Last refreshed: October 5, 2026 (Pacific)
• Long-form Position
• Practitioner-grade
If you’re considering running Claude Managed Agents around the clock, you want a number. Not “it depends.” An actual number you can put in a budget. Here’s the math, worked out by scenario, with the honest caveats about where the real costs are.
The Formula
Total monthly cost = (Active session hours × $0.08) + token costs + optional tool costs
The $0.08/session-hour charge only applies during active execution. Idle time — waiting for input, tool confirmations, external API responses — doesn’t count. This matters significantly for 24/7 workloads, because very few agents are active 100% of the time even when “running around the clock.”
The Maximum Theoretical Cost
Scenario: Agent running continuously, zero idle time, 24 hours a day, 30 days a month.
- Session runtime: 24 hrs × $0.08 × 30 days = $57.60/month
- Token costs: separate, highly variable (see below)
$57.60/month is the ceiling on session runtime charges. You cannot pay more than this in session fees under any 24/7 scenario. But here’s the reality: that ceiling assumes zero idle time across the entire month, which doesn’t describe any real production agent.
Realistic 24/7 Scenarios
Monitoring Agent (High Idle Ratio)
Runs continuously watching for triggers — error alerts, specific data patterns, incoming requests. Activates on trigger, processes, returns to monitoring state.
- Assumption: 5% active execution time (watching 95% of the time, executing 5%)
- Active hours: 24 × 30 × 0.05 = 36 hours/month
- Session runtime: 36 × $0.08 = $2.88/month
- Token costs: low — moderate bursts on trigger events
- Realistic total: $5–15/month
Customer Support Agent (Business Hours Active)
“24/7” in the sense of always-available, but actual request volume concentrates in business hours. Waits for tickets, processes them, waits again.
- Assumption: 8 hours/day active execution, 16 hours waiting
- Active hours: 8 × 30 = 240 hours/month
- Session runtime: 240 × $0.08 = $19.20/month
- Token costs: depends heavily on ticket volume and average length
- At 100 tickets/day with moderate length: likely $30–80/month in tokens
- Realistic total: $50–100/month
Continuous Autonomous Pipeline
Batch processing agent that runs continuously through a queue with minimal waiting — the closest to true 24/7 active execution.
- Assumption: 20 hours/day truly active (4 hours queue exhaustion/maintenance)
- Active hours: 20 × 30 = 600 hours/month
- Session runtime: 600 × $0.08 = $48/month
- Token costs: high — continuous processing means continuous token consumption
- This is where tokens become the dominant cost driver by a significant margin
- Realistic total: $200–500+/month (tokens dominate)
The Real Variable: Token Costs
For any 24/7 workload that’s genuinely busy, token costs will substantially exceed session runtime costs. The math:
A moderately active agent processing 10,000 input tokens and 2,000 output tokens per hour with Claude Sonnet 5.5:
- Input: 10,000 tokens × $2/million = $0.02/hour
- Output: 2,000 tokens × $10/million = $0.02/hour
- Token cost: $0.04/hour vs. session runtime of $0.08/hour — the runtime charge now exceeds token cost at this volume
Scale to 100,000 input tokens and 20,000 output tokens per hour (a busy processing agent):
- Input: $0.30/hour; Output: $0.30/hour
- Token cost: $0.60/hour vs. session runtime of $0.08/hour — tokens are 7.5× the runtime charge
The session runtime fee is flat and bounded. Token costs scale with workload volume. For high-volume 24/7 agents, optimize token efficiency (prompt caching, context management, output brevity) before worrying about the session runtime charge.
Prompt Caching Changes the Token Math
If your agent has a large, stable system prompt — common in agents with extensive tool definitions or knowledge bases — prompt caching dramatically reduces input token costs. Cache hits cost a fraction of base input rates. For a 24/7 agent with a 20,000-token system prompt hitting the same context repeatedly, caching that prompt can cut input costs by up to 95% (cache reads run $0.20/MTok). The session runtime charge is unchanged, but the total cost picture improves significantly.
The Budget Summary
| Agent Type | Runtime/mo | Typical Total |
|---|---|---|
| Monitoring / low activity | ~$3 | $5–15 |
| Support agent (business hours volume) | ~$19 | $50–100 |
| Continuous processing pipeline | ~$48 | $200–500+ |
| Theoretical maximum (zero idle) | $57.60 | Unbounded (tokens) |
Complete pricing reference: Claude Managed Agents Pricing Guide. How idle time affects billing: Idle Time and Billing Explained. All questions: FAQ Hub.
Run your own 24/7 cost model from the Anthropic Console — API keys, billing, and a token-to-dollar cost estimator.
What to do next
Now that you have the cost math — here’s how to choose and implement
You now know what Managed Agents costs at scale. The next decision is whether it’s the right architecture vs. OpenAI’s equivalent — and what the implementation actually looks like in practice.
