openai
OpenAI: Text Embedding Ada 002
openai/text-embedding-ada-002
Our take
AI-assisted analysis based on the sources below. Suitability is an editorial assessment; test it on your own workload.
openai/text-embedding-ada-002 is listed by the OpenRouter catalog as an OpenAI model that converts text inputs into embedding outputs, with a reported context length of 8,192 tokens. The catalog calls it OpenAI's legacy text embedding model. No independent model card or measured benchmark evidence was included in this source pack, so capability details remain catalog-reported rather than independently verified for this profile.[1]
Strengths
Limitations
- Evidence comes solely from the OpenRouter catalog; an independent model card was not available in this source pack.[1]
- No measured performance evidence was supplied, so quality, latency, and workload suitability require validation.[1]
- The catalog describes the model as legacy but provides no migration status or replacement guidance.[1]
Where to use it
- Consider for evaluation in text-similarity, retrieval, search, or clustering pipelines that require embedding outputs.[1]
Sources
- [1] OpenRouter catalog · OpenAI: Text Embedding Ada 002Sources checked: Nov 13, 2026
About this model
Description below is the original text supplied by OpenRouter, shown in the source language.
text-embedding-ada-002 is OpenAI's legacy text embedding model.
Specifications
- Model ID
- openai/text-embedding-ada-002
- Creator
- openai
- Added to OpenRouter
- 30.10.2025
- Context length
- 8,192
- Modality
- text->embeddings
- Input modalities
- text
- Output modalities
- embeddings
- Token pricing
- USD per 1M tokens: in $0.100 / 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 | — |
| 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) |
|---|---|---|---|---|---|---|
| OpenAI | 8,192 | $0.100 | $0 | — | — | 100% |
Provider data retrieved: 13.11.2026
Related articles
No published articles identify this model yet.