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01

Providers + pricing

CapabilitiesProvider details
● Credits · billed by AnyRouter
cloudflare
cloudflare
$0.01
$0
● Free pool · donated keys · not available for this model — donate a key
02

Try it

POST /api/v1/embeddings
import OpenAI from "openai" const client = new OpenAI({  apiKey: process.env.ANYROUTER_API_KEY,  baseURL: "https://anyrouter.dev/api/v1",}) const resp = await client.embeddings.create({  model: "google/embeddinggemma-300m",  input: "The quick brown fox jumps over the lazy dog",})console.log(resp.data[0].embedding.slice(0, 8))
Set ANYROUTER_API_KEY · edits on the demo update this code
03

Uptime + latency

—recent checks · all routes

No health checks recorded for this model yet.

24h
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No uptime data yet

These providers haven't been health-probed for this model yet. The router still routes around upstreams that fail live requests — uptime fills in once probe history accrues.

EmbeddingGemma 300MDisabled since Aug 12, 2026

Smoke reported model_unavailable (no upstream for platform keys). See #1799/#1806.

  • cloudflare
Embedtext → [0.12, -0.4, …]768dimensions
Context
2K
Input
$0.01
Output
$0
TTFT
—
Uptime
—
Routes
1
04

Your access

Credits
Free poolnot in pool yetDonate key →
Create API key for this model
Embedding vectors
Vector dimensions768
Max input2,048 tokens
Price$0.012 / 1M tokens
Request parameters
inputmodelencoding_format
ArchitectureTransformer
Categoryembedding
ReleasedSep 4, 2025
Modalities
→
Capabilities
Embeddings are fixed-length vectors — compare them with cosine similarity for semantic search, RAG retrieval, clustering, and deduplication. Embed queries and documents with the same model, or the distances are meaningless.
05

About

EmbeddingGemma is a 300M parameter open embedding model from Google, built from Gemma 3 research. Produces text vectors for search, retrieval, classification, clustering, and semantic similarity across 100+ languages.

Released 2025-09-04 · params: input · model · encoding_format

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