Google: Gemini Embedding 2
google/gemini-embedding-2
Our take
AI-assisted analysis based on the sources below. Suitability is an editorial assessment; test it on your own workload.
OpenRouter's catalog identifies google/gemini-embedding-2 as a Google embedding model that accepts text, image, file, audio, and video input and returns embeddings. Its catalog description more narrowly says it is Google's first multimodal embedding model and currently maps text and images into a shared vector space for semantic search and RAG. No measured performance results or independent model card were included in this source pack.[1]
Strengths
Limitations
- Only OpenRouter catalog data was provided; an independent model card was not available, so capability claims are source-reported rather than independently verified.[1]
- No benchmark results or measured retrieval quality were included; suitability for a workload requires validation.[1]
- The catalog's modality field includes file, audio, and video, while its description says current support covers text and images; confirm other modalities before relying on them.[1]
Where to use it
- Evaluate it for semantic search where text and images need to share an embedding space, subject to workload testing.[1]
- Consider it as a candidate for retrieval-augmented generation indexing while validating retrieval quality on your data.[1]
- It may fit multimodal asset retrieval if the catalog's broader input support is confirmed for the chosen modality.[1]
Sources
- [1] OpenRouter catalog · Google: Gemini Embedding 2Sources checked: Nov 13, 2026
About this model
Description below is the original text supplied by OpenRouter, shown in the source language.
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...
Specifications
- Model ID
- google/gemini-embedding-2
- Creator
- Added to OpenRouter
- 20.05.2026
- Context length
- 8,192
- Modality
- text+image+file+audio+video->embeddings
- Input modalities
- text, image, file, audio, video
- Output modalities
- embeddings
- Token pricing
- USD per 1M tokens: in $0.200 / out $0
- Knowledge cutoff
- —
- Expiration date
- —
Tasks and capabilities
A grade appears only where the source supplies a matching measurement for that task, the model is active and the cohort holds at least 10 comparable models. The capability column lists facts the source declares — supported formats, reasoning and tool parameters — which are not measured quality.
| Task | Grade | Source-declared capability |
|---|---|---|
| General quality | No measurement | — |
| Coding | No measurement | — |
| Agents | No measurement | — |
| Writing | No measurement | — |
| Reasoning | No measurement | — |
| Document analysis | No measurement | input: file |
| Vision | No measurement | input: image |
| Image generation | No measurement | — |
| Audio | No measurement | input: audio |
| Video | No measurement | input: video |
| Embeddings | No measurement | output: embeddings |
Evaluations
No evaluations are supplied for this model.
How grades work
Each letter grade compares a model only against other models scored by the same source and metric in the current snapshot. S means the top 10%, A the next 20%, B the next 30%, C the rest. Models without a published measurement are shown as not rated — a supported format alone never implies measured quality.
- S — S — top 10% of the cohort
- A — A — next 20% of the cohort
- B — B — next 30% of the cohort
- C — C — below the B band
Providers
Optional live provider statistics from OpenRouter. Missing values are unknown, not zero.
| Provider | Context length | Price in /1M | Price out /1M | Latency p50 (30m, s) | Throughput p50 (30m, tok/s) | Uptime (30m) |
|---|---|---|---|---|---|---|
| 8,192 | $0.200 | $0 | — | — | 100% | |
| 8,192 | $0.200 | $0 | — | — | 100% | |
| Google AI Studio | 8,192 | $0.200 | $0 | — | — | 100% |
| 8,192 | $0.220 | $0 | — | — | 100% |
Provider data retrieved: 13.11.2026
Related articles
No published articles identify this model yet.