Overview

Run long-horizon agents on Sail.

Sail serves trillions of tokens, with support for the best open-source models and your own LoRA fine-tunes. To achieve maximum efficiency for long-horizon agents, we serve traffic at higher latencies in tiers of service called completion windows.

Python

from openai import OpenAI

client = OpenAI(
    base_url="https://api.sailresearch.com/v1",
    api_key="YOUR_SAIL_API_KEY",
)

completion = client.chat.completions.create(
    model="zai-org/GLM-5.2-FP8",
    messages=[{"role": "user", "content": "What are the top 3 things to do in San Francisco?"}],
)

print(completion.choices[0].message.content)

Run an AI model

Run leading open-source AI models with our OpenAI-compatible inference API.

Create a Sailbox

Give long-horizon agents persistent compute that can run indefinitely.

Send requests at scale

Use completion windows and background requests for large workloads.

Intelligence at scale

More agents thinking longer and harder, with space to act and explore, can do incredible things:

• Detail

  uses Sail inference to deeply scan codebases for their most consequential yet hard-to-catch bugs

• Jack & Jill

  runs large-scale deep research with Sail inference, matching job seekers’ resumes with job descriptions from thousands of employers

• We

  won Browsecomp-Plus

  , the AI deep research benchmark, using open models running on Sail inference

• We

  built Redis in Rust

  with a swarm of 4 long-horizon coding agents running on Sailboxes with Sail inference over 27 hours

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