What is the fastest AI API?
There is no single fastest AI API. As of October 23, 2026, 2 different providers hold the lead across 4 measured regions: Asia (Tokyo) — fireworks (20 ms), Europe (Germany) — fireworks (98 ms), South America (São Paulo) — openrouter (59 ms), US (Central) — fireworks (27 ms). Use the ranking for the region closest to where your requests originate.
Which AI API is fastest in each region?
| Region | Fastest API | p50 TTFB | p95 | Uptime | Samples |
|---|---|---|---|---|---|
| Asia (Tokyo) | fireworks | 20 ms | 63 ms | 100% | 289 |
| Europe (Germany) | fireworks | 98 ms | 203 ms | 100% | 288 |
| South America (São Paulo) | openrouter | 59 ms | 98 ms | 100% | 288 |
| US (Central) | fireworks | 27 ms | 75 ms | 100% | 288 |
Edge latency (time-to-first-byte), last 24 hours, measured directly against each provider’s API host. Full ranking per region
Why is there no single fastest AI API?
The same provider is not equally fast everywhere. sambanova responds in 26 ms from Asia (Tokyo) but 397 ms from Europe (Germany) — a 15.4× difference for the identical API, driven by where the request originates.
| Provider | Fastest | from | Slowest | from | Spread |
|---|---|---|---|---|---|
| sambanova | 26 ms | Asia (Tokyo) | 397 ms | Europe (Germany) | 15.4× |
| fireworks | 20 ms | Asia (Tokyo) | 253 ms | South America (São Paulo) | 12.7× |
| upstage | 59 ms | Asia (Tokyo) | 606 ms | South America (São Paulo) | 10.2× |
| hyperbolic | 126 ms | US (Central) | 844 ms | South America (São Paulo) | 6.7× |
| glm | 90 ms | Asia (Tokyo) | 538 ms | South America (São Paulo) | 6.0× |
| aleph-alpha | 100 ms | Europe (Germany) | 555 ms | Asia (Tokyo) | 5.5× |
| nscale | 98 ms | Europe (Germany) | 497 ms | Asia (Tokyo) | 5.0× |
| nebius | 99 ms | Europe (Germany) | 475 ms | Asia (Tokyo) | 4.8× |
| siliconflow | 84 ms | US (Central) | 373 ms | Asia (Tokyo) | 4.5× |
| qwen | 161 ms | Asia (Tokyo) | 708 ms | South America (São Paulo) | 4.4× |
Providers measured in all 4 regions, ranked by how much their latency varies by origin. This is the part a single-location benchmark cannot show.
How should I use this?
Compare providers from the region where your requests originate. If your application sends requests from several regions, check each region separately. Edge latency measures connection and response overhead before model inference.
Is this time to first token or time to first byte?
Every figure on this page is time to first byte (TTFB), also called edge latency: DNS, TCP, TLS and the first response byte, measured without calling a model. It is the floor you pay on every request. Time to first token (TTFT) — how long a real streamed completion takes to emit its first token — additionally includes queueing and the model’s prefill, so it depends far more on which model you call than on the provider.
Both are measured here and never averaged together. Measured TTFT per provider and region, with the model named on every row and the network share of TTFT broken out, is on the time to first token page.
Compare two specific providers
Each pair below has its own page with latency per region, observed uptime and the worst region for each provider — the head-to-head form of the tables above.
- anthropic vs openai latency and uptime
- anthropic vs google latency and uptime
- google vs openai latency and uptime
- cerebras vs groq latency and uptime
- deepseek vs openai latency and uptime
- groq vs sambanova latency and uptime
- fireworks vs together latency and uptime
- mistral vs openai latency and uptime
Where does this data come from?
Independent probes in 4 regions measure 46 AI inference APIs every five minutes and publish the result automatically. No provider pays for placement and nothing is ranked by commission. The full method, including its limitations, is on the methodology page; the underlying numbers are available as JSON under CC BY 4.0.