mit 2.5 M from 0.8 GB
11 Qwen3-Embedding-4B Qwen · feature-extraction Open weights 4.0 B 41 K ✓ apache-2.0 2.5 M from 10.0 GB
12 Qwen3-Embedding-8B Qwen · feature-extraction Open weights 7.6 B 41 K ✓ apache-2.0 2.4 M from 18.3 GB
13 mxbai-embed-large-v1 mixedbread-ai · feature-extraction Open weights 340 M 512 ✓ apache-2.0 2.3 M from 1.3 GB
14 bge-reranker-large BAAI · feature-extraction Open weights 560 M 512 ✓ mit 2.0 M from 3.0 GB
15 multilingual-e5-large-instruct intfloat · feature-extraction Open weights 560 M 512 ✓ mit 1.7 M from 1.8 GB
16 jina-embeddings-v3 jinaai · feature-extraction Open weights 570 M 8 K ✗ cc-by-nc-4.0 1.5 M from 1.8 GB
17 SapBERT-from-PubMedBERT-fulltext cambridgeltl · feature-extraction Open weights 110 M 512 ✓ apache-2.0 1.4 M from 1.0 GB
18 wavlm-large microsoft · feature-extraction Open weights — — unknown 1.4 M —
19 w2v-bert-2.0 facebook · feature-extraction Open weights 580 M — ✓ mit 1.3 M from 3.1 GB
20 jina-embeddings-v2-small-en jinaai · feature-extraction Open weights 30 M 8 K ✓ apache-2.0 1.3 M from 0.6 GB
21 jina-embeddings-v5-omni-small jinaai · feature-extraction Open weights 1.6 B — ✗ cc-by-nc-4.0 1.0 M from 4.5 GB
22 UAE-Large-V1 WhereIsAI · feature-extraction Open weights 340 M 512 ✓ mit 1.0 M from 2.0 GB
23 1 unslothai · feature-extraction Open weights — 2 K unknown 963 K from 0.5 GB
24 clap-htsat-unfused laion · feature-extraction Open weights — — ✓ apache-2.0 954 K —
25 bge-small-en-v1.5 Xenova · feature-extraction Open weights 30 M 512 unknown 855 K from 0.6 GB
26 repeat unslothai · feature-extraction Open weights — — unknown 812 K from 0.5 GB
27 FRIDA ai-forever · feature-extraction Open weights 823 M — ✓ mit 698 K from 4.2 GB
28 specter2_base allenai · feature-extraction Open weights — 512 ✓ apache-2.0 662 K —
29 bge-small-en-v1.5 michaelfeil · feature-extraction Open weights 30 M 512 ✓ mit 599 K from 0.7 GB
30 embeddinggemma-2-ONNX onnx-community · feature-extraction Open weights 744 M — ✓ apache-2.0 531 K from 2.2 GB
31 conv-bert-base YituTech · feature-extraction Open weights — 512 unknown 521 K —
32 jina-embeddings-v5-text-nano jinaai · feature-extraction Open weights 210 M 8 K ✗ cc-by-nc-4.0 515 K from 1.1 GB
33 deepset-mxbai-embed-de-large-v1 mixedbread-ai · feature-extraction Open weights 487 M 512 ✓ apache-2.0 504 K from 1.6 GB
34 hubert-base-ls960 facebook · feature-extraction Open weights — — ✓ apache-2.0 496 K —
35 embeddinggemma-2 google · feature-extraction Open weights 744 M — ✓ apache-2.0 475 K from 2.2 GB
36 sentence-bert-base-ja-mean-tokens-v2 sonoisa · feature-extraction Open weights 110 M 512 cc-by-sa-4.0 474 K from 1.0 GB
37 bge-small-en-v1.5 unsloth · feature-extraction Open weights 33 M 512 ✓ mit 470 K from 0.7 GB
38 pplx-embed-v1-0.6b perplexity-ai · feature-extraction Open weights 600 M 33 K ✓ mit 461 K from 3.2 GB
39 mimi kyutai · feature-extraction Open weights 100 M 8 K ✓ cc-by-4.0 458 K from 0.9 GB
40 multilingual-e5-small Xenova · feature-extraction Open weights 120 M 512 unknown 456 K from 0.8 GB
41 MedCPT-Query-Encoder ncbi · feature-extraction Open weights 110 M 512 other 454 K from 1.0 GB
42 vram-16 unslothai · feature-extraction Open weights — — unknown 432 K from 0.5 GB
43 lambda unslothai · feature-extraction Open weights — — unknown 428 K from 0.5 GB
44 efficient-splade-VI-BT-large-doc naver · feature-extraction Open weights — 512 ✗ cc-by-nc-sa-4.0 427 K from 0.5 GB
45 llama2-embedding-1b-8k mesolitica · feature-extraction Open weights 947 M 33 K unknown 416 K from 4.8 GB
46 wavlm-base-plus microsoft · feature-extraction Open weights — — unknown 396 K —
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.