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gemini-embedding-2

⁦Google DeepMind⁩ · ⁦gemini-embedding-2⁩

Gemini Embedding 2: multimodal embeddings (text, image, audio, video, PDF) in one space.

⁦8K⁩ tokens

Starting price

54,380

per million tokens

Billing

Pay as you go

Service status

Active

About gemini-embedding-2

Gemini Embedding 2: multimodal embeddings (text, image, audio, video, PDF) in one space.

gemini-embedding-2 pricing

Input

54,380

Output

54,380

same as input

Cache (read)

54,380

same as input

Cache (write)

54,380

same as input

Model id

gemini-embedding-2

Provider

Google DeepMind

Context window

8K

Billing basis

Input and output tokens

Status

Active

Share model

https://cupai.ir/en/models/gemini-embedding-2

Sample code and API for gemini-embedding-2

Point the base URL at CupAI and use your own API key; the rest of the request stays exactly as it is in any compatible client.

curl 'https://api.cupai.ir/v1beta/models/gemini-embedding-2:generateContent' \
  -H 'Content-Type: application/json' \
  -H 'x-goog-api-key: $CUPAI_API_KEY' \
  -d '{
    "contents": [
      {
        "parts": [
          {
            "text": "Hello!"
          }
        ]
      }
    ]
  }'

Replace CUPAI_API_KEY with your own key.

Create an API key

Frequently asked questions about gemini-embedding-2

How is usage of gemini-embedding-2 billed?
By the input and output tokens of each request. The rate for each part is in the pricing table on this page, and the amount is deducted from your wallet.
How do I connect to gemini-embedding-2?
Point the base URL at CupAI, put your API key in the request header, and send the model id in the request body. Ready-made samples are on this page.
How do payments work?
Payments are in Toman and need no foreign credit card. Credit you buy can be spent on any available model.

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How model pricing works

Every AI model strikes a different balance between speed, answer quality and cost. Flagship models suit complex reasoning, long-document analysis and precise code generation, while lighter models cost considerably less for summarising, classification and short answers. The list above shows each model's rate broken down by input token, output token and cache, so you can estimate the cost of your workload before you start.

A token is the smallest unit of text a model processes; roughly speaking a thousand tokens is about 750 English words. The cost of a request is the sum of its input and output tokens, so shortening your prompt and capping the response length reduces cost directly. Some models have a second price tier for very long inputs, which reprices the entire request once it crosses a stated threshold.