Model Cost Profile

Relace: Relace Search

Developer: relace

Pricing updated Mar 11, 2026

Input rank: #246Output rank: #242

Live Pricing

Input: $1.00

Output: $3.00

Pricing via OpenRouter API ยท Last synced Mar 11, 2026

Relace Search, developed by Relace, offers an extensive context window of 256,000 tokens, making it suitable for applications requiring in-depth analysis of large datasets, such as legal document review or comprehensive research projects. With an input cost of $1.00 per million tokens and an output cost of $3.00 per million tokens, teams can effectively manage their budgets while leveraging the model for tasks like customer support automation or content generation. This pricing structure allows organizations to scale their usage based on specific project needs, optimizing both performance and cost-efficiency.

๐Ÿ”ง Tool Calling

Context Window

256,000

Tokens

Input Price / 1M

$1.00

Prompt tokens

Output Price / 1M

$3.00

Completion tokens

Intelligence (MMLU)

Benchmark Pending

Massive Multitask Language Understanding

Price History

Relace: Relace Search Pricing Trend

Input / 1M tokens0.0%Output / 1M tokens0.0%
Mar 7 โ€” Mar 11
$1.00$2.00$3.00Mar 7Mar 8Mar 9Mar 10Mar 11

Current Input / 1M

$1.00

Current Output / 1M

$3.00

Cheaper Alternatives to Compare

Quick links for cost-down decisions before production rollout.

FAQ

Common pricing and benchmark questions for Relace: Relace Search.

How much does Relace: Relace Search cost per 1M input tokens?

Relace: Relace Search input pricing is $1.00 per 1M tokens based on the latest synced provider data.

How much does Relace: Relace Search cost per 1M output tokens?

Relace: Relace Search output pricing is $3.00 per 1M tokens based on the latest synced provider data.

What context window does Relace: Relace Search support?

Relace: Relace Search supports a context window of 256,000 tokens.

How can I compare Relace: Relace Search with cheaper alternatives?

Use the comparison links on this page to open direct model-vs-model pricing and benchmark pages, then evaluate monthly spend projections for your workload.