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embeddinggemma-300m

EmbeddingGemma is a 300M parameter, state-of-the-art for its size, open embedding model from Google, built from Gemma 3 (with T5Gemma initialization) and the same research and technology used to create Gemini models. EmbeddingGemma produces vector representations of text, making it well-suited for search and retrieval tasks, including classification, clustering, and semantic similarity search. This model was trained with data in 100+ spoken languages.

Best for

EmbeddingsSemantic Search
Context Window
Input Cost
Free
Output Cost
Latency p50

Pricing Details

Standard PricingFree tier
Input (per 1M tokens)
$0.00
Output (per 1M tokens)
$0.00

Hallucination Score™ (est.)

Community reliability estimate · not official

Not yet rated

About this score: Community-estimated based on user reports and publicly available benchmark data (e.g. TruthfulQA). This is not an official score from the model provider. Scores may be inaccurate — always verify with the official leaderboard before making production decisions.

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Provider

google

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