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Relace: Relace Search

relace/relace-search

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The relace-search model uses 4-12 view_file and grep tools in parallel to explore a codebase and return relevant files to the user request.

In contrast to RAG, relace-search performs agentic multi-step reasoning to produce highly precise results 4x faster than any frontier model. It's designed to serve as a subagent that passes its findings to an "oracle" coding agent, who orchestrates/performs the rest of the coding task.

To use relace-search you need to build an appropriate agent harness, and parse the response for relevant information to hand off to the oracle. Read more about it in the Relace documentation(opens in new tab).

Modalities

Input Price

$1per 1M

Output Price

$3per 1M

Context

256K

Weekly Tokens

5.14M

Released

Dec 8, 2025

Overview
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API

Sample code and API for Relace Search

OpenRouter normalizes requests and responses across providers for you.

1

Get your API key

Create an API key from your OpenRouter dashboard and set it as an environment variable:

2

Make your first request

Use relace/relace-search with the OpenRouter API:

OpenRouter provides an OpenAI-compatible completion API to 400+ models & providers that you can call directly, or using the OpenAI SDK. Additionally, some third-party SDKs are available.

In the examples below, the OpenRouter-specific headers are optional. Setting them allows your app to appear on the OpenRouter leaderboards.

Using third-party SDKs

For information about using third-party SDKs and frameworks with OpenRouter, please see our frameworks documentation.

3

Enable streaming

Add "stream": true to your request body to receive responses as server-sent events:

Endpoint

POSThttps://openrouter.ai/api/v1/chat/completions
AuthorizationBearer $OPENROUTER_API_KEY
Content-Typeapplication/json
HTTP-Refereroptional — your site URL, for rankings
X-Titleoptional — your site name, for rankings
Modelrelace/relace-search

Parameters

NameTypeDefaultDescription
max_tokensinteger—This sets the upper limit for the number of tokens the model can generate in response.
stoparray—Stop generation immediately if the model encounter any token specified in the stop array.
temperaturefloat1This setting influences the variety in the model's responses.
top_pfloat1This setting limits the model's choices to a percentage of likely tokens: only the top tokens whose probabilities add up to P.
seedinteger—If specified, the inferencing will sample deterministically, such that repeated requests with the same seed and parameters should return the same result.
toolsarray—Tool calling parameter, following OpenAI's tool calling request shape.
tool_choicestring or object—Controls which (if any) tool is called by the model.