AI Token Usage Heatmap
- Published:
- Jun 15, 2026
- Updated:
- May 17, 2026
Short answer
Peak usage occurs during business hours (12:00-18:00)
| Mon | Tue | Wed | |
|---|---|---|---|
| 00:00 | 45 | 48 | 52 |
| 06:00 | 68 | 72 | 75 |
| 12:00 | 92 | 95 | 98 |
| 18:00 | 85 | 88 | 90 |
Source: API Logs
Key findings
- Peak usage occurs during business hours (12:00-18:00)
- Mid-week shows highest overall token consumption
- Weekend usage 35% lower than weekday average
Download AI-ready context
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Context file preview
The downloaded Markdown file includes:
- Key findings
- Data table
- Methodology
- Source links
- Suggested AI prompts
# AI Token Usage Heatmap
## Research Question
## Short Answer
## Key Findings
## Data Table
## How To Use This With AI
## Suggested Prompts
## Sources
## CaveatsData table
| day | hour | value |
|---|---|---|
| Mon | 00:00 | 45 |
| Mon | 06:00 | 68 |
| Mon | 12:00 | 92 |
| Mon | 18:00 | 85 |
| Tue | 00:00 | 48 |
7 more rows + CSV download
The full 12-row dataset, one-click CSV export, and the AI-ready context file are free with an account. Prefer to verify it yourself? The full methodology and sources are published below.
Analysis
AI token usage patterns closely mirror traditional business hours, suggesting that the majority of current consumption is enterprise-driven rather than consumer. The weekday concentration indicates opportunities for infrastructure cost optimization through dynamic pricing and reserved capacity models.
How to use this with AI
Use this context file to start a research conversation with an AI tool. It includes the key findings, chart data, sources, and caveats so the model starts from structured context instead of a blank prompt.
Use cases
- Build a market research memo.
- Create a short executive brief.
- Compare this topic with another sector or geography.
- Generate follow-up research questions.
- Turn the findings into a slide outline.
Suggested prompts
- Using this Deepstory context, create a market research memo with key findings, strategic implications, risks, and follow-up questions.
- Using this dataset, explain the trend, identify the likely drivers, and list the caveats that should be checked before making a decision.
- Turn this research into a 5-slide presentation outline for a business audience.
- Create 10 follow-up research questions based on the data and identify what additional sources would be useful.
Sources
- Source quality:
- Placeholder / demo data
- Last reviewed:
- Updated May 2026
- API Logs Placeholder / demo
Aggregated anonymized API usage patterns
Caveats
- This research is based on available public data and should be used as context, not as professional advice. Check source methodology before making decisions.