{"uid":"cap_k8jfuYhZTMCLbT1UGBXBf","slug":"ged-x402-gemma-300m-text-embedding-e3c13cc1","name":"GED x402 Gemma-300M Text Embedding","description":"x402 workers ai. pay with usdc on base, polygon, arbitrum, world, or solana. no api keys.","url":"https://ged-x402-embed.jvalamis.workers.dev/v1/embed/embeddinggemma-300m","method":"GET","headers":{},"bodySchema":{"type":"object","properties":{"text":{"type":"string"},"texts":{"type":"array","items":{"type":"string"}}}},"responseSchema":{"type":"json","example":{"data":[{"index":0,"embedding":[0.01,-0.02]}]}},"example":null,"exampleRequest":null,"tags":["x402"],"displayCostAmount":"0.003","displayCostAsset":"USDC","priceDynamic":false,"priceHint":null,"priceStatus":"priced","priceSource":"settled","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":"static","summary":"$0.003/call","primary":{"kind":"static","protocol":"x402","network":"base","amountUsd":"0.003","per":"call","confidence":"exact"},"accepted":[{"kind":"static","protocol":"x402","network":"base","amountUsd":"0.003","per":"call","confidence":"exact"}]},"paymentMethods":[{"uid":"pm_SempYBsUC54IXQdsGH3MF","protocol":"x402","methodType":"crypto","chain":"base","mode":"charge","costAmount":"0.003","costPer":"request","priority":0,"asset":"0x833589fCD6eDb6E08f4c7C32D4f71b54bdA02913","unit":"request","depositMicros":null,"planRef":null}],"brandName":null,"brandSlug":null,"brandBaseUrl":null,"brandDocsUrl":null,"whatItDoes":"Generates vector embeddings for text using a Gemma-300M model, payable with USDC via x402 protocol — no API keys required.","exampleAgentPrompt":"Can you embed this text into a vector using the Gemma-300M model: 'The quick brown fox jumps over the lazy dog'? Pay with USDC — no API key needed.","exampleUseCases":null,"resultDescription":"A JSON object with a 'data' array, each element containing an 'index' and an 'embedding' field — the embedding is a float array representing the semantic vector of the input text.","failureModes":["Payment not completed or USDC balance insufficient — HTTP 402 returned","Invalid or missing 'text' and 'texts' fields — malformed request","Model inference timeout on Cloudflare Workers edge","Empty input string causes degenerate or error embedding","Unsupported blockchain network for payment fails the x402 handshake"],"whenToPreferThis":"Choose this endpoint when you need text embeddings without setting up API keys or managing credentials — ideal for autonomous agents that can pay per-call in USDC on Base, Polygon, Arbitrum, World, or Solana. It is well-suited for RAG pipelines, semantic search indexing, or similarity tasks where the Gemma-300M model's quality is sufficient and cost-per-call simplicity matters.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-09-15T00:40:14.861Z","isFirstParty":false}