Quickstart

Overview

In addition to our purpose-built code models, we host our set of preferred open-weight models for coding tasks. You can hit these models directly through our OpenAI-compatible API. For discounted reserve rates, reach out to info@relace.ai. All hosted models are served from https://models.relace.ai and authenticate with your regular Relace API key — no separate setup, and any OpenAI SDK works by pointing it at our base URL.

Model	Slug	Context	Input	Output	Cached Input
DeepSeek V4 Flash 0731	`deepseek-ai/DeepSeek-V4-Flash-0731`	1M	$0.14 / M	$0.28 / M	$0.028 / M
Kimi K3	`moonshotai/kimi-k3`	1M	$3.00 / M	$15.00 / M	$0.30 / M

Prerequisites

Sign up for a Relace account.
Create an API key.

List Available Models

The live up to date model catalog is available from the /models endpoint.

curl https://models.relace.ai/models \
  -H "Authorization: Bearer $RELACE_API_KEY"

Each entry in the returned data array includes the model id, context_length, per-token pricing, and supported sampling parameters and features.

Call Chat Completions

Send requests to /v1/chat/completions with the model ID of your choice. The endpoint is OpenAI-compatible, so you can use the OpenAI SDK directly.

from openai import OpenAI

client = OpenAI(
    api_key="[YOUR_API_KEY]",
    base_url="https://models.relace.ai/v1",
)

response = client.chat.completions.create(
    model="deepseek-ai/DeepSeek-V4-Flash-0731",
    messages=[
        {"role": "user", "content": "Write a binary search in Python."}
    ],
)

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

import OpenAI from "openai";

const client = new OpenAI({
  apiKey: "[YOUR_API_KEY]",
  baseURL: "https://models.relace.ai/v1"
});

const response = await client.chat.completions.create({
  model: "deepseek-ai/DeepSeek-V4-Flash-0731",
  messages: [
    { role: "user", content: "Write a binary search in Python." }
  ]
});

console.log(response.choices[0].message.content);

curl https://models.relace.ai/v1/chat/completions \
  -H "Authorization: Bearer $RELACE_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "deepseek-ai/DeepSeek-V4-Flash-0731",
    "messages": [
      {"role": "user", "content": "Write a binary search in Python."}
    ]
  }'

Tool calling, JSON mode, structured outputs, and the standard sampling parameters (temperature, top_p, stop, etc.) work as they do with any OpenAI-compatible provider.

Stream Responses

Set stream: true to receive tokens as they are generated. Token usage is always reported in the final chunk of the stream.

stream = client.chat.completions.create(
    model="moonshotai/kimi-k3",
    messages=[
        {"role": "user", "content": "Explain the actor model in one paragraph."}
    ],
    stream=True,
)

for chunk in stream:
    if chunk.choices and chunk.choices[0].delta.content:
        print(chunk.choices[0].delta.content, end="")
    if chunk.usage:
        print(f"\n\nTokens used: {chunk.usage.total_tokens}")

Usage

Hosted model usage is billed per token at the rates advertised in the catalog. Usage appears in your dashboard alongside your other Relace API usage.

Getting Started

Model Guides

Repos

Agents

Overview

Prerequisites

Usage

​Overview

​Prerequisites

​Usage

Overview

Prerequisites

Usage