Model Cost Profile

Inception: Mercury 2

Developer: inception

Pricing updated Mar 11, 2026

Input rank: #155Output rank: #148

Live Pricing

Input: $0.2500

Output: $0.7500

Pricing via OpenRouter API ยท Last synced Mar 11, 2026

Inception: Mercury 2 offers a substantial context window of 128,000 tokens, making it ideal for applications requiring extensive text analysis, such as legal document review or large-scale content generation. The pricing structure, with an input cost of $0.25 per million tokens and an output cost of $0.75 per million tokens, allows teams to budget effectively based on their specific usage patterns. This model is particularly beneficial for organizations that need to process and generate large volumes of text efficiently, optimizing both performance and cost.

๐Ÿ”ง Tool Calling๐Ÿ“‹ Structured Output๐Ÿง  Reasoning

Context Window

128,000

Tokens

Input Price / 1M

$0.2500

Prompt tokens

Output Price / 1M

$0.7500

Completion tokens

Intelligence (MMLU)

Benchmark Pending

Massive Multitask Language Understanding

Price History

Inception: Mercury 2 Pricing Trend

Input / 1M tokens0.0%Output / 1M tokens0.0%
Mar 7 โ€” Mar 11
$0.2500$0.5000$0.7500Mar 7Mar 8Mar 9Mar 10Mar 11

Current Input / 1M

$0.2500

Current Output / 1M

$0.7500

Cheaper Alternatives to Compare

Quick links for cost-down decisions before production rollout.

FAQ

Common pricing and benchmark questions for Inception: Mercury 2.

How much does Inception: Mercury 2 cost per 1M input tokens?

Inception: Mercury 2 input pricing is $0.2500 per 1M tokens based on the latest synced provider data.

How much does Inception: Mercury 2 cost per 1M output tokens?

Inception: Mercury 2 output pricing is $0.7500 per 1M tokens based on the latest synced provider data.

What context window does Inception: Mercury 2 support?

Inception: Mercury 2 supports a context window of 128,000 tokens.

How can I compare Inception: Mercury 2 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.