Sub-100ms inference
Requests are routed to the nearest accelerator pool and served from a runtime tuned for time-to-first-token. Median latency stays under 80 ms worldwide.
Deploy and scale large language models on a globally distributed runtime. Median latency under 80 ms, elastic autoscaling to millions of tokens per second, and an OpenAI-compatible API your team already knows.
No credit card required · 1M free tokens every month
# Same API surface as the model providers you already use
curl https://api.zerohollow.org/v1/chat/completions \
-H "Authorization: Bearer $ZH_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"model": "atlas-3",
"stream": true,
"messages": [{ "role": "user", "content": "Explain RLHF in one line." }]
}'
# → first token in 71 ms · 248 tok/s sustained
Powering AI products at fast-moving teams
Platform
One runtime for serving, scaling, and observing frontier models — so your team ships features instead of managing GPUs.
Requests are routed to the nearest accelerator pool and served from a runtime tuned for time-to-first-token. Median latency stays under 80 ms worldwide.
Scale from zero to millions of tokens per second with no capacity planning. Cold starts are measured in milliseconds, and you only pay for what you use.
Trace every request end to end, inspect token usage, replay prompts, and stream structured logs to your stack. Debug regressions before users notice.
SOC 2 Type II, end-to-end encryption, granular access controls, and private VPC deployments. Your prompts and data are never used for training.
Models
Open-weight and proprietary models, served behind a single endpoint. Switch between them with one parameter — no redeploys.
Our frontier general-purpose model. State-of-the-art reasoning, tool use, and instruction following for agents and assistants.
Tuned for software engineering: repository-scale context, fill-in-the-middle, and high-accuracy diffs across 80+ languages.
Reads documents, screenshots, charts, and photos. Grounded visual reasoning with precise bounding-box and OCR outputs.
Developers
Point your existing OpenAI-compatible client at ZeroHollow and you are done. Streaming, function calling, structured outputs, and fine-tuning all work the way you expect.
from openai import OpenAI
client = OpenAI(
base_url="https://api.zerohollow.org/v1",
api_key=os.environ["ZH_API_KEY"],
)
stream = client.chat.completions.create(
model="atlas-3",
messages=[{"role": "user", "content": "Draft a launch tweet."}],
stream=True,
)
for chunk in stream:
print(chunk.choices[0].delta.content or "", end="")
import OpenAI from "openai";
const client = new OpenAI({
baseURL: "https://api.zerohollow.org/v1",
apiKey: process.env.ZH_API_KEY,
});
const stream = await client.chat.completions.create({
model: "atlas-3",
messages: [{ role: "user", content: "Draft a launch tweet." }],
stream: true,
});
for await (const chunk of stream) {
process.stdout.write(chunk.choices[0]?.delta?.content ?? "");
}
Trust & company
ZeroHollow is an independent research and infrastructure company. We keep the runtime fast, private, and compliant so you can focus on product.
Spin up a key, send your first request in minutes, and scale when you are ready. The first million tokens are on us every month.
Free tier · upgrade anytime · cancel whenever