EmbeddingGemma 2 BF16 — 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 — 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.