gemini-embedding-001 API — pricing & specs

gemini-embedding-001 is a text-embedding model from Google DeepMind. On KeepRouter, gemini-embedding-001 costs $0.1500 per 1M input tokens and $0.6000 per 1M output tokens, billed pay-as-you-go with no monthly fee. Call it through a compatible KeepRouter endpoint supported by its active route, with the model id gemini-embedding-001.

MakerGoogle DeepMind
ModalityText embeddings
Input price$0.1500 per 1M tokens
Output price$0.6000 per 1M tokens
CapabilitiesText embeddings
EndpointPOST /v1/embeddings
Model idgemini-embedding-001

How pricing works for gemini-embedding-001

gemini-embedding-001 is billed per token — $0.1500 per 1M input tokens and $0.6000 per 1M output tokens. The published price is pay-as-you-go, with no monthly fee; actual request cost depends on measured token usage.

Calling gemini-embedding-001 on KeepRouter

Point a compatible client at the supported KeepRouter endpoint and set the model to gemini-embedding-001. KeepRouter preserves the client-facing request shape while handling upstream routing or translation. Send embedding requests to POST /v1/embeddings.

cURL

curl https://keeprouter.com/v1/embeddings \
  -H "Authorization: Bearer $KEEPROUTER_KEY" -H "Content-Type: application/json" \
  -d '{"model":"gemini-embedding-001","input":"The quick brown fox"}'

Python

import os
from openai import OpenAI
client = OpenAI(base_url="https://keeprouter.com/v1", api_key=os.environ["KEEPROUTER_KEY"])
e = client.embeddings.create(model="gemini-embedding-001", input="The quick brown fox")

JavaScript

const res = await fetch("https://keeprouter.com/v1/embeddings", {
  method: "POST",
  headers: { Authorization: "Bearer " + process.env.KEEPROUTER_KEY, "Content-Type": "application/json" },
  body: JSON.stringify({ model: "gemini-embedding-001", input: "The quick brown fox" }),
});

Estimate API costs

At the current KeepRouter customer price, an example workload of 1,000 total input tokens, no cached input, and 0 output tokens per request costs approximately $0.000150 per request. At 100 requests per day, that is $0.4500 over 30 days. This is a usage estimate, excluding processing fees, taxes, retries and application infrastructure. Actual usage, cache hits and supported generation durations need their own checks.

Adjust quantities in the API cost calculator.

How to evaluate gemini-embedding-001

gemini-embedding-001 is listed on KeepRouter as text embeddings under the exact id gemini-embedding-001. Use /v1/embeddings for the listed route; a maker's upstream features do not automatically apply to this gateway endpoint. No context limit is asserted here because the exact upstream limit has not been verified for this catalog entry.

First workload: Embed a small, labeled set of your own documents and queries; measure retrieval recall and index size before migrating the full corpus.

Before production: Keep query and document embeddings on the same model and version. Re-index after a model change rather than mixing incompatible vector spaces.

Public model usage evidence

No public, exact-variant usage figure has been verified for this KeepRouter model id. Missing data is not zero usage; family-level or maker-wide traffic is not presented as this model's traffic.

Published examples and cases

No exact-model customer case has been verified for this entry. The workload above is an evaluation recipe, not a claim of a public deployment.

Source and verification boundary

Official Google DeepMind website. KeepRouter's live catalog is authoritative for the customer price and enabled endpoint shown here; the maker remains authoritative for upstream model capabilities and limits.

Pricing and implementation guides

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