As of September 06, 2026, the yi-01ai AI API responds in 194 ms p50 (edge, time-to-first-byte) from Asia (Tokyo) — its fastest measured region — with 92.4% uptime. Slowest is South America (São Paulo) at 351 ms p50.
Is yi-01ai down right now?
Reachable from all 4 regions
Last successful probe Sep 6, 18:16 UTC · every 5 minutes from 4 region(s)
There was an outage: on Sep 6, 12:55 UTC, host probes failed from 2 of 4 regions simultaneously for at least 5 minutes. No other provider failed in that window, so a shared route or CDN does not explain it. Measured from outside yi-01ai’s own network, independently of its status page; full log: measured AI API incidents.
Real requests: not measured for yi-01ai — only the API host is probed here, so errors limited to specific models are invisible to these probes. That is exactly what a status page tends to report, hence the line below.
yi-01ai publishes no machine-readable status page, so there is nothing to cross-check against.
Edge latency, 24 h
194 ms
p50 from Asia (Tokyo), the fastest region
Uptime, 24 h
98.0%
1,153 probes across 4 region(s)
Failed probes, 72 h
91
of 3,457 · Asia (Tokyo), South America (São Paulo)
Reported by yi-01ai, 72 h
—
no machine-readable status page
Was yi-01ai down in the last 3 days?
Yes. 1 outage(s) could be attributed to yi-01ai in the last 72 hours: probes failed from two or more regions at once while no other provider was failing.
Asia (Tokyo) only — not an outage · under one 5-minute probe cycle · 1 failed probe(s) · timeout
Asia (Tokyo) only — not an outage · at least 10 minutes · 2 failed probe(s) · timeout
Asia (Tokyo) only — not an outage · under one 5-minute probe cycle · 1 failed probe(s) · timeout
Asia (Tokyo) only — not an outage · under one 5-minute probe cycle · 1 failed probe(s) · timeout
Outage — 2 of 4 regions (Asia (Tokyo), South America (São Paulo)) · at least 5 minutes · 2 failed probe(s) · timeout
Asia (Tokyo) only — not an outage · under one 5-minute probe cycle · 1 failed probe(s) · timeout
Asia (Tokyo) only — not an outage · under one 5-minute probe cycle · 1 failed probe(s) · timeout
Asia (Tokyo) only — not an outage · under one 5-minute probe cycle · 1 failed probe(s) · timeout
Asia (Tokyo) only — not an outage · under one 5-minute probe cycle · 1 failed probe(s) · timeout
Asia (Tokyo) only — not an outage · at least 10 minutes · 2 failed probe(s) · timeout
Asia (Tokyo) only — not an outage · under one 5-minute probe cycle · 1 failed probe(s) · timeout
Asia (Tokyo) only — not an outage · at least 10 minutes · 2 failed probe(s) · timeout
What yi-01ai’s own status page reported
yi-01ai publishes no machine-readable status page, so there is nothing to set against the measurements above.
Is yi-01ai getting faster or slower?
hourly p50 latencyall probes succeededsome probes failedhalf or more failedno data
One panel per region: the line is the hourly p50 edge latency (shared scale, ms), the strip beneath it is the outcome of that hour’s host probes. Hover any hour for the numbers. Flat is good; a rising line means the endpoint is slowing down from that origin, a gap means no probe succeeded in that hour.
How fast is the yi-01ai API from each region?
Region
p50 TTFB
p95
Uptime
Asia (Tokyo)
194 ms
993 ms
92.4%
Europe (Germany)
221 ms
711 ms
100%
South America (São Paulo)
351 ms
1246 ms
99.7%
US (Central)
247 ms
859 ms
100%
Measured from Asia (Tokyo), yi-01ai responds in 194 ms; from South America (São Paulo) the same API takes 351 ms — 1.8× longer for an identical request. That difference is the network path, not the model, and it applies to every call you make.
What is actually being measured here?
A probe in each region opens a real connection to yi-01ai’s own API host every five
minutes and times DNS resolution, the TCP handshake, the TLS handshake and the first byte of the
response. Nothing is routed through a gateway or aggregator, so these figures describe
yi-01ai’s infrastructure rather than a reseller’s. Uptime counts a probe as failed only when the
service genuinely fails — a 401 from an unauthenticated probe means the endpoint answered
correctly and is counted as up.
What this page does not tell you
These are edge latency numbers: the time before the model begins generating. They
say nothing about answer quality, throughput, price, or how long a full completion takes — those
depend on the model you call. Edge latency matters because it is unavoidable: it is paid on every
request, before a single token exists, and no prompt engineering removes it. Where an API key is
available, inference time-to-first-token is measured separately and shown on the region pages with the
model named next to the figure. Likewise, an unauthenticated probe cannot see errors that hit only some
models or some accounts — the kind a status page usually reports — which is why yi-01ai’s
own reports are shown next to the measurements rather than folded into them.