meta-llama — AI API latency & reliability by region
As of September 06, 2026, the meta-llama AI API responds in 75 ms p50 (edge, time-to-first-byte) from US (Central) — its fastest measured region — with 100% uptime. Slowest is South America (São Paulo) at 220 ms p50.
Is meta-llama down right now?
Reachable from all 4 regions
Last successful probe Sep 6, 19:20 UTC · every 5 minutes from 4 region(s)
Every probe from every region reached the meta-llama API successfully in the last 72 hours. Measured from outside meta-llama’s own network, independently of its status page; full log: measured AI API incidents.
Real requests: not measured for meta-llama — 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.
meta-llama publishes no machine-readable status page, so there is nothing to cross-check against.
Edge latency, 24 h
75 ms
p50 from US (Central), the fastest region
Uptime, 24 h
100%
1,154 probes across 4 region(s)
Failed probes, 72 h
0
of 3,458 probes, all regions
Reported by meta-llama, 72 h
—
no machine-readable status page
Was meta-llama down in the last 3 days?
No. All 3,458 probes from 4 region(s) reached the meta-llama API in the last 72 hours.
What meta-llama’s own status page reported
meta-llama publishes no machine-readable status page, so there is nothing to set against the measurements above.
Is meta-llama getting faster or slower?
Right now meta-llama is slower than usual from US (Central): 117 ms against a three-day typical of 68 ms.
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 meta-llama API from each region?
Region
p50 TTFB
p95
Uptime
Asia (Tokyo)
125 ms
321 ms
100%
Europe (Germany)
101 ms
299 ms
100%
South America (São Paulo)
220 ms
305 ms
100%
US (Central)
75 ms
151 ms
100%
Measured from US (Central), meta-llama responds in 75 ms; from South America (São Paulo) the same API takes 220 ms — 2.9× 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 meta-llama’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
meta-llama’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 meta-llama’s
own reports are shown next to the measurements rather than folded into them.