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EmbeddingGemma 2

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EmbeddingGemma 2 is Google's open embedding model, published October 6, 2026 under the Apache 2.0 license.

Provider

Google

Model family

Gemma

Multimodal embedding model

Cost tier

Embedding

Status

Current

Release Oct 6, 2026

Why teams choose it

🧠

Text-only use can drop the vision and audio encoders and run the 270M text encoder.

📎

Quantized on-device RAM cited on the post is about 191MB for text-only and about 567MB

for the full model on Pixel 11 Pro.

Tradeoffs to know

  • Not a chat or image-generation model, and not a Gemini API model ID.
  • Model Garden availability was still listed as coming soon on the launch post.
  • The MTEB Code score on the launch post is vendor-reported.

Technical specs

Inputs
text, image, video, audio
Outputs
embedding
Capabilities
Text, image, video, and audio embeddings, 768-dimension vectors, truncatable to 512, 256, or 128, 8,000-token context, Apache 2.0 weights on Hugging Face and Kaggle
License
Apache 2.0
Context tokens
8,000
Parameters Text
270M
Parameters Audio
300M
Parameters Total
740M
Parameters Vision
170M
Embedding Dimensions
768, 512, 256, 128

Benchmarks

Mteb Code (vendor-reported)
78.68
Mteb Code Previous (vendor-reported)
68.76

Related models

EmbeddingGemma 2 FAQ

What is EmbeddingGemma 2?

0 license. It is not a generative Gemini API model. The launch post says it has 740 million parameters: a 270 million text encoder, an optional 170 million vision encoder, and a 300 million audio encoder. Embeddings are 768 dimensions and can be truncated to 512, 256, or 128. Context is 8,000 tokens, four times EmbeddingGemma 1. 5 minutes of audio, 29 images, or 58 video frames, and that the text-only configuration can run at 270 million parameters. Weights are on Hugging Face and Kaggle. Google says a Model Garden listing is coming soon. 68.

When does EmbeddingGemma 2 fit best?

On-device and open-weight search, clustering, and retrieval

What should teams watch out for with EmbeddingGemma 2?

Not a chat or image-generation model, and not a Gemini API model ID.

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