models

Google: Gemini Embedding 001

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Google: Gemini Embedding 001

Text or token-ID input to vectors, with float encoding and a listed 20,000-token hosted context.

About the model

This description covers the model’s capabilities. Available in Ailoot inputs, outputs and options are listed for the selected method below.

google/gemini-embedding-001 represents text as vectors for retrieval. A practical use is finding the relevant technical passage when a question uses different wording from the document. The Ailoot route lists a 20,000-token hosted context and accepts text strings, string arrays or token-ID arrays, using one consistent input kind per request.

The result contains indexed finite-float vectors. The accepted contract does not publish a default vector width and explicitly excludes a dimensions override; establish your index width from the actual returned vector length and keep it fixed for that index. encoding_format supports float. No task-type or query/document selector is exposed on this route. Use a consistent preparation convention for questions and documents, and keep the exact model and vector width together when building or updating the index.

Ailoot Ultra · Embeddings POST /v1/embeddings google/gemini-embedding-001

google/gemini-embedding-001

Google /google/gemini-embedding-001

Overview

Text or token-ID input to vectors, with float encoding and a listed 20,000-token hosted context.

Accepted inputs
Text · token_ids
Results
embedding

Available in Ailoot · inputs & methods

Ailoot Ultra · Embeddings POST /v1/embeddings
Input types
text, token_ids
Output types
embedding
Context
20,000 tokens
Output format
json
FieldTypeRequirementValues & limitsDefault
FieldmodelTypestringRequirementRequiredValues & limits
google/gemini-embedding-001
Default—
FieldinputTypestring|string[]|integer[]|integer[][]RequirementRequiredValues & limits
Minimum items: 1
Conditions: Nonempty homogeneous batch. Token IDs are nonnegative integers.
Input budget: Maximum: 20,000 · Text unit: UTF8 bytes · Token unit: token-array elements
Default—
Fieldencoding_formatTypestringRequirementOptionalValues & limits
float
Defaultfloat
FielddimensionsTypeintegerRequirementNot supportedValues & limits
Minimum: 1
Default—
FielduserTypejson_valueRequirementOptionalValues & limits
Conditions: Source allows this JSON metadata field; exact upstream semantics are model-specific.
Default—
Fieldsession_idTypejson_valueRequirementOptionalValues & limits
Conditions: Source allows this JSON metadata field; exact upstream semantics are model-specific.
Default—
FieldtraceTypejson_valueRequirementOptionalValues & limits
Conditions: Source allows this JSON metadata field; exact upstream semantics are model-specific.
Default—
FieldproviderTypeobjectRequirementOptionalValues & limits
Conditions: provider.options rejected
Default—
Input material combinations

text_to_embedding

Method parameters and lifecycle
ParameterContract
Parametercontent_typeContractapplication/json
ParameterrequiredContractmodel, input
Parameterinput_shapesContractstring, string[], nonnegative_integer_token_array, nonnegative_integer_token_array[]
Parameterencoding_formatContractfloat
Parameterdimensions_overrideContractfalse
Parametermax_input_budget_unitsContract20000
Parametermultimodal_objectsContractfalse
Parametermaterial_typesContracttext, token_ids

Lifecycle: synchronous_json

Keep every vector index and dimension.

Multimodal model name does not admit image objects on this exact path.

Pricing

Tariff references do not add request options. Supported parameters are listed for the selected method.

Fast mode
Standard rate When fast mode is selected
Flex mode
Standard rate When flex mode is selected
Maximum reasoning effort
Standard rate When maximum reasoning effort uses the default adjustment

Ailoot rates

Prices by configuration

ConfigurationRate scheduleCharge
ConfigurationBase token ratesRate scheduleBase rateCharge
Input · Input tokens $0.0003 / 1K tokens
Output · Output tokens $0 / 1K tokens
Input · Cache read — / 1K tokens
Input · Cache write — / 1K tokens
Input · Cache write, 1 hour — / 1K tokens

Ailoot reserves an estimated amount before a request. After the result, it settles the final charge from measured usage. Streaming settlement uses the final usage record. How reservation and settlement work →

Example requests

Ailoot Ultra · Embeddings

curlPython SDK
set -eu
: "${AILOOT_API_KEY:?Set your Ailoot API key}"
python3 - <<'PY_REQUEST'
import json,os
from pathlib import Path
p=json.loads('{"model": "google/gemini-embedding-001", "input": ["First document", "Second document"]}')

Path("request.json").write_text(json.dumps(p,ensure_ascii=False))
PY_REQUEST
curl --fail-with-body --silent --show-error https://api.ailoot.ai/v1/embeddings \
  -H "Authorization: Bearer $AILOOT_API_KEY" -H 'Content-Type: application/json' \
  --data-binary @request.json -D response-headers.txt -o result.json
python3 - <<'PY_RESULT'
import json
from pathlib import Path
r=json.loads(Path("result.json").read_text())
for x in r.get("data",[]): print(json.dumps({"index":x.get("index"),"embedding":x.get("embedding")}))
PY_RESULT
from openai import OpenAI
import os

client=OpenAI(base_url="https://api.ailoot.ai/v1",api_key=os.environ["AILOOT_API_KEY"],max_retries=0)
result=client.embeddings.create(model='google/gemini-embedding-001',input=["First document","Second document"])
print(result)
for item in result.data:print(item.index,item.embedding)

Receive and save results

Ailoot Ultra · Embeddings

json

Keep all completed results

Keep every complete returned response, file and content part.

Keep every vector with its index. Vector count must equal input count; dimensions must be consistent.

If the original response needs checking

No embedding job endpoint is introduced.

Response fields
FieldType
FieldobjectTypestring
FieldmodelTypestring
Fielddata[].indexTypeinteger
Fielddata[].embeddingTypefinite float[]
FieldusageTypeobject
Errors and next steps
ResponseConditionNext step
Response400 · invalid_request_errorConditionInvalid required fields, material representation or parameter valueNext stepCorrect the indicated fields before a new creation request.

Aliases

Model aliases

Ailoot Ultra google/gemini-embedding-001

Method path aliases

Use the method paths shown above.

Related caller IDs

google/gemini-embedding-001

FAQ · Google: Gemini Embedding 001
What inputs and results are available?

POST /v1/embeddings · google/gemini-embedding-001: text, token_ids → embedding

Which fields does the request use?

POST /v1/embeddings · google/gemini-embedding-001: model, input, encoding_format, provider

What limits apply?

POST /v1/embeddings · google/gemini-embedding-001: ctx: 20000; input.budget.maximum: 20000 (UTF8 bytes); input.min_items: 1

More details

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