Embedding API
OpenAI text embeddings for semantic search, retrieval, clustering, and ranking workflows.
# Install the model skill for app development workflows
npx skills add runapi-ai/embedding -gInstall the Embedding skill for this app: 1. Add runapi-ai/embedding with the skills installer. 2. Load SKILL.md in this workspace. 3. Use its docs, schemas, pricing notes, and setup steps when adding model features. 4. Confirm the install path when done.
OpenAI Embedding models convert text into dense vectors for semantic search, retrieval-augmented generation, clustering, classification, and ranking. The text-embedding-3 family supports efficient production retrieval with optional vector dimensionality control.
- Multiple variants for different speed / quality tiers
- Model skill includes docs, schemas, and setup notes
- Works with app-focused coding workflows
- Failed generations are not charged
Compare all API variants
Install the Embedding skill for app development
Load the model docs, schemas, pricing notes, and setup steps into your coding workspace.
# Install the model skill for app development workflows
npx skills add runapi-ai/embedding -gInstall the Embedding skill for this app: 1. Add runapi-ai/embedding with the skills installer. 2. Load SKILL.md in this workspace. 3. Use its docs, schemas, pricing notes, and setup steps when adding model features. 4. Confirm the install path when done.
From model skill to first result in four steps
Choose a model
Pick the model and variant that match your output type, quality bar, and latency target.
Configure
Set your RunAPI key and install the model skill in your coding workspace.
Call
Use the skill instructions to add the model feature inside your application.
Receive
Poll by task ID, stream when supported, or handle the webhook callback.
What is the Embedding API?
OpenAI Embedding models expose the standard OpenAI Embeddings API through RunAPI, so vector search and RAG pipelines can use the same RunAPI key as GPT chat and Responses traffic.
Why route the Embedding API through RunAPI
One auth, every provider
A single RunAPI key unlocks the whole catalog. No separate accounts, no key rotation per integration.
Unified pricing & billing
Per-call pricing in USD, billed monthly. Failed generations are not charged.
Schema-first SDK
Typed schemas and setup notes are packaged in the model skill so implementation starts from the right contract.
Common questions
Which variant should I start with?
Pick the cheapest variant that meets your quality bar. Most teams start on the fast variant and graduate to pro for production.
Is there a free tier?
New accounts get free first calls on every model. After that, pay per call.
Do you stream results?
Where streaming is available, RunAPI streams end-to-end.
How are failures billed?
Failed generations are not charged.
Are outputs cached?
Generated outputs are stored and retrievable by task ID. Inputs are not cached.
Can I use commercially?
Yes — commercial use is included for every variant unless a model license explicitly restricts it, which is called out on the variant page.
What about rate limits?
Per-key rate limits scale with usage tier. See pricing page for current limits.
Where can I report issues?
Open an issue on the public GitHub repo or email support.
