Unverified50% confidenceFactExact time
EmbeddingGemma 2 is based on the Gemma 3 decoder architecture, shares the text tokenizer and audio encoder with Gemma 3, has a context window of 8K tokens (4 times that of the previous generation), and outputs vectors with a dimension of 768.
1
Sources
50%
Confidence
Long-term
Relevance
10/7/2026
First Seen
Sources
Related Entities
Related Claims
UnverifiedEmbeddingGemma 2 is built on Gemma 4 and shares its text tokenizer and audio encoder, enabling both models to run simultaneously within a unified pipeline with lower total memory usage.78% similarUnverifiedGemma 4省去了传统编码器结构，使小尺寸模型能在消费级显卡上运行深度思考任务68% similarUnverifiedGemma 3 is an open-source multimodal language model series released by Google DeepMind that can process both text and image inputs.65% similarUnverifiedWisprGemma 使用单个 Gemma E2B 模型在单次推理中完成语音识别、文本清理和重写62% similarUnverifiedEmbeddingGemma 2 adopts a modular design, requiring a minimum of 270 million parameters for text-only tasks, with a 170 million parameter visual encoder and a 300 million parameter audio encoder available as optional components that can be enabled on demand.61% similar
Cite This Claim
Stable URI
https://kongchang.com/claim/985562API
curl https://kongchang.com/api/v1/knowledge/claims/985562MCP
get_claim(id=985562)