google/siglip-so400m-patch14-384
Primitive: /encode · Encode ·
SigLIP
SigLIP model pre-trained on WebLi at resolution 384x384. It was introduced in the paper Sigmoid Loss for Language Image Pre-Training by Zhai et al. and first released in this repository.
MultimodalDense
View on Hugging Face → Guide: SigLIP so400m reference →
Overview
Hardware: — drives latency, throughput & cost
| Size | 878M params |
|---|---|
| Tasks | /encode |
| License | apache-2.0 |
| Latency | 347 ms |
| Throughput | 451 tok/s |
| Cost | $0.493 /1M tok |
Cost is approximate — computed from list GPU prices; your actual price depends on the provider you deploy SIE with.
Embedding
| Output types | Dense |
|---|---|
| Dimensions | dense: 1,152 |
| Max sequence length | 64 |
| Inputs | text · image |
Benchmarks
Flickr30kI2TRetrieval
Image-to-text retrieval: retrieve captions from images
Corpus: 31,783 Queries: 1,000
Quality
ndcg at 10 0.9001
map at 10 0.8365
mrr at 10 0.9663
Performance L4-SPOT b1 c8
Corpus 202 tok/s
Corpus p50 523.6ms
Query 9.7 img/s
Query p50 711.3ms
Performance L4 b1 c16
Corpus 700 tok/s
Corpus p50 170.9ms
Query 7.3 mpix/s
Query p50 197.2ms
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