cerebras vs google — AI API latency comparison

Last verified September 07, 2026

As of September 07, 2026, google has lower edge latency (time-to-first-byte) than cerebras in 4 of 4 measured region(s). From Asia (Tokyo), google responds in 62 ms p50 vs 197 ms.

Is cerebras or google faster in each region?

Full details: cerebras by region · google by region.

Does the answer change by region?

The answer flips depending on where you measure from. In Asia (Tokyo) the gap is widest at 135 ms, while in South America (São Paulo) it narrows to 23 ms.

This is why a single-location benchmark cannot answer “is cerebras or google faster” for you. Pick the row that matches where your requests originate.

Does cerebras or google have better uptime?

Over the last 24 hours cerebras and google are level on availability at 100% of probes succeeding across 4 region(s). Neither is separated from the other by uptime at this sample size.

Availability observed by our probes over the last 24 hours, not a contractual SLA. Providers publish their own SLA terms and their own status pages; this is an outside view of whether requests actually completed, which is the number a status page cannot give you about your own region. The worst region is shown next to the average because an average hides the one place where a share of your users sees a different service. Longer windows and all 4 regions: uptime comparison · confirmed outages: incidents.

What exactly is being compared?

Both providers are measured the same way, from the same probes, on the same schedule: a real connection is opened to each provider’s own API host and DNS, TCP, TLS and the first response byte are timed. Neither is measured through a gateway or aggregator, so the numbers reflect each provider’s own infrastructure. Figures are p50 and p95 over the last 24 hours; percentiles are nearest-rank, because a handful of outliers would distort an average.

What this comparison does not cover

This is edge latency — the time before the model starts working. It is the floor you pay on every request regardless of which model you call, and it is the part you cannot optimise away with a better prompt. It is not time-to-first-token, throughput, price or answer quality: those depend on the specific model, and comparing them across providers running different models would not be like-for-like. Measured time to first token (TTFT), with the model named next to every figure and the network share broken out, is on the time to first token page.

Method in full: methodology · Raw numbers under CC BY 4.0: JSON API · No provider pays for placement.