Context Window
128,000
Tokens
Model Cost Profile
Inception: Mercury
Developer: inception
Pricing updated Mar 11, 2026
Input rank: #154Output rank: #147
Inception: Mercury features an extensive context window of 128,000 tokens, making it ideal for applications requiring in-depth analysis of long documents or complex datasets. Teams utilizing this API model can expect input costs of $0.25 per million tokens and output costs of $1.00 per million tokens, allowing for scalable budgeting based on usage needs. This model is particularly useful for industries such as legal, research, and content creation, where comprehensive understanding and generation of large text volumes are essential.
🔧 Tool Calling📋 Structured Output
Input Price / 1M
$0.2500
Prompt tokens
Output Price / 1M
$0.7500
Completion tokens
Intelligence (MMLU)
Benchmark Pending
Massive Multitask Language Understanding
Side-by-Side Pricing Table
| Usage Type | Price / 1M Tokens |
|---|---|
| Input (Prompt) | $0.2500 |
| Output (Completion) | $0.7500 |
Price History
Inception: Mercury Pricing Trend
Input / 1M tokens0.0%Output / 1M tokens0.0%
Mar 7 — Mar 11
Current Input / 1M
$0.2500
Current Output / 1M
$0.7500
Cost Calculator
Estimate monthly spend for Inception: Mercury based on your workload.
01.0B
0500M
Estimated Monthly Cost
$15
25M input + 12M output tokens
Cheaper Alternatives to Compare
Quick links for cost-down decisions before production rollout.
FAQ
Common pricing and benchmark questions for Inception: Mercury.
How much does Inception: Mercury cost per 1M input tokens?
Inception: Mercury input pricing is $0.2500 per 1M tokens based on the latest synced provider data.
How much does Inception: Mercury cost per 1M output tokens?
Inception: Mercury output pricing is $0.7500 per 1M tokens based on the latest synced provider data.
What context window does Inception: Mercury support?
Inception: Mercury supports a context window of 128,000 tokens.
How can I compare Inception: Mercury 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.