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Telnyx Inference – Qwen3-235B-A22B Chat Completions (Large Context)
x402
Telnyx Inference – Qwen3-235B-A22B Chat Completions (Large Context) is a paid API for AI agents from x402.telnyx.com, paid per call via x402, $0.058485/call, status unknown (last checked 2026-10-15).
Runs OpenAI-compatible chat completions using Qwen/Qwen3-235B-A22B on Telnyx Inference, billed per call via x402 micropayments, optimized for large context workloads.
Price / call$0.058485
Success—
StatusUnknown
How this service works
Chat completions via Telnyx Inference (Qwen/Qwen3-235B-A22B). OpenAI-compatible. $0.010497 USDC per call. (upto metered — large context)
Output
Returns an OpenAI-compatible chat completion response object containing the assistant's generated message text, finish reason, token usage statistics, and any tool call objects if tools were provided. The model used is Qwen/Qwen3-235B-A22B.
Example use cases
Long-document legal analysis
“I have a 40,000-word contract I need analyzed. Use Qwen3-235B on Telnyx to review it and flag any clauses that limit indemnification — keep the temperature at 0.1 so it stays precise and cap the output at 6000 tokens.”
Multi-turn coding assistant session
“Set up a multi-turn conversation with Qwen3-235B on Telnyx Inference: first message is a system prompt saying you are an expert Python engineer, then ask it to design a Redis-backed task queue with retry logic — temperature 0.7, up to 4096 tokens.”
Tool-augmented research agent
“I want to run an agentic research loop using Qwen3-235B via Telnyx — give it these three tool definitions for web search, calculator, and calendar lookup, then ask it to plan a product launch timeline for Q4 with temperature 0.5 and max 2048 tokens.”
Technical details
Endpoint
POSThttps://x402.telnyx.com/v1/chat/completions/_t/qwen3-235b/upto?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need a very large open-weights model (235B parameters, Mixture-of-Experts architecture) for complex reasoning, long-document analysis, or nuanced instruction following, and want OpenAI-compatible API semantics with per-call micropayment billing via x402. Prefer it over smaller Telnyx Inference models when task complexity demands frontier-scale capability and over proprietary APIs when you want transparent per-call pricing without subscription overhead.
Side effects
- Payment failure via x402 protocol if wallet has insufficient USDC balance
- Context length exceeded if total tokens across messages surpass model limits (up to 200,000 chars per message, 32 messages max)
- Rate limiting or throttling on high-frequency requests
- Model returns truncated output if max_tokens is set too low
- Invalid tool schema causes tool-call parsing errors
- Temperature out of [0,2] range returns validation error
- Non-1 value for n parameter rejected by fixed constraint
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| n | integer | Fixed to one completion per paid call. |
| model | string | Model identifier; fixed to Qwen/Qwen3-235B-A22B on this route. |
| tools | array | |
| messages | array | OpenAI-style chat messages. |
| max_tokens | integer | |
| temperature | number |
Tags
x402
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