{"uid":"cap_gchkHgBWOs3fWmQUmh1D2","slug":"agents-llmapi-ai-create-embeddings-llm-api-3e83a7ab","name":"Create Embeddings (LLM API)","description":"Embedding vectors for the input text. model is one of: text-embedding-3-large, text-embedding-3-small, jina-embeddings-v4. Billed per exact input token at the model's service rate.","url":"https://agents.llmapi.ai/zc/v1/embeddings?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","example":{"input":"hello world","model":"text-embedding-3-small"},"required":["model","input"],"properties":{"input":{"description":"Text or array of texts to embed."},"model":{"enum":["text-embedding-3-large","text-embedding-3-small","jina-embeddings-v4"],"type":"string","description":"The model id exactly as written in the service description: text-embedding-3-large, text-embedding-3-small, or jina-embeddings-v4."}}},"responseSchema":null,"example":null,"exampleRequest":null,"tags":[],"displayCostAmount":"unknown","displayCostAsset":"USD","priceDynamic":true,"priceHint":null,"priceStatus":"unknown_unparsed","priceSource":"registry","requiresHandshake":false,"reviewCount":0,"rating":{"score":"0.00","successRate":"0.00","reviews":0,"stars":null,"state":"unrated"},"availabilityStatus":"unknown","priceObserved":null,"sessionDeposit":null,"pricing":{"kind":"unknown","summary":"price unknown","primary":{"kind":"dynamic","protocol":"mpp","network":"tempo","amountUsd":null,"per":"call","confidence":"unknown"},"accepted":[{"kind":"dynamic","protocol":"mpp","network":"tempo","amountUsd":null,"per":"call","confidence":"unknown"}]},"paymentMethods":[{"uid":"pm_bxuFYisLl6FSak0YuLUls","protocol":"mpp","methodType":"crypto","chain":"tempo","mode":"charge","costAmount":"unknown","costPer":"request","priority":0,"asset":null,"unit":"request","depositMicros":null,"planRef":null}],"brandName":"agents.llmapi.ai","brandSlug":"agents-llmapi-ai-x402","brandBaseUrl":"https://agents.llmapi.ai","brandDocsUrl":null,"whatItDoes":"Generates vector embeddings for input text using OpenAI or Jina embedding models, returning dense float vectors suitable for semantic search, clustering, or retrieval.","exampleAgentPrompt":"Generate an embedding for the text 'The quick brown fox jumps over the lazy dog' using the text-embedding-3-small model.","exampleUseCases":[{"title":"Semantic search over product catalog","prompt":"Embed this user query 'wireless noise-cancelling headphones under $200' using text-embedding-3-large so I can find the closest matching products in my vector database."},{"title":"Document clustering for research papers","prompt":"I need vector embeddings for this abstract — 'This paper explores transformer architectures for low-resource NLP tasks' — use jina-embeddings-v4 so I can cluster it with similar papers."},{"title":"RAG pipeline query encoding","prompt":"Before I retrieve context from my knowledge base, embed my question 'What are the cancellation terms for premium subscriptions?' using text-embedding-3-small so I can do a nearest-neighbor lookup."}],"resultDescription":"Returns a dense float vector (array of numbers) representing the semantic content of the input text. The dimensionality depends on the model chosen — text-embedding-3-large produces 3072-dim vectors, text-embedding-3-small produces 1536-dim vectors, and jina-embeddings-v4 varies. The response follows OpenAI embedding API conventions including the embedding array, model name, and token usage counts.","failureModes":["Invalid model name — must be exactly 'text-embedding-3-large', 'text-embedding-3-small', or 'jina-embeddings-v4'","Missing required 'input' or 'model' field returns 422 validation error","Input text exceeds model token limit causing a 400 or 413 error","Payment or authentication failure returns 402 or 401","Upstream LLM API timeout or outage returns 502 or 503"],"whenToPreferThis":"Choose this endpoint when you need pay-per-call embedding inference without a subscription, especially if you're already using the LLM API ecosystem for chat completions or other inference. It's ideal for agents that need OpenAI-compatible embeddings (text-embedding-3-small/large) or Jina v4 embeddings on demand without managing API keys for multiple providers. Prefer alternatives if you need streaming, batch processing of thousands of documents at discounted rates, or models not in the supported enum.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-17T18:33:50.125Z","isFirstParty":false,"canonicalSlug":"agents-llmapi-ai-create-embeddings-llm-api-3e83a7ab"}