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Fastest AI API from South America (São Paulo)

· edge + inference latency

As of October 22, 2026, measured from South America (São Paulo), the fastest AI inference API by edge latency (time-to-first-byte) is openrouter at 61 ms p50 (n=289).

Which AI API is fastest from South America (São Paulo)?

Endpoint response (TTFB) · last 24 hours · milliseconds (ms) · lower is faster.

How to read these metrics
Endpoint response (TTFB)Network connection and the first response byte, without model inference.
Typical · p5050% of successful timed samples finish within this time.
Slower · p9595% of successful timed samples finish within this time.
#ProviderTypical (p50 TTFB)Slower (p95)UptimeSamples
1openrouter61 ms104 ms100%289
2google142 ms199 ms100%289
3baseten154 ms167 ms100%289
4cohere167 ms203 ms100%289
5typesafe174 ms186 ms100%289
6cerebras192 ms259 ms100%289
7anthropic197 ms266 ms100%289
8perplexity204 ms425 ms100%289
9reka208 ms447 ms100%289
10meta-llama218 ms377 ms100%289
11inference-net227 ms560 ms100%289
12xai233 ms426 ms100%289
13groq234 ms281 ms100%289
14writer247 ms288 ms100%289
15novita247 ms316 ms100%289
16fireworks252 ms276 ms100%289
17openai253 ms606 ms100%289
18mistral253 ms329 ms100%289
19replicate267 ms556 ms100%289
20friendli271 ms380 ms100%289
21together273 ms652 ms100%289
22siliconflow285 ms290 ms100%289
23targon316 ms329 ms100%289
24ai21326 ms460 ms100%289
25yi-01ai332 ms1196 ms100%289
26kimi354 ms451 ms100%289
27baichuan360 ms392 ms100%289
28nebius366 ms374 ms100%289
29sambanova376 ms403 ms100%289
30ernie409 ms451 ms100%289
31deepseek436 ms501 ms100%289
32aleph-alpha444 ms532 ms100%289
33nscale451 ms478 ms100%289
34minimax484 ms517 ms100%289
35deepinfra538 ms1045 ms99.7%289
36glm539 ms573 ms100%289
37upstage606 ms646 ms100%289
38sarvam625 ms645 ms99.0%289
39sensenova634 ms1532 ms99.3%289
40iflytek648 ms1580 ms99.7%289
41stepfun659 ms1654 ms99.7%289
42doubao694 ms1598 ms99.7%289
43qwen716 ms772 ms100%289
44featherless744 ms2095 ms100%289
45hyperbolic845 ms933 ms100%289
46hunyuan1657 ms1739 ms100%289

openrouter leads by 81 ms over google here. The median provider measured from South America (São Paulo) answers in 326 ms, so the spread between the fastest and a typical option is 264 ms on every single request — before the model has produced anything.

Inference latency (time-to-first-token)

Each provider is measured on the model named below — model size affects TTFT far more than the network does, so these numbers are not a like-for-like ranking of providers. Use the edge-latency table above for that. Coverage is limited to providers we hold an API key for.

First model token (TTFT) · last 24 hours · milliseconds (ms) · lower is faster.

How to read these metrics
First model token (TTFT)Wait until a streamed model response emits its first token.
Typical · p5050% of successful timed samples finish within this time.
Slower · p9595% of successful timed samples finish within this time.

Models differ between providers; compare each named model over time.

#ProviderModelTypical (p50 TTFT)Slower (p95)Samples
1typesafejev-1.13.0400 ms496 ms72
2groqopenai/gpt-oss-120b776 ms1141 ms72
3googlegemini-flash-lite-latest1151 ms3599 ms72

Why measure from South America (São Paulo) separately?

Latency is a property of a route, not of a company. The same provider can lead in one region and trail in another, so a ranking produced from a single location tells you very little about what your users will experience somewhere else. This page reports only what was measured from South America (São Paulo); the other regions are ranked independently and often disagree — see the cross-region summary for how far apart they get.

How should these numbers be read?

p50 is the typical request and p95 is the slow tail: if p95 is far above p50, that provider is inconsistent from here, which usually hurts more than a slightly higher median. Uptime counts a probe as failed only on a genuine service failure — an authentication error means the endpoint answered correctly and counts as up. All figures cover the last 24 hours and are recomputed continuously; the methodology page states the limits of this data plainly.