Gemini Embedding 2
google/gemini-embedding-2
Coming soon
Listed, not sold yet: the provider's resale terms are being confirmed.
Multimodal embedding model that maps text, images, video, audio and PDFs into one embedding space.
Price
- Input
- $0.2 per 1M tokens
- Output
- Price on request
- Notes
- Text input $0.20/1M. Image $0.45/1M ($0.00012 per image), audio $6.50/1M, video $12.00/1M. Output not billed.
- Source
- Google pricing , last verified October 8, 2026
No markup on model usage: you pay the provider's list price.
Model
- Context
- 8K (8,192 tokens)
- Modality
- Embeddings
- Input
- text, image, video, audio, file
- Output
- embeddings
- Weights
- Closed
- Released
- April 22, 2026
- Tags
- embeddings, retrieval, multimodal
Data policy
- Prompts go to
- Google (Gemini Developer API)
- Retention
- Paid tier: prompts and responses not used to improve Google products, but logged for a limited period for abuse monitoring, free tier content may be used to improve products
- Zero data retention
- Not offered
- Region
- No region guarantee, data may be stored transiently or cached in any country where Google operates. Google points ZDR and enterprise processing needs to Vertex AI (Gemini Enterprise Agent Platform)
- Policy
- Google data policy
Summarised from the provider's published terms. The provider's own policy is what applies.
Call it with any OpenAI SDK
Available when the model is live
from openai import OpenAI
client = OpenAI(
base_url="https://api.safeguard.sh/v1",
api_key="SAFEGUARD_API_KEY",
)
response = client.chat.completions.create(
model="google/gemini-embedding-2",
messages=[{"role": "user", "content": "Hello"}],
)
print(response.choices[0].message.content)Base URL https://api.safeguard.sh/v1, model google/gemini-embedding-2.
Self-healing security runs on Safeguard.
Your first fix PR is minutes away.
No sales call required, even your agent can complete the purchase over MCP.