{"uid":"cap_FkmesUTMrMJj25tLqI7MR","slug":"qwen3-32b-llm-chat-completions-2a9e91bb","name":"Qwen3-32B LLM Chat Completions","description":"","url":"https://ari001.tailb4ac3a.ts.net/v1/ventures/llm_chat_api/llm_chat_qwen3_32b?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","$schema":"https://json-schema.org/draft/2020-12/schema","required":["input"],"properties":{"input":{"type":"object","required":["type","method","bodyType","body"],"properties":{"body":{"type":"object","required":["messages"],"properties":{"messages":{"type":"array","items":{"type":"object","required":["role","content"],"properties":{"role":{"enum":["system","user","assistant"]},"content":{"type":"string"}}},"maxItems":32,"minItems":1},"max_tokens":{"type":"integer","maximum":1024,"minimum":1}}},"type":{"type":"string","const":"http"},"method":{"enum":["POST","PUT","PATCH"],"type":"string"},"bodyType":{"enum":["json","form-data","text"],"type":"string"}},"additionalProperties":false},"output":{"type":"object","required":["type"],"properties":{"type":{"type":"string"},"example":{"type":"object","required":["ok","service"],"properties":{"ok":{"type":"boolean"},"error":{"type":"string","description":"present when ok is false"},"model":{"type":"string"},"usage":{"type":"object","properties":{"prompt_tokens":{"type":["integer","null"]},"completion_tokens":{"type":["integer","null"]}}},"method":{"type":"string"},"message":{"type":"object","properties":{"role":{"const":"assistant"},"content":{"type":"string"}}},"service":{"type":"string"}}}}}}},"responseSchema":null,"example":null,"exampleRequest":null,"tags":["x402"],"displayCostAmount":"0.003","displayCostAsset":"USDC","priceDynamic":false,"priceHint":null,"priceStatus":"priced","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":"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_btia1asmRxvHa6pFQJacx","protocol":"x402","methodType":"crypto","chain":"base","mode":"charge","costAmount":"0.003","costPer":"request","priority":0,"asset":null,"unit":"request","depositMicros":null,"planRef":null}],"brandName":null,"brandSlug":null,"brandBaseUrl":null,"brandDocsUrl":null,"whatItDoes":"Runs a conversational chat completion request through the Qwen3-32B large language model and returns an assistant reply with token usage statistics.","exampleAgentPrompt":"Ask Qwen3-32B to summarize the following research abstract in 3 bullet points, keeping the response under 300 words: 'Large language models have demonstrated remarkable capabilities across diverse tasks...'","exampleUseCases":[{"title":"Automated customer FAQ answering","prompt":"Use Qwen3-32B to answer this customer question based on our product policy: 'Can I return a product after 60 days if it's unopened?' — keep the answer under 150 words and polite in tone."},{"title":"Code explanation for developer tools","prompt":"Have Qwen3-32B explain what this Python snippet does and suggest any improvements: 'def fib(n): return n if n <= 1 else fib(n-1) + fib(n-2)' — limit the reply to 200 tokens."},{"title":"Multi-turn reasoning conversation","prompt":"I want to run a multi-turn reasoning session with Qwen3-32B: first tell it 'You are a financial analyst assistant', then ask it 'What are the top 3 risks of investing in emerging market bonds right now?' and give me the full reply."}],"resultDescription":"An OpenAI-style chat completion object containing the assistant's text reply, the model name ('Qwen3-32B'), and token usage stats (prompt_tokens and completion_tokens). The response indicates whether the call succeeded (ok: true/false) and includes an error field if something went wrong.","failureModes":["Message array exceeds 16,000 characters total — request rejected","max_tokens exceeds 1024 — validation error","Empty or missing messages array — returns validation error","Model unavailability or timeout — ok: false with error message","Malformed role values (not system/user/assistant) — schema rejection"],"whenToPreferThis":"Choose this endpoint when you specifically need Qwen3-32B's reasoning quality — it is stronger than Llama-3.1-8B-Instruct for complex tasks and may differ stylistically from DeepSeek-V3.2. Ideal when you want an OpenAI-compatible chat API behind x402 micropayment ($0.003/call) without managing your own GPU infrastructure. Best for single-turn or short multi-turn conversations under the 16,000-character context limit and 1024-token output cap.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-02T01:18:39.534Z","isFirstParty":false,"canonicalSlug":"qwen3-32b-llm-chat-completions-2a9e91bb"}