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Software Engineering / DevOps

How much does an AI agent cost to run On-call Runbook?

Token cost benchmark for an autonomous On-call Runbook agent, across 26 models. Prices as of 26 Jul 2026.

An agent for On-call Runbook on the clean path costs about $0.0459 to $3.16 per outcome depending on the model, around 40x the cost of a single chat message. At 10,000 outcomes a month that is roughly $459 to $31,580.
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Cost per outcome by model

Model$/1M in$/1M outCost / outcomeCost / month*
GPT-4o mini$0.15$0.60$0.0459$459
Llama 4 Maverick$0.27$0.85$0.0805$805
Gemini 2.5 Flash$0.30$2.50$0.104$1,043
GPT-4.1 mini$0.40$1.60$0.122$1,225
DeepSeek V4$0.43$0.87$0.125$1,248
Mistral Large 3$0.50$1.50$0.148$1,483
Qwen3.5 397B$0.60$3.60$0.195$1,952
Kimi K2.6$0.95$4.00$0.293$2,928
Claude Haiku 4.5$1.00$5.00$0.316$3,158
Grok 4.3$1.25$2.50$0.359$3,588
Qwen3.7 Max$1.25$3.75$0.371$3,708
GLM-5.2$1.40$4.40$0.417$4,172
Gemini 2.5 Pro$1.25$10.00$0.431$4,308
Mistral Medium 3.5$1.50$7.50$0.474$4,737
Gemini 3.5 Flash$1.50$9.00$0.488$4,881
GPT-4.1$2.00$8.00$0.612$6,124
Claude Sonnet 5$2.00$10.00$0.632$6,316
GPT-4o$2.50$10.00$0.765$7,655
GPT-5.4$2.50$15.00$0.814$8,135
GPT-5.6 Terra$2.50$15.00$0.814$8,135
Claude Sonnet 4.6$3.00$15.00$0.947$9,474
Kimi K3$3.00$15.00$0.947$9,474
Claude Opus 4.8$5.00$25.00$1.58$15,790
GPT-5.5$5.00$30.00$1.63$16,270
GPT-5.6 Sol$5.00$30.00$1.63$16,270
Claude Fable 5$10.00$50.00$3.16$31,580

*At 10,000 outcomes per month. Cheapest model highlighted.

What this agent does

The clean-path steps this benchmark prices:

  1. Acknowledge Page
  2. Pull Telemetry
  3. Real issue?
  4. Runbook exists?
  5. Run Runbook Diagnostics
  6. Cause found?
  7. Customer- impacting?
  8. Safe auto- mitigation?
  9. Apply Mitigation
  10. Verify Recovery
  11. Recovered?

What drives the cost

This path runs 11 steps: 5 tool calls and 6 decision points. Tool steps make two model calls each, and the agent re-reads its growing context on every call. That compounding is why one On-call Runbook outcome costs about 40x a single chat message ($0.947 on Claude Sonnet 4.6), not the price of one message.

Why these numbers matter.

How this benchmark is calculated

These figures are modeled estimates, not metered bills. We price a generic, representative On-call Runbook workflow across 26 models using the same cost engine as the live estimator, at each model’s published list price (checked 26 Jul 2026), under documented default assumptions for planning loops, tool calls, memory retrieval, sub-agents and context size. Your own process will differ, so use these as starting points, tune the assumptions in the estimator, and validate against your real usage. Illustrative estimates, not financial advice.

Frequently asked questions

How much does an AI agent cost to run On-call Runbook?

On the clean path with default assumptions, an agent for On-call Runbook costs about $0.0459 to $3.16 per outcome depending on the model, or roughly $459 to $31,580 per month at 10,000 outcomes. The cheapest model here is GPT-4o mini at $0.0459; the most expensive is Claude Fable 5 at $3.16.

Why does an AI agent cost more than a single chatbot message?

An agent does not make one model call. It plans, calls tools, retrieves context and re-reads its growing working context on every step. For On-call Runbook that adds up to about 40x the cost of a single chat message.

Which model is cheapest for On-call Runbook?

Across the 26 models benchmarked, GPT-4o mini is cheapest at $0.0459 per outcome and Claude Fable 5 is the most expensive at $3.16. A cheaper model is not always the right choice, but it sets the floor for this workflow.

How can I reduce the cost of an agent for On-call Runbook?

The biggest levers are prompt caching on the base context, fewer planning loops, smaller tool results, less retrieval, and choosing a cheaper model where quality allows. You can test each lever in the live estimator.

What is this On-call Runbook benchmark based on?

These are modeled estimates, not metered bills. Each figure prices a generic, representative On-call Runbook workflow across 26 models with the same cost engine as the live estimator, at each model's published list price (checked 26 Jul 2026), under documented default assumptions for planning loops, tool calls, memory retrieval, sub-agents and context size. Your own process will differ, so treat these as starting points, tune them in the estimator, and validate against your own usage.

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