Workers AI - EmbeddingGemma 2 now available on Workers AI

@cf/google/embeddinggemma-2 is now available on Workers AI. EmbeddingGemma 2 is an open multimodal embedding model from Google DeepMind. It maps text (including code), images, video, and audio into a single 768-dimensional vector space, so you can search a mixed collection of products, documents, and media with one text query.

Key capabilities:

• Multimodal: Embed text, images, video, audio, or any combination of them in one input. Every embedding shares the same vector space.
• Multilingual and code: Understands more than 100 languages and improves code retrieval over the original EmbeddingGemma.
• Flexible dimensions: Set dimensions to 128, 256, or 512 to return shorter vectors and reduce storage, with a small cost to quality.
• Long context: An 8,192 token context window, shared across all content in an input.
• Task prefixes: Add short instructions such as task: search result | query: ... to tune embeddings for search, classification, clustering, or similarity.

Send text with input. Send images, video, and audio as base64 data URIs in messages:

const response = await env.AI.run("@cf/google/embeddinggemma-2", {
	messages: [
		[
			{
				role: "user",
				content: [
					{ type: "text", text: "Waterproof running shoes." },
					{ type: "image_url", image_url: { url: imageDataUri } },
				],
			},
		],
		[
			{
				role: "user",
				content:
					"task: search result | query: waterproof shoes for trail running",
			},
		],
	],
});

const response = await env.AI.run("@cf/google/embeddinggemma-2", {
	messages: [
		[
			{
				role: "user",
				content: [
					{ type: "text", text: "Waterproof running shoes." },
					{ type: "image_url", image_url: { url: imageDataUri } },
				],
			},
		],
		[
			{
				role: "user",
				content:
					"task: search result | query: waterproof shoes for trail running",
			},
		],
	],
});

Pricing is $0.0017 per million input tokens.

For more information, refer to the EmbeddingGemma 2 model page and pricing.