Google / EMBEDDINGS

embeddinggemma-300m

A compact multilingual embedding model for semantic retrieval and similarity, rather than answer generation.

Source reviewed 2026-10-24 · AiBrainWorX editorial summary

Creator: Google
Parameters: 300M
Context: Task-specific; see the reviewed source and runtime
License: gemma

01 / CAPABILITIES

What it is built for

Vector representations
External task-specific runtime; not integrated into launcher chat

Inputs: Text → vectors

Runtime limits and on-device memory must be validated separately.

02 / ON YOUR MACHINE

Very small model / edge candidate; runtime validation required

Embedding output is a vector. This launcher’s chat and project memory do not automatically use it.

Launcher integration

External task-specific runtime; not integrated into launcher chat

Runtime and training workflow

Sentence Transformers · Compatible edge embedding runtime

Separate embedding fine-tuning. Training suitability requires exact checkpoint format and prepared data; a catalog entry is not a completed training test.

Compare dataset preparation guides →

03 / WHAT IS VERIFIED

Evidence, with context

Our test status

Source reviewed only. No local model or Android inference test performed.

We have not added a benchmark number without documenting its test conditions. A model-card capability is not a measured speed or quality guarantee on your hardware.

04 / OWNERSHIP & USE

gemma

Gemma terms apply; review and accept access conditions yourself. No weights or license acceptance are bundled.

AiBrainWorX authors this profile and the launcher. Google remains the model’s creator. Models are not rebranded as our own weights.

05 / GO DEEPER

Original sources & model files

This page is our concise summary, not a mirror of the full upstream card. Review the original documentation and exact artifact before downloading.

Official card on Hugging Face ↗Files & versions ↗Reviewed card revision ↗

Reviewed revision: 57c266a740f5 · Specifications may change after the review date.