Fastest AI inference API in 2026: 30 days of latency data for Groq, Cerebras, SambaNova and 43 more, from 3 regions

The fastest API depends on where the client runs. The measurement compared network latency to 46 providers from US Central, Tokyo, and São Paulo. It tested each provider's official API host, so the result reflects the route to that provider's front door, not necessarily the speed of the model's underlying GPUs.

Fireworks AI was closest in Tokyo, at 19 milliseconds, and US Central, at 28 milliseconds. OpenRouter led in São Paulo, at 61 milliseconds, while Fireworks was 252 milliseconds away there. SambaNova was especially uneven: 25 milliseconds from Tokyo, 167 milliseconds from US Central, and 371 milliseconds from São Paulo.

Those results show why a global ranking would mislead. Provider locations, routing, and regional infrastructure change the network distance for each client. The article therefore recommends measuring from the region where application servers run, then rechecking regularly because provider front doors can move.

Network latency, reported as TTFB, measures the time from sending a request until the first byte of the reply arrives. The probe opens an HTTPS connection to the provider's official API host and usually receives a 401 because no API key is used. This captures the network path and edge processing, not model generation.

TTFT measures a real streamed completion. The probe opens a fresh HTTPS connection, sends a one-word prompt with max_tokens set to 1, and records the first non-empty streamed chunk. It therefore includes connection setup, routing, queueing, prefill, and the initial model computation inside the provider.

That difference matters when choosing an API. Groq's front door was 121–234 milliseconds away, but its first token took 560–1,330 milliseconds after that network distance. The article also notes that TTFT used fresh connections, so reusing connections can reduce the observed delay.

The study covered 46 providers, three probe regions, and a 30-day window from 27 September to 26 October 2026. Probes ran every five minutes and measured one request to each provider's official API host. In total, 1,190,063 successful network probes were included, showing that latency was not a single stable number.

Regional differences were large. SambaNova measured 25 milliseconds from Tokyo, 167 milliseconds from US Central, and 371 milliseconds from São Paulo. That is about a 15-fold difference between its closest and farthest measured regions. Fireworks AI ranged from 19 milliseconds in Tokyo to 252 milliseconds in São Paulo, while Groq ranged from 121 to 234 milliseconds.

The results also changed the provider ranking by region. Fireworks led in Tokyo and US Central, but OpenRouter led in São Paulo. The practical implication is clear: developers need measurements from their actual deployment regions, plus regular checks as provider infrastructure and routing change.

A farther API front door does not automatically mean a slower first token. TTFT includes much more than the network trip. It also includes connection setup, queueing, prefill, and the provider's initial model work. Those internal delays can outweigh differences in network latency.

Groq's front door was 234 milliseconds from São Paulo, compared with 121 milliseconds from US Central. Yet Groq's first token arrived fastest from São Paulo: its median was about 0.8 seconds there, versus 1.4 seconds from US Central. The pattern appeared in both halves of the month, so it was not just one brief measurement spike.

The article observes the result but cannot establish its cause from outside the provider. A likely explanation is that requests from different regions used different Groq capacity, though that remains unconfirmed. The lesson is practical: measure complete TTFT from user regions instead of assuming network distance predicts generation speed.

Median latency describes the middle request, but users also experience the slowest part of the distribution. A high p95 means one request in twenty is at least that slow. Frequent timeouts and 5xx errors are worse: some users receive no answer at all, may retry, or may abandon the interaction.

Lumen illustrates the difference. Its median TTFT was within a few hundred milliseconds of Groq's, but its p95 reached 5.6–6.1 seconds. The article also reports that 8–10% of requests timed out or returned a 5xx. That combination can make an application feel unreliable even when its typical response looks competitive.

For a real product, the tail affects perceived quality, support costs, and workflow consistency. The article recommends examining p95 alongside p50. It also cautions that the Google key used free-tier capacity, so these tail results may not represent a paid account. Developers should measure their own account and workload before deciding.

Choosing the lowest median is only one way to improve perceived response time. Developers should first measure from the region where their servers run, because provider rankings changed across US Central, Tokyo, and São Paulo. They should also compare p95, since a slightly slower typical response may feel better if its tail is tight.

Connection reuse is another concrete improvement. The measurements opened a fresh HTTPS connection for every request, and that setup time is included in TTFT. A warm, reused connection skips some of that work. Developers can also compare complete first-token measurements, rather than relying on network latency or vendor tokens-per-second claims, which the study did not measure.

The article recommends rechecking monthly because provider front doors move. It also advises testing the exact model endpoint and account conditions. For example, Google's free-tier key may have contributed to its high tail. These steps produce a more realistic view of what users will experience than a single benchmark number.

AI inference is the process of using a trained model to generate an output for a request. In a streamed response, the model produces tokens progressively. The first token matters because it marks when the user begins seeing an answer, even though the full completion may take longer.

The request must first travel from the application to the provider's API and establish an HTTPS connection. That network path produces part of the delay measured by TTFB. After the request arrives, the provider may queue it, prepare the prompt through prefill, and run the model on its computing system before sending the first generated token. TTFT includes these stages.

The article's Groq results show why the distinction matters. Its front door was 121–234 milliseconds away, while the first token arrived 560–1,330 milliseconds after that network distance. The internal portion was larger in all three regions. Thus, a nearby API endpoint does not guarantee fast inference, and network benchmarks cannot replace end-to-end TTFT tests.