ModelRefs / Text Embedding Ada 002 by OpenAI — Benchmarks, Pricing & Re…

Text Embedding Ada 002 by OpenAI — Benchmarks, Pricing & Re…

Text Embedding Ada 002 (OpenAI): Text Embedding Ada 002 by OpenAI.. 8K context. Pricing: from $0.00010/1K in. Specs, benchmarks and code examples.

What this reference supports

Text Embedding Ada 002 is OpenAI's earlier-generation hosted embedding model, widely deployed in existing RAG and search systems. New builds should evaluate the Text Embedding 3 family instead; teams on Ada 002 should verify its current lifecycle and deprecation status before extending reliance.

Text Embedding Ada 002 is attributed to OpenAI in ModelRefs' canonical registry. Tracked modalities: Text input, Vector embedding output. Primary use cases considered on ModelRefs: Maintaining and comparing against existing Ada-002 retrieval indexes; Baseline retrieval where a stable, well-known embedding is already integrated.

This ModelRefs profile is Provisional and pending review — decision-support material, not a final or universal ranking. Confirm current behavior, access, pricing, limits, licensing, and lifecycle in OpenAI's own documentation, and evaluate Text Embedding Ada 002 on representative workloads before implementation.

Benchmark & Evaluation

ModelRefs currently has partial, narrow benchmark coverage for Text Embedding Ada 002. Treat the available benchmark evidence as one input to the decision, not a guarantee that Text Embedding Ada 002 is the strongest option for your workload, and evaluate it on representative workloads before selecting it.

  • No benchmark score is imported into this editorial record. Canonical benchmark runs and scores are governed separately with their own provenance and render only through those records; coverage in ModelRefs is currently narrow (partial), so any scored comparison must show its coverage limits.
  • ModelRefs holds canonical run evidence on retrieval benchmarks (MTEB, MIRACL); coverage is narrow and results are corpus-dependent.

Implementation considerations

  • For new systems, benchmark Text Embedding 3 Small/Large against Ada 002 before committing; do not assume the older model is equivalent.
  • Check current lifecycle/deprecation status before building new dependencies on this snapshot.
  • Hosted through the OpenAI embeddings API endpoint.
  • Confirm the model's current availability and deprecation timeline on OpenAI's deprecations page.

Risks and limitations

  • This is an earlier-generation embedding model; the Text Embedding 3 family generally supersedes it for new builds, subject to task-level verification.
  • Embedding quality is task- and domain-specific: retrieval/RAG performance depends on chunking, distance metric, and re-ranking, and does not follow chat-model quality intuitions.
  • Hosted embedding behavior, dimensions, pricing, and lifecycle can change; verify the current model snapshot and deprecation status before production reliance.

Source coverage

This reference is Provisional. Model behavior, access, pricing, limits, licensing, and lifecycle can change; verify the linked provider documentation and run task-specific evaluations before implementation.

Known coverage gaps:

  • Current deprecation timeline needs periodic verification against OpenAI's lifecycle pages.
  • Migration guidance from Ada 002 to the Text Embedding 3 family is not attached.

Sources

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