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Model infoModelsSnapshot: 15 Oct 2026

Google / Gemini Embedding

Gemini Embedding 001

Embeddings model offered through the Gemini API.

availableClosed weightsEmbeddings
Official documentation (opens in a new tab)Reviewed 14 Oct 2026
8 of 19 specification fields collected
Input token limit2K2,048 tokens
Vector dimensions128–3,072See specification notes below
Input billingNot collectedGoogle Gemini API
Output billingNot collectedNo inferred price

Specifications

Provider-documented facts. “Not collected” means we have not verified that field yet, not that the feature is unsupported.

Input token limit
2,048 tokensSource for Input token limit (opens in a new tab)

Provider input-token limit.

Maximum output
Not collected
Output modalities
EmbeddingsSource for Output modalities (opens in a new tab)

Text embeddings

Reasoning
Not collected
Tool calling
Not collected
Structured output
Not collected
Streaming
Not collected
Batch processing
SupportedSource for Batch processing (opens in a new tab)

Supported on Enterprise; does not establish batch access on every host.

Fine-tuning
Not collected
Knowledge cutoff
Not collected
Parameters
Not collected
Architecture
Not collected
Languages
Not collected
Embedding dimensions
128–3,072Source for Embedding dimensions (opens in a new tab)

Flexible vector dimensions; recommended sizes are 768, 1,536 and 3,072.

Model card updated
June 2025Source for Model card updated (opens in a new tab)

Card update month, not a release date.

Context caching
Not collected

See endpoint caching records. No verified support claim for this model.

Access & pricing

Prices belong to an endpoint and billing tier. A provider listing does not guarantee access for every account or region.

API model ID
gemini-embedding-001
Access
Google AI Studio / Gemini API account; region, tier and quota restrictions apply.
Regions
See Google supported-region and account requirements; region-specific availability not yet collected.

Endpoint pricing has not been collected. Check the provider for applicable rates.

Data & enterprise terms

Retention, training use, regional processing and enterprise terms have not been summarized for this endpoint.

Google Enterprise Agent Platform (online)

Provider source (opens in a new tab)
API model ID
gemini-embedding-001
Access
Google Cloud project with billing and Agent Platform API enabled; IAM and regional quotas apply. Online prediction.
Regions
See model-specific Enterprise region availability
Batch limits
Cloud Storage JSONL only, no BigQuery. Up to 1,000,000 rows and 1 GB per job. Dynamic scheduling, up to 72 hours queued, target completion under 24 hours.Source for Batch limits (opens in a new tab)
taskInstructions
Supports task_type and title in embed_content_config.Source for taskInstructions (opens in a new tab)
Request limits
One text per online request, at most 2,048 tokens.Source for Request limits (opens in a new tab)

Prices retain their published currencies and billing units below.

Published billing units · original currency · observed 14 Oct 2026
CategoryUsageRateUnit
Embedding pricing: billing unit needs verificationText input1$0.000151,000 provider billing counts (unit unresolved)
Embedding inferenceEmbedding output2$0.00output response

Rate conditions

  1. The Gemini Embedding row in the current Enterprise pricing page uses count without defining its denominator. Do not assume character billing from legacy models or token billing from another host.
  2. No output charge is listed; input charges and model-version conditions apply.
Pricing source (opens in a new tab)

Data & enterprise terms

Retention, training use, regional processing and enterprise terms have not been summarized for this endpoint.

Google Enterprise Agent Platform (batch)

Provider source (opens in a new tab)
API model ID
gemini-embedding-001
Access
Google Cloud project with billing and Agent Platform API enabled; IAM and regional quotas apply. Asynchronous batch inference.
Regions
us-central1, us-east1, us-east4, us-west1, us-west4, europe-west1, europe-west4
Batch limits
Cloud Storage JSONL only, no BigQuery. Up to 1,000,000 rows and 1 GB per job. Dynamic scheduling, up to 72 hours queued, target completion under 24 hours.Source for Batch limits (opens in a new tab)
taskInstructions
Supports task_type and title in embed_content_config.Source for taskInstructions (opens in a new tab)
Request limits
One text per online request, at most 2,048 tokens.Source for Request limits (opens in a new tab)

Prices retain their published currencies and billing units below.

Published billing units · original currency · observed 14 Oct 2026
CategoryUsageRateUnit
Embedding pricing: billing unit needs verificationText input1$0.000121,000 provider billing counts (unit unresolved)
Embedding inferenceEmbedding output2$0.00output response

Rate conditions

  1. The Gemini Embedding row in the current Enterprise pricing page uses count without defining its denominator. Do not assume character billing from legacy models or token billing from another host.
  2. No output charge is listed; input charges and model-version conditions apply.
Pricing source (opens in a new tab)

Data & enterprise terms

Retention, training use, regional processing and enterprise terms have not been summarized for this endpoint.

Caching

Caching can reuse earlier input processing. Availability, lifetime and billing depend on the endpoint. A cache hit still generates a new response.

01 / INITIAL INPUTProcess & retain

The system processes eligible input and retains reusable state.

02 / LATER REQUESTCheck available state

Reuse depends on matching input, session state and the cache policy.

03 / CACHE HITReuse & generate

Reusing state can reduce repeated work. Any charges follow the billing rules below.

Google Gemini API

gemini-embedding-001
Not verified

Provider-side caching has not been verified for this endpoint. Missing documentation is not evidence that caching is unsupported.

How it works
Not collected
Minimum reusable input
Not collected
Lifetime & refresh
Not collected
How to enable it
Not collected
Usage fields
Not collected
Billing rules
Not collected
Limits & data boundaries
Not collected

No verified cache rate for this endpoint. An empty rate is not a zero charge.

Google Enterprise Agent Platform (online)

gemini-embedding-001
Not verified

Caching for this embedding endpoint is not established by the reviewed model docs. Generative Gemini prompt-cache support is not assumed.

How it works
Not collected

Caching for this embedding endpoint is not established by the reviewed model docs. Generative Gemini prompt-cache support is not assumed.

Minimum reusable input
Not collected

Caching for this embedding endpoint is not established by the reviewed model docs. Generative Gemini prompt-cache support is not assumed.

Lifetime & refresh
Not collected

Caching for this embedding endpoint is not established by the reviewed model docs. Generative Gemini prompt-cache support is not assumed.

How to enable it
Not collected

Caching for this embedding endpoint is not established by the reviewed model docs. Generative Gemini prompt-cache support is not assumed.

Usage fields
Not collected

Caching for this embedding endpoint is not established by the reviewed model docs. Generative Gemini prompt-cache support is not assumed.

Billing rules
Not collected

Caching for this embedding endpoint is not established by the reviewed model docs. Generative Gemini prompt-cache support is not assumed.

Limits & data boundaries
Not collected

Caching for this embedding endpoint is not established by the reviewed model docs. Generative Gemini prompt-cache support is not assumed.

No verified cache rate for this endpoint. An empty rate is not a zero charge.

Caching reviewed 14 Oct 2026

Google Enterprise Agent Platform (batch)

gemini-embedding-001
Not verified

Caching for this embedding endpoint is not established by the reviewed model docs. Generative Gemini prompt-cache support is not assumed.

How it works
Not collected

Caching for this embedding endpoint is not established by the reviewed model docs. Generative Gemini prompt-cache support is not assumed.

Minimum reusable input
Not collected

Caching for this embedding endpoint is not established by the reviewed model docs. Generative Gemini prompt-cache support is not assumed.

Lifetime & refresh
Not collected

Caching for this embedding endpoint is not established by the reviewed model docs. Generative Gemini prompt-cache support is not assumed.

How to enable it
Not collected

Caching for this embedding endpoint is not established by the reviewed model docs. Generative Gemini prompt-cache support is not assumed.

Usage fields
Not collected

Caching for this embedding endpoint is not established by the reviewed model docs. Generative Gemini prompt-cache support is not assumed.

Billing rules
Not collected

Caching for this embedding endpoint is not established by the reviewed model docs. Generative Gemini prompt-cache support is not assumed.

Limits & data boundaries
Not collected

Caching for this embedding endpoint is not established by the reviewed model docs. Generative Gemini prompt-cache support is not assumed.

No verified cache rate for this endpoint. An empty rate is not a zero charge.

Caching reviewed 14 Oct 2026

What the measurements say

No benchmark observations have been added for this model. We do not turn a vendor description into a performance score.

Latency and throughput depend on the host, request size, reasoning settings and load. There is no measured speed or global usage figure in this record.

The record behind the model

Why it is included

Google-documented proprietary hosted release in the Gemini API model catalog. No public weights identified for this release in the reviewed documentation; public-weight Gemma models are excluded.

Classification evidence (opens in a new tab)

Lifecycle dates

Gemini API release14 Jul 2025Source (opens in a new tab)
Earliest possible Gemini API shutdown14 May 2028Source (opens in a new tab)
Enterprise general availability20 May 2025Source (opens in a new tab)
Earliest possible Enterprise retirement20 May 2028Source (opens in a new tab)

Sources reviewed