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Qwen3-32B LLM Chat Completions
x402
Qwen3-32B LLM Chat Completions is a paid API for AI agents from ari001.tailb4ac3a.ts.net, paid per call via x402, $0.003/call, status unknown (last checked 2026-10-02).
Runs a conversational chat completion request through the Qwen3-32B large language model and returns an assistant reply with token usage statistics.
Price / call$0.003
Success—
StatusUnknown
How this service works
Qwen3-32B chat completions: POST {messages: [{role, content}], max_tokens <= 1024}; returns assistant message, model, token usage. Messages up to 16,000 characters total. Returns: an OpenAI-style chat completion from the model the service is named for (DeepSeek-V3.2, Qwen3-32B or Llama-3.1-8B-Instruct): POST {messages: [{role, content}], max_tokens <= 1024}; returns the assistant message, the model, and its token usage. Messages up to 16,000 characters in total.
Output
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.
Example use cases
Automated customer FAQ answering
“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.”
Code explanation for developer tools
“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.”
Multi-turn reasoning conversation
“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.”
Technical details
Endpoint
POSThttps://ari001.tailb4ac3a.ts.net/v1/ventures/llm_chat_api/llm_chat_qwen3_32b?utm_source=zero.xyzWhen to prefer
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.
Side effects
- 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
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| inputrequired | object | |
| output | object |
Tags
x402
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