EmbeddingGemma 2 BF16 β€” radiance container

google/embeddinggemma-2 in bf16, exactly as the checkpoint ships it, as a single .rad container for the radiance inference engine. It embeds text, images, video and audio on an AMD card (RDNA4, ROCm) or on the CPU.

File embeddinggemma2-bf16.rad β€” 1.40 GiB
Weights every weight of the model, the vision and audio towers included, bf16 as the checkpoint ships it
Output 768-dimensional vectors, mean-pooled and normalised as the model's sentence-transformers configuration states
Modalities text, image, video, audio
Needs radiance 1.5.0 or newer

Serve

radiance --model embeddinggemma2-bf16.rad --host 0.0.0.0 --port 8000

With no card visible, radiance serves it on the CPU. The Docker image is stilldeadcode/radiance. Requests go to /v1/embeddings. input is a string, a list of strings, or content parts:

{"input": [{"type": "image_url", "image_url": {"url": "data:image/png;base64,..."}},
           {"type": "text", "text": "a red square"}]}

Video is a video_url part, and audio an input_audio part ({"data": <base64 wav>, "format": "wav"}). prompt_name applies one of the model's named prompts (query, document, Retrieval-query, ...), dimensions truncates the vector and normalises it again, and image_tokens (70, 140, 280, 560 or 1120) sets an image's token budget.

Accuracy

Cosine similarity against the Hugging Face transformers reference in bf16, served by radiance 1.5.0:

input R9700 CPU
text, 4 to 6,704 tokens 0.99992 – 0.99997 0.99990 – 0.99998
images 0.99998 – 0.99999 0.99998 – 0.99999
video 0.99997 0.99997
audio (7 s, 30 s) 0.99992 – 0.99993 0.99974 (7 s)
text + image 0.99997 0.99996

A text that itself begins with the literal string <bos> scores 0.998: radiance does not add a second <bos> in front of it, where the reference does.

Speed

On one Radeon AI PRO R9700 (gfx1201): about 148,000 text tokens a second in batches; 27 images a second one at a time and 52 at eight in parallel; a 7 s audio clip in 20 ms and a 30 s clip in 49 ms. On a Ryzen 9 9950X3D: about 12,000 text tokens a second, 2.3 images a second, and a 30 s audio clip in 265 ms.

How this file was made

rad-convert google/embeddinggemma-2 -o embeddinggemma2-bf16.rad

No recipe: every weight is the checkpoint's own.

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