{"uid":"cap_w_AwSObzFH1pkGlkvX23X","slug":"agent-data-tools-revmesh2074-workers-dev-chat-completion-llama-3-3-90fb64e8","name":"Chat Completion – Llama 3.3 70B or GPT-OSS-120B (Large Model)","description":"181 pay-per-call tools for AI agents over HTTP or MCP, most at $0.003. Every caller gets 25 free calls; then pay per call in USDC via x402 (Base, Polygon, Arbitrum, Monad, World Chain) or by card with prepaid credits from /credits. No account needed; failed calls are never charged; per-tool reliability is public at /status. Crypto: token prices and wallet portfolios from Uniswap v3, chain reads on Base, Ethereum, Arbitrum, Optimism and Polygon, OFAC sanctions screening. Web: Read public static documentation, pages, PDFs and RSS feeds as clean text, plus link previews and sitemaps. Business: company profiles, domain and email checks. Also Bitcoin, FX, weather, holidays, geocoding, AI text, and JSON, date and validation utilities.","url":"https://agent-data-tools.revmesh2074.workers.dev/ai/chat-large?utm_source=zero.xyz","method":"GET","headers":{},"bodySchema":{"type":"object","$schema":"https://json-schema.org/draft/2020-12/schema","required":["input"],"properties":{"input":{"type":"object","required":["type","method"],"properties":{"type":{"type":"string","const":"http"},"method":{"enum":["GET"],"type":"string"},"queryParams":{"type":"object","required":["prompt"],"properties":{"model":{"enum":["llama-3.3-70b","gpt-oss-120b"],"type":"string","examples":["llama-3.3-70b"],"description":"llama-3.3-70b (default) or gpt-oss-120b"},"prompt":{"type":"string","examples":["Explain x402 in one sentence."],"description":"User prompt, up to 8,000 characters"},"system":{"type":"string","examples":["You are a concise assistant."],"description":"Optional system prompt, up to 2,000 characters"},"maxTokens":{"type":"integer","examples":[200],"description":"Maximum output tokens, 1-1024 (default 400)"},"temperature":{"type":"number","examples":[0.6],"description":"0-1.5 (default 0.6)"}}}},"additionalProperties":false},"output":{"type":"object","required":["type"],"properties":{"type":{"type":"string"},"example":{"type":"object","properties":{"model":{"type":"string"},"response":{"type":"string"}}}}}}},"responseSchema":{"type":"json","example":{"model":"@cf/meta/llama-3.3-70b-instruct-fp8-fast","response":"x402 lets software pay for an HTTP request with a stablecoin by answering a 402 Payment Required challenge."}},"example":null,"exampleRequest":null,"tags":["x402"],"displayCostAmount":"0.01","displayCostAsset":"USDC","priceDynamic":false,"priceHint":null,"priceStatus":"priced","priceSource":"probe","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":"$0.01/call","primary":{"kind":"static","protocol":"x402","network":"base","amountUsd":"0.01","per":"call","confidence":"exact"},"accepted":[{"kind":"static","protocol":"x402","network":"base","amountUsd":"0.01","per":"call","confidence":"exact"}]},"paymentMethods":[{"uid":"pm_3YbQtc26qHfvOAYTbFDek","protocol":"x402","methodType":"crypto","chain":"base","mode":"charge","costAmount":"0.01","costPer":"request","priority":0,"asset":"0x833589fCD6eDb6E08f4c7C32D4f71b54bdA02913","unit":"request","depositMicros":null,"planRef":null}],"brandName":"agent-data-tools.revmesh2074.workers.dev","brandSlug":"agent-data-tools-revmesh2074-workers-dev-x402","brandBaseUrl":"https://agent-data-tools.revmesh2074.workers.dev","brandDocsUrl":null,"whatItDoes":"Runs a user prompt through a large open model (Llama 3.3 70B Instruct or GPT-OSS-120B) and returns the generated text response, with optional system prompt and temperature control.","exampleAgentPrompt":"Use the Llama 3.3 70B model to draft a detailed technical explanation of how transformer attention mechanisms work, aimed at a software engineer with no ML background — give it up to 800 tokens and keep the temperature at 0.5.","exampleUseCases":[{"title":"Complex technical Q&A drafting","prompt":"I need a thorough explanation of the differences between TCP and UDP protocols, with examples of when to use each — use the llama-3.3-70b model, up to 1,000 tokens, and keep the tone educational but not too academic."},{"title":"Multi-step reasoning problem","prompt":"Walk me through step-by-step reasoning for this logic puzzle: 'Five people each own a different pet and drink a different beverage. Alice drinks tea. The person with a dog drinks coffee...' — use the gpt-oss-120b model with temperature 0.3 for accuracy."},{"title":"Persuasive business email drafting","prompt":"Draft a persuasive cold outreach email to a potential enterprise client for our data pipeline tool, highlighting reliability and cost savings — use llama-3.3-70b, system prompt: 'You are a B2B sales copywriter', and give it 600 tokens."}],"resultDescription":"A JSON object containing the model name used and the generated text response string (up to 1,024 tokens). The response field holds the full completion text produced by the selected large model.","failureModes":["Prompt exceeds 8,000 characters — request rejected","maxTokens out of 1–1024 range — validation error","Invalid model enum value — error returned","Prompt results in a policy refusal — empty or truncated response","Payment not provided or insufficient credits — 402 response with no charge","Temperature outside 0–1.5 range — error or clamped value"],"whenToPreferThis":"Prefer this endpoint over the smaller /ai/chat (8B model) when the task requires deep multi-step reasoning, long-form drafting, nuanced Q&A, or when the 8B model produces unsatisfactory results. Choose llama-3.3-70b for open-weight reproducibility or gpt-oss-120b for maximum capability. At $0.01/call it is 3× more expensive than the 8B endpoint, so reserve it for tasks where quality clearly matters.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-22T18:18:52.450Z","isFirstParty":false,"canonicalSlug":"agent-data-tools-revmesh2074-workers-dev-chat-completion-llama-3-3-90fb64e8"}