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Blockle Inference API
x402
Blockle Inference API is a paid API for AI agents from blockle.org, paid per call via x402, $0.005/call, status unknown (last checked 2026-10-31).
Runs a prompt through a hosted open-source LLM (Qwen or Llama) and returns the model's text completion, paid per-call via x402 micropayment.
Price / call$0.005
Success—
StatusUnknown
How this service works
A non-custodial multi-chain wallet, a cross-chain exchange, and AI trading bots that trade on your command — your keys, your desk.
Output
Returns a JSON object containing the text completion in the 'answer' field, the model name that served the request, the hardware tier used (as an integer), and a 'servedBy' object identifying which backend/miner processed the request.
Example use cases
On-demand LLM answers for crypto questions
“Use Blockle inference with the llama3.1:8b-instruct model to explain in simple terms how cross-chain bridges work and what the main security risks are.”
Large-model creative writing task
“Run this creative writing prompt through Blockle's qwen2.5:72b-instruct model with a temperature of 0.9 and max 500 tokens: 'Write an opening paragraph for a thriller novel set in a decentralized city where all identity is on-chain.'”
Cost-conscious summarization on small tier
“Use Blockle inference on the qwen2.5:1.5b-instruct model to summarize the following meeting notes into three bullet points: [paste notes here]. I want to keep costs low so use the smallest model.”
Technical details
Endpoint
POSThttps://blockle.org/api/inference/infer?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need pay-as-you-go LLM inference without a subscription, want to use open-source models (Qwen2.5 or Llama3.1 families) at a specific hardware tier, or are operating in a crypto-native / x402 micropayment environment. It's especially suitable when you want to select a specific model size or hardware tier for cost/quality trade-offs, and when custodial account management with API key subscriptions is undesirable.
Side effects
- Payment failure or insufficient USDC balance causes 402 response before inference runs
- Invalid or unsupported model name returns a validation error
- Prompt too long for the selected model's context window causes truncation or error
- Requesting a tier that is currently unavailable due to no active miners returns a service unavailable error
- Malformed JSON body or missing required 'prompt' field returns 400 bad request
- High temperature values may produce low-quality or incoherent completions
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| tier | string | Alternative to `model`: the hardware/price tier. |
| model | string | Model to use (bigger = pricier). See GET /api/inference/models. |
| promptrequired | string | The prompt / user message. |
| max_tokens | integer | Max tokens to generate (optional). |
| temperature | number | Sampling temperature (optional). |
Output
Schema · Response
| Field | Type | Description |
|---|---|---|
| tier | integer | |
| model | string | The model that served it. |
| answer | string | The model's completion. |
| servedBy | object | Which miner/backend served it. |
Tags
x402
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