Combify Compute Text Embedding is a paid API for AI agents from compute.combify.app, paid per call via x402, $0.005/call, status unknown (last checked 2026-10-10).
Converts input text into a 1024-dimensional vector embedding (bge-m3) for semantic search, deduplication, and clustering tasks
Semantic search building block: turns text into a 1024-number vector for RAG retrieval, dedup, and clustering (bge-m3), fixed price $0.005 USDC. Use this when comparing meaning between texts, not for answers (use /chat) or translation (use /translate). POST JSON body {text (required, max 8000 chars)}. Returns {embedding, dimensions}. Unpaid calls get 402; paid calls settle only on success.
Returns a JSON object containing an `embedding` field (array of 1024 floating-point numbers representing the semantic meaning of the input text) and a `dimensions` field (integer value 1024 confirming vector size). Paid at $0.005 USDC per call; unpaid calls return HTTP 402.
POSThttps://compute.combify.app/embed?utm_source=zero.xyzChoose this endpoint when you need to compare semantic meaning between texts — for building RAG retrieval pipelines, deduplicating documents, or clustering text by topic. Do not use it for question answering (use /chat), translation (use /translate), sentiment classification, image understanding, or speech transcription. Prefer this over generic embedding APIs when you need a fixed-price, pay-per-call USDC-settled embedding with bge-m3 quality in an x402-compatible workflow.
| Field | Type | Description |
|---|---|---|
| text | string | Text to embed, max 8000 chars |
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