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SignalHarness Model Output Latency Comparator (Caller-Supplied Metrics)
x402
SignalHarness Model Output Latency Comparator (Caller-Supplied Metrics) is a paid API for AI agents from signalharness.ai, paid per call via x402, $0.015/call, status unknown (last checked 2026-09-15).
Compares model output latency metrics supplied by the caller and returns a structured analysis of relative performance differences.
Price / call$0.015
Success—
StatusUnknown
How this service works
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Output
Returns a JSON analysis object containing a comparison of the caller-supplied latency metrics, along with a warnings array noting that results are based on caller-supplied data, the service ID, and a signed receipt with execution metadata including payment ID, network, and a SHA-256 hash of the result for integrity verification.
Example use cases
LLM selection for production deployment
“I benchmarked three models on our internal test suite and have the latency data as JSON — can you compare them and tell me which one has the best median and p99 response times so I can decide which to deploy?”
Regression check after model update
“We upgraded our model last week and I have latency metrics from before and after. Can you run a comparison on this data to see if the update introduced any meaningful slowdown?”
Vendor evaluation for cost-performance tradeoff
“I have latency samples from two API providers we're evaluating. Can you analyze these metrics and tell me which vendor is faster overall and where the gaps are most significant?”
Technical details
Endpoint
POSThttps://signalharness.ai/api/agent/services/model_output_latency_compare_from_supplied_metrics/invokeWhen to prefer
Choose this endpoint when you already have latency metrics collected from your own benchmarking runs and want a structured comparison without re-running inference. It is best suited for post-hoc analysis where you control the data, as opposed to endpoints that run live model calls to measure latency directly. Useful when you need a signed, tamper-evident receipt of the analysis for audit or compliance purposes.
Side effects
- Malformed or non-JSON request_json input returns a validation error
- Missing or empty request_json causes a schema rejection
- Caller-supplied data that is not interpretable as latency metrics may produce a schema-valid but semantically meaningless analysis
- Payment failure on the x402 protocol blocks execution
- Result accuracy is fully dependent on the quality and accuracy of caller-supplied data — garbage in, garbage out
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| request_json | string |
Output
Schema · Response
{
"type": "json",
"example": {
"replay": false,
"result": {
"warnings": [
"Verify the caller-supplied data before relying on this result."
],
"service_id": "model_output_latency_compare_from_supplied_metrics",
"analysis_json": "{\"example\":\"schema-valid caller-supplied data\"}",
"evidence_scope": "caller_supplied_data"
},
"status": "succeeded",
"receipt": {
"asset": "0x833589fCD6eDb6E08f4c7C32D4f71b54bdA02913",
"usage": [],
"status": "succeeded",
"network": "eip155:8453",
"artifacts": [],
"endedAtMs": 0,
"latencyMs": 0,
"paymentId": "example-payment",
"receiptId": "example-receipt",
"requestId": "example-request",
"serviceId": "model_output_latency_compare_from_supplied_metrics",
"executionId": "example-execution",
"startedAtMs": 0,
"amountAtomic": "15000",
"resultSha256": "bf04d1fbf6d5e760b5cf2ece4a758bfeb4b367c9ba85850679d2e4f6d3566bb3",
"serviceVersion": "1.0.0",
"settlementReference": "0x0000000000000000000000000000000000000000000000000000000000000000"
},
"artifacts": [],
"requestId": "example-request",
"executionId": "example-execution"
}
}Tags
x402
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