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How much does an AI agent cost to run Recruiting & Screening?

Token cost benchmark for an autonomous Recruiting & Screening agent, across 24 models. Prices as of 25 Oct 2026.

An agent for Recruiting & Screening on the clean path costs about $0.0150 to $1.50 per outcome depending on the model, around 19x the cost of a single chat message. At 10,000 outcomes a month that is roughly $150 to $15,000.
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Cost per outcome by model

Model$/1M in$/1M outCost / outcomeCost / month*
Claude Haiku 5.5$0.10$0.50$0.0150$150
GPT-6 Luna$0.10$0.50$0.0150$150
Llama 4 Maverick$0.25$0.87$0.0352$352
DeepSeek V4.1 Flash$0.30$1.20$0.0432$432
Gemini 2.5 Flash$0.30$2.50$0.0510$510
Mistral Large 3$0.50$1.50$0.0690$690
Gemini 3.8 Flash$0.75$3.75$0.113$1,125
Claude Haiku 4.5$1.00$5.00$0.150$1,500
DeepSeek V4 Pro$1.32$3.96$0.182$1,822
Mistral Large 4$1.36$4.18$0.188$1,883
Gemini 2.5 Pro$1.25$10.00$0.210$2,100
Grok 4.7$2.00$6.00$0.276$2,760
Claude Sonnet 5.5$2.00$10.00$0.300$3,000
Claude Sonnet 5$2.00$10.00$0.300$3,000
GPT-6.1 Sol$2.00$10.00$0.300$3,000
Gemini 4 Argon$2.00$10.00$0.300$3,000
Gemini 3.1 Pro$2.00$12.00$0.312$3,120
Claude Sonnet 4.6$3.00$15.00$0.450$4,500
Claude Opus 5.5$4.00$20.00$0.600$6,000
Claude Opus 5$5.00$25.00$0.750$7,500
Claude Opus 4.8$5.00$25.00$0.750$7,500
Claude Fable 5.1$10.00$50.00$1.50$15,000
Claude Fable 5$10.00$50.00$1.50$15,000
GPT-6 Astra$10.00$50.00$1.50$15,000

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

What this agent does

The clean-path steps this benchmark prices:

  1. Parse Role & Criteria
  2. Source Candidates
  3. Screen & Rank
  4. Qualified pool?
  5. Borderline calls?
  6. Confidence high?
  7. Schedule Interviews

What drives the cost

This path runs 7 steps: 3 tool calls, 1 reasoning step and 3 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 Recruiting & Screening outcome costs about 19x a single chat message ($0.450 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 Recruiting & Screening 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 Recruiting & Screening?

On the clean path with default assumptions, an agent for Recruiting & Screening costs about $0.0150 to $1.50 per outcome depending on the model, or roughly $150 to $15,000 per month at 10,000 outcomes. The cheapest model here is Claude Haiku 5.5 at $0.0150; the most expensive is GPT-6 Astra at $1.50.

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 Recruiting & Screening that adds up to about 19x the cost of a single chat message.

Which model is cheapest for Recruiting & Screening?

Across the 24 models benchmarked, Claude Haiku 5.5 is cheapest at $0.0150 per outcome and GPT-6 Astra is the most expensive at $1.50. 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 Recruiting & Screening?

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 Recruiting & Screening benchmark based on?

These are modeled estimates, not metered bills. Each figure prices a generic, representative Recruiting & Screening 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.

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