Google: Gemini Embedding 2 Preview
google/gemini-embedding-2-preview
Our take
AI-assisted analysis based on the sources below. Suitability is an editorial assessment; test it on your own workload.
Google's Gemini Embedding 2 Preview is a multimodal embedding model listed in the OpenRouter catalog. Per the catalog, it is described as Google's first multimodal embedding model, mapping text and images into a unified vector space for semantic search and retrieval-augmented generation. The catalog lists text, image, file, audio, and video as accepted input modalities with embeddings as the sole output, and reports a context length of 8192 tokens. All information here comes from the OpenRouter catalog; an independent model card was not available in this source pack.[1]
Strengths
- Described by the OpenRouter catalog as Google's first multimodal embedding model, unifying text and images in a single vector space.[1]
- The catalog lists five input modalities (text, image, file, audio, video) mapping to embedding outputs, suggesting broad ingestion flexibility.[1]
- Reported context length of 8192 tokens, which may accommodate longer passages than shorter-context embedding endpoints.[1]
Limitations
- Evidence is catalog-only: no independent model card, benchmarks, or measured performance data were included, so real-world quality and latency are unverified.[1]
- The catalog description states support for text and images specifically; the broader audio, video, and file input modalities listed are not qualified, and their maturity is unclear.[1]
- As a preview release, stability, pricing, and feature terms may change; embedding dimensionality and other technical details are not specified in the source.[1]
Where to use it
- Semantic search over text and image collections, matching the unified vector space the catalog describes.[1]
- Retrieval-augmented generation pipelines, which the catalog names as a target scenario.[1]
- Experimental indexing of mixed-modality content (audio, video, files), pending workload validation since only text and image support is explicitly described.[1]
Sources
- [1] OpenRouter catalog · Google: Gemini Embedding 2 PreviewSources checked: Nov 13, 2026
About this model
Description below is the original text supplied by OpenRouter, shown in the source language.
Gemini Embedding 2 Preview 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...
Specifications
- Model ID
- google/gemini-embedding-2-preview
- Creator
- Added to OpenRouter
- 17.04.2026
- 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) |
|---|---|---|---|---|---|---|
| Google AI Studio | 8,192 | $0.200 | $0 | — | — | 100% |
Provider data retrieved: 13.11.2026
Related articles
No published articles identify this model yet.