Embeddinggemma 300M
Developed by Google, EmbeddingGemma 300M is an open-source embedding model that excels at producing vector representations of text, making it well-suited for search and retrieval tasks such as classification, clustering, and semantic similarity search. With a context window of 2,048 tokens, this model is notable for its ability to be deployed in resource-limited environments due to its relatively small size.
Input
Output
Context
2K
Max Output
-
Parameters
302.9M
Technical Specifications
Model TypeEmbedding
Context Window2,048 tokens
Max Output TokensNot available
Parameters302.9M
Release DateJul 17, 2025
Training CutoffNot available
Licensegemma
Open SourceYes
Input Modalities
Text
Output Modalities
Embedding
Capabilities
Estimated GPU Requirements for Embeddinggemma 300M
Estimates based on INT8 quantization. Actual requirements vary by framework and configuration.
Related Tools
Data sourced from official provider APIs and documentation
Last updated: Jun 23, 2026
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