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How much does an AI agent cost to run Access Provisioning?

Token cost benchmark for an autonomous Access Provisioning agent, across 24 models. Prices as of 25 Oct 2026.

An agent for Access Provisioning on the clean path costs about $0.0145 to $1.45 per outcome depending on the model, around 19x the cost of a single chat message. At 10,000 outcomes a month that is roughly $145 to $14,500.
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Cost per outcome by model

Model$/1M in$/1M outCost / outcomeCost / month*
Claude Haiku 5.5$0.10$0.50$0.0145$145
GPT-6 Luna$0.10$0.50$0.0145$145
Llama 4 Maverick$0.25$0.87$0.0340$340
DeepSeek V4.1 Flash$0.30$1.20$0.0417$417
Gemini 2.5 Flash$0.30$2.50$0.0495$495
Mistral Large 3$0.50$1.50$0.0665$665
Gemini 3.8 Flash$0.75$3.75$0.109$1,088
Claude Haiku 4.5$1.00$5.00$0.145$1,450
DeepSeek V4 Pro$1.32$3.96$0.176$1,756
Mistral Large 4$1.36$4.18$0.181$1,815
Gemini 2.5 Pro$1.25$10.00$0.204$2,037
Grok 4.7$2.00$6.00$0.266$2,660
Claude Sonnet 5.5$2.00$10.00$0.290$2,900
Claude Sonnet 5$2.00$10.00$0.290$2,900
GPT-6.1 Sol$2.00$10.00$0.290$2,900
Gemini 4 Argon$2.00$10.00$0.290$2,900
Gemini 3.1 Pro$2.00$12.00$0.302$3,020
Claude Sonnet 4.6$3.00$15.00$0.435$4,350
Claude Opus 5.5$4.00$20.00$0.580$5,800
Claude Opus 5$5.00$25.00$0.725$7,250
Claude Opus 4.8$5.00$25.00$0.725$7,250
Claude Fable 5.1$10.00$50.00$1.45$14,500
Claude Fable 5$10.00$50.00$1.45$14,500
GPT-6 Astra$10.00$50.00$1.45$14,500

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

What this agent does

The clean-path steps this benchmark prices:

  1. Validate Identity & Role
  2. Valid requester?
  3. Standard entitlement?
  4. Toxic combo (SoD)?
  5. Confidence high?
  6. Provision Access
  7. Verify & Notify

What drives the cost

This path runs 7 steps: 3 tool calls and 4 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 Access Provisioning outcome costs about 19x a single chat message ($0.435 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 Access Provisioning workflow across 24 models using the same cost engine as the live estimator, at each model’s published list price (checked 25 Oct 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 Access Provisioning?

On the clean path with default assumptions, an agent for Access Provisioning costs about $0.0145 to $1.45 per outcome depending on the model, or roughly $145 to $14,500 per month at 10,000 outcomes. The cheapest model here is Claude Haiku 5.5 at $0.0145; the most expensive is GPT-6 Astra at $1.45.

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 Access Provisioning that adds up to about 19x the cost of a single chat message.

Which model is cheapest for Access Provisioning?

Across the 24 models benchmarked, Claude Haiku 5.5 is cheapest at $0.0145 per outcome and GPT-6 Astra is the most expensive at $1.45. 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 Access Provisioning?

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 Access Provisioning benchmark based on?

These are modeled estimates, not metered bills. Each figure prices a generic, representative Access Provisioning workflow across 24 models with the same cost engine as the live estimator, at each model's published list price (checked 25 Oct 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.

More ITSM benchmarks

Open Access Provisioning in the live estimator →