OpenAI cut its embedding API price 5x from text-embedding-ada-002 to text-embedding-3-small ($0.10 → $0.02 per 1M tokens)

OpenAI's own current developer documentation lists text-embedding-ada-002 (released December 2022) at $0.10 per 1M tokens and its successor text-embedding-3-small (released January 2024) at $0.02 per 1M tokens — a direct 5x reduction in list price across one model generation.

The figure matters because it counters a claim circulating in 2026 pricing round-ups (e.g. pecollective.com and similar aggregator listicles): that "embedding prices have stayed remarkably stable compared to LLM API prices, where cuts of 50–80% over 18 months have been common." That framing is a Tier 4 content-aggregator assertion, recorded here only as the claim under test, not as evidence. The one comparison checkable against a primary source — OpenAI's own two embedding generations — shows the 2022–24 boom in API price competition reached embeddings too, at least for OpenAI's line.

This extends claim-inference-cost-collapsed-280x, which documents the roughly 280x per-token collapse in generative LLM inference cost over the same window; the embedding case is a narrower but concrete counter to the idea that embeddings were exempt from that competition. It also mirrors the shape of myth-inference-two-thirds-of-compute — a plausible-sounding aggregate claim that a primary source does not actually support once the load-bearing number is checked. The note sits in moc-inference-economics.

Scope caveat. The refutation is established only for OpenAI's own line. Whether Cohere, Google, and Voyage embedding APIs show the same launch-to-launch price cut, or whether this is an OpenAI-specific effect, is open and routed to question-embedding-api-price-cuts-across-providers. The successor model text-embedding-3-small also introduced truncatable dimensions via claim-matryoshka-representation-learning-truncatable-embeddings, so the newer generation is cheaper and more flexible.