NexaAI/embeddinggemma-300m-npu

EmbeddingGemma-300M (NPU)

Model Description

EmbeddingGemma is a 300M-parameter open embedding model developed by Google DeepMind.
It is built from Gemma 3 (with T5Gemma initialization) and the same research and technology used in Gemini models.

The model produces vector representations of text, making it well-suited for search, retrieval, classification, clustering, and semantic similarity tasks.
It was trained on 100+ languages with ~320B tokens, optimized for on-device efficiency (mobile, laptops, desktops).

Features

• Compact and efficient: 300M parameters, optimized for on-device use.
• Multilingual: trained on 100+ spoken languages.
• Flexible embeddings: default dimension 768, with support for 512, 256, 128 via Matryoshka Representation Learning (MRL).
• Wide task coverage: retrieval, QA, fact-checking, classification, clustering, similarity.
• Commercial-friendly: open weights available for research and production.

Use Cases

• Semantic similarity and recommendation systems
• Document, code, and web search
• Clustering for organization, research, and anomaly detection
• Classification (e.g., sentiment, spam detection)
• Fact verification and QA embeddings
• Code retrieval for programming assistance

Inputs and Outputs

Input:

• Type: Text string (e.g., query, prompt, document)
• Max Length: 2048 tokens

Output:

• Type: Embedding vector (default 768d)
• Options: 512 / 256 / 128 dimensions via truncation & re-normalization (MRL)

Limitations & Responsible Use

This model has known limitations:

• Bias & coverage: quality depends on training data diversity.
• Nuance & ambiguity: may struggle with sarcasm, figurative language.
• Ethical concerns: risk of bias perpetuation, privacy leakage, or malicious misuse.

Mitigations:

• CSAM and sensitive data filtering applied.
• Users should adhere to Gemma Responsible AI guidelines and Prohibited Use Policy.

License

• Licensed under Google’s Gemma Terms of Use.
• See: Gemma Terms

Ensure your usage complies with upstream license conditions.

References

• nexaSDK

Support

For SDK-related issues, visit sdk.nexa.ai.
For model-specific questions, open an issue in this repository.