amazon
Amazon: Titan Multimodal Embeddings G1
amazon/titan-embed-image-v1
Our take
AI-assisted analysis based on the sources below. Suitability is an editorial assessment; test it on your own workload.
According to OpenRouter's catalog, amazon/titan-embed-image-v1 is an Amazon multimodal embeddings model that accepts text, images, or combined text-and-image input and returns vectors in a shared embedding space. The catalog frames it for multimodal search and recommendation, with images submitted in base64 subject to a size limit that is truncated in the supplied evidence. It lists a contextLength value of 128, embedding-only output, and no supported parameters. This evidence is catalog metadata, not an independent model card or measured evaluation.[1]
Strengths
Limitations
- Only OpenRouter catalog evidence was supplied; an independent model card was not available in this source pack, so architecture, training data, license terms, and safety properties remain unknown.[1]
- No measured benchmark results were supplied; the catalog benchmark fields are empty or null, so retrieval quality and comparative performance require validation on the intended workload.[1]
- The listed contextLength is 128, the image size limit is cut off in the catalog excerpt, and supportedParameters is empty, leaving input limits and tunability unclear.[1]
Where to use it
Sources
- [1] OpenRouter catalog · Amazon: Titan Multimodal Embeddings G1Sources checked: Nov 13, 2026
About this model
Description below is the original text supplied by OpenRouter, shown in the source language.
Amazon Titan Multimodal Embeddings G1 embeds text, images, or text and image together into a shared vector space for multimodal search and recommendation. Images are sent as base64 (up to...
Specifications
- Model ID
- amazon/titan-embed-image-v1
- Canonical ID
- amazon/titan-embed-image-v1-20261026
- Creator
- amazon
- Added to OpenRouter
- 26.10.2026
- Context length
- 128
- Modality
- text+image->embeddings
- Input modalities
- text, image
- Output modalities
- embeddings
- Token pricing
- USD per 1M tokens: in $0.800 / 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 | — |
| Vision | No measurement | input: image |
| Image generation | No measurement | — |
| Audio | No measurement | — |
| Video | No measurement | — |
| 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) |
|---|---|---|---|---|---|---|
| Amazon Bedrock | 128 | $0.800 | $0 | — | — | — |
Provider data retrieved: 13.11.2026
Related articles
No published articles identify this model yet.