# SigLIP

> Google's sigmoid loss for image-language pretraining

- Category: [Foundation Models](https://ailandscape.org/category/foundation-models) › Embedding Models
- Homepage: https://github.com/google-research/big_vision
- Tags: embeddings, vision, multimodal, oss
- Added to the landscape: 2026-03-18

## Similar tools in Embedding Models

- [ALIGN](https://ailandscape.org/tool/align): Google's large-scale visual-language embedding model
- [BGE-M3](https://ailandscape.org/tool/bge-m3): Multi-lingual, multi-granularity embedding model by BAAI
- [CLIP](https://ailandscape.org/tool/clip): OpenAI's contrastive image-text embedding model
- [Cohere Embed](https://ailandscape.org/tool/cohere-embed): Cohere's multilingual text embedding models
- [E5-Mistral](https://ailandscape.org/tool/e5-mistral): Instruction-tuned Mistral-based text embeddings
- [ImageBind](https://ailandscape.org/tool/imagebind): Meta's unified embedding across 6 modalities
- [Jina Embeddings](https://ailandscape.org/tool/jina-embeddings): Long-context text embeddings with 8k token support
- [sentence-transformers](https://ailandscape.org/tool/sentence-transformers): Python framework for sentence embeddings

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Part of [AI Landscape](https://ailandscape.org), an open map of the AI ecosystem. Web page: https://ailandscape.org/tool/siglip · Index for AI assistants: https://ailandscape.org/llms.txt