Google: Gemini Embedding 2
google/gemini-embedding-2
Gemini Embedding 2 is Google's first multimodal embedding model. We currently support mapping text and images into a unified vector space for semantic search and retrieval-augmented generation (RAG). It supports input context up to 8,192 tokens and flexible output dimensions from 128 to 3,072 (recommended: 768, 1536, or 3,072). Designed for cross-modal similarity — you can embed a text query and retrieve the most relevant images, or vice versa — making it well-suited for multimodal search, recommendation, and document understanding pipelines.
Providers
Different companies host the same model. OpenRouter routes your request to one of them based on the routing mode you pick: Balanced (price + speed), Nitro (fastest), or Floor (cheapest).
| $0.450 | $6.50 | $12.00 | 0.36s | ||
| $0.450 | $6.50 | $12.00 | 0.32s | ||
| $0.450 | $6.50 | $12.00 | 0.17s | ||
Not used in Standard routing:Why these endpoints are not used | |||||
| $0.495 | $7.15 | $13.20 | 0.14s | ||
- Image $0.45 / Audio $6.500.36s latency100.00% uptime
- Image $0.45 / Audio $6.500.32s latency100.00% uptime
- Image $0.45 / Audio $6.500.17s latency100.00% uptime
- Not used in Standard routing:Why these endpoints are not used
- Image $0.495 / Audio $7.150.14s latency100.00% uptime
Pricing
The average price customers actually pay for this model, next to the prices providers post. Caching and discounts mean the price actually paid is often well below the listed one.
Weighted average
Gemini Embedding 2 — Price history
| $0.225 | $0.00 | 0.0% | 0.6% | ||
| $0.243 | $0.00 | 0.0% | 61.5% | ||
| $0.398 | $0.00 | 0.0% | 32.4% | ||
Not used in Standard routing:Why these endpoints are not used | |||||
| $0.226 | $0.00 | 0.0% | 5.5% | ||
- Effective in $0.225 / Effective out $0.00Token share0.6%
- Effective in $0.243 / Effective out $0.00Token share61.5%
- Effective in $0.398 / Effective out $0.00Token share32.4%
- Not used in Standard routing:Why these endpoints are not used
- Effective in $0.226 / Effective out $0.00Token share5.5%
Performance
Latency is how long it takes to return the full response (lower is better).
P50, best provider
Uptime
Uptime is the percentage of the past 3 days that at least one provider was responding to requests. Availability is the percentage of time that inference was successfully served. OpenRouter continuously monitors and uses the next-best provider when one returns an error.
Availability over the last 3 days
Last 72 hoursAvailability over the last 24 hours
When an error occurs in an upstream provider, we can recover by routing to another healthy provider, if your request filters allow it. You can access per-provider uptime data programmatically through the Endpoints API. Learn more about our load balancing and provider routing options.
Apps
Public apps that send the most traffic to this model. Good signal for what real production workloads look like — and a hint at which use cases this model is best suited for.
Activity
Token volume and request traffic to this model over time.
API
Drop-in code to call this model. OpenRouter's API is OpenAI-compatible — most SDKs work by just swapping the base URL. The only thing that changes between models is the model slug below.
Available through EU in-region routing
Google: Gemini Embedding 2 is available through EU in-region routing. Requests sent to eu.openrouter.ai are decrypted in the EU and routed only to shared provider endpoints in Europe (the EU/EEA, the UK, and Switzerland).
- Providers in Europe
- Google Vertex
- Base URL
https://eu.openrouter.ai/api/v1- Plan
- Requires Business or Enterprise. Self-serve on Business: no contract, no monthly minimum. OpenRouter Business for EU in-region routing
Fails closed: if no shared provider endpoint in Europe is available, the request errors instead of leaving the region. Requests served by your own BYOK key go to your deployment’s region, which you control. In-region routing docs
Documentation
Guides, cookbooks, blog posts, and tools for building with Google: Gemini Embedding 2 on OpenRouter.
Frequently asked questions
Gemini Embedding 2 is Google's first multimodal embedding model. We currently support mapping text and images into a unified vector space for semantic search and retrieval-augmented generation (RAG). It supports input context up to 8,192 tokens and flexible output dimensions from 128 to 3,072 (recommended: 768, 1536, or 3,072).
The Gemini Embedding 2 documentation on OpenRouter includes the Reranking in RAG: How to Fix Bad Retrieval with a Reranker blog post. The quickstart covers API keys and your first request, and the API reference lists every parameter.
Gemini Embedding 2 costs $0.20/M tokens for Text Input, $0.45/M tokens for Image Input, $0.45/M tokens for File Input, $6.50/M tokens for Audio Input, and $12.00/M tokens for Video Input.
Gemini Embedding 2 accepts up to 8,192 tokens per input. Longer text has to be split into multiple inputs.
Gemini Embedding 2 accepts text, images, files such as PDFs, audio, and video as input and returns embedding vectors.
Gemini Embedding 2 is served by 2 providers on OpenRouter: Google Vertex and Google AI Studio. Requests are routed to the best available provider, with automatic failover to the others, and you can pin or exclude providers with provider routing.
Gemini Embedding 2 was released on May 20, 2026.