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	$0.065 / M	$0.18 / M	$0.016 / M
Kimi K3	`moonshotai/kimi-k3`	1M	$3.00 / M	$15.00 / M	$0.30 / M
GLM 5.3 Flash	`z-ai/glm-5.3-flash`	1M	$0.07125 / M	$0.2375 / M	$0.01425 / M

Prerequisites

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

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}")

Anthropic-Compatible API

The same models are also served at /v1/messages in the Anthropic Messages dialect, so an Anthropic SDK works by pointing it at https://models.relace.ai. Content blocks, tool use, streaming, and extended thinking map onto the same model features as Chat Completions; pick whichever dialect your client already speaks.

from anthropic import Anthropic

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

message = client.messages.create(
    model="deepseek-ai/DeepSeek-V4-Flash-0731",
    max_tokens=1024,
    messages=[
        {"role": "user", "content": "Write a binary search in Python."}
    ],
)

print(message.content[0].text)

import Anthropic from "@anthropic-ai/sdk";

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

const message = await client.messages.create({
  model: "deepseek-ai/DeepSeek-V4-Flash-0731",
  max_tokens: 1024,
  messages: [
    { role: "user", content: "Write a binary search in Python." }
  ]
});

console.log(message.content[0].text);

curl https://models.relace.ai/v1/messages \
  -H "x-api-key: $RELACE_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "deepseek-ai/DeepSeek-V4-Flash-0731",
    "max_tokens": 1024,
    "messages": [
      {"role": "user", "content": "Write a binary search in Python."}
    ]
  }'

Prompt caching is automatic here too: hits are reported in usage.cache_read_input_tokens, and metadata.user_id plays the role of prompt_cache_key for session affinity.

Prompt Caching and Session Affinity

Prompt caching is automatic: when a request’s prompt shares a prefix with a recent request, the shared tokens are served from cache and billed at the Cached Input rate above. There are no cache breakpoints to place. Cache hits are reported in usage.prompt_tokens_details.cached_tokens. Caches are per server, so hit rates depend on requests from the same session routing to the same server. By default, requests are routed on a fingerprint of the conversation’s opening messages. To control routing explicitly, set prompt_cache_key (the same parameter as OpenAI’s): requests with the same key are routed to the same server, even when their prompts differ.

response = client.chat.completions.create(
    model="deepseek-ai/DeepSeek-V4-Flash-0731",
    messages=messages,
    prompt_cache_key="agent-7f3:session-456",
)

const response = await client.chat.completions.create({
  model: "deepseek-ai/DeepSeek-V4-Flash-0731",
  messages: messages,
  prompt_cache_key: "agent-7f3:session-456"
});

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": "Continue our review of auth.py."}
    ],
    "prompt_cache_key": "agent-7f3:session-456"
  }'

Guidelines:

Use a stable value per conversation or session, such as a session ID or user ID.
Don’t use a single key for all of your traffic; that concentrates it on one server and lowers your hit rate.
Affinity is best-effort: under failover or capacity pressure, a request may be served by a different server.

Usage

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

Getting Started

Model Guides

Repos

Agents

Overview

Prerequisites

Anthropic-Compatible API

Prompt Caching and Session Affinity

Usage

​Overview

​Prerequisites

​Anthropic-Compatible API

​Prompt Caching and Session Affinity

​Usage

Overview

Prerequisites

Anthropic-Compatible API

Prompt Caching and Session Affinity

Usage