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How much does an AI agent cost to run Vendor Onboarding?

Token cost benchmark for an autonomous Vendor Onboarding agent, across 26 models. Prices as of 26 Jul 2026.

An agent for Vendor Onboarding on the clean path costs about $0.0242 to $1.68 per outcome depending on the model, around 22x the cost of a single chat message. At 10,000 outcomes a month that is roughly $242 to $16,780.
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Cost per outcome by model

Model$/1M in$/1M outCost / outcomeCost / month*
GPT-4o mini$0.15$0.60$0.0242$242
Llama 4 Maverick$0.27$0.85$0.0420$420
Gemini 2.5 Flash$0.30$2.50$0.0569$569
DeepSeek V4$0.43$0.87$0.0644$644
GPT-4.1 mini$0.40$1.60$0.0645$645
Mistral Large 3$0.50$1.50$0.0773$773
Qwen3.5 397B$0.60$3.60$0.105$1,046
Kimi K2.6$0.95$4.00$0.154$1,545
Claude Haiku 4.5$1.00$5.00$0.168$1,678
Grok 4.3$1.25$2.50$0.185$1,850
Qwen3.7 Max$1.25$3.75$0.193$1,933
GLM-5.2$1.40$4.40$0.218$2,178
Gemini 2.5 Pro$1.25$10.00$0.235$2,345
Mistral Medium 3.5$1.50$7.50$0.252$2,517
Gemini 3.5 Flash$1.50$9.00$0.262$2,616
GPT-4.1$2.00$8.00$0.322$3,224
Claude Sonnet 5$2.00$10.00$0.336$3,356
GPT-4o$2.50$10.00$0.403$4,030
GPT-5.4$2.50$15.00$0.436$4,360
GPT-5.6 Terra$2.50$15.00$0.436$4,360
Claude Sonnet 4.6$3.00$15.00$0.503$5,034
Kimi K3$3.00$15.00$0.503$5,034
Claude Opus 4.8$5.00$25.00$0.839$8,390
GPT-5.5$5.00$30.00$0.872$8,720
GPT-5.6 Sol$5.00$30.00$0.872$8,720
Claude Fable 5$10.00$50.00$1.68$16,780

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

What this agent does

The clean-path steps this benchmark prices:

  1. Collect Vendor Docs
  2. Verify (tax, bank, sanctions)
  3. Records valid?
  4. Assess Risk
  5. High- risk?
  6. Material spend?
  7. Confidence high?
  8. Create Vendor Record

What drives the cost

This path runs 8 steps: 3 tool calls, 1 reasoning step 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 Vendor Onboarding outcome costs about 22x a single chat message ($0.503 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 Vendor Onboarding 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 Vendor Onboarding?

On the clean path with default assumptions, an agent for Vendor Onboarding costs about $0.0242 to $1.68 per outcome depending on the model, or roughly $242 to $16,780 per month at 10,000 outcomes. The cheapest model here is GPT-4o mini at $0.0242; the most expensive is Claude Fable 5 at $1.68.

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 Vendor Onboarding that adds up to about 22x the cost of a single chat message.

Which model is cheapest for Vendor Onboarding?

Across the 26 models benchmarked, GPT-4o mini is cheapest at $0.0242 per outcome and Claude Fable 5 is the most expensive at $1.68. 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 Vendor Onboarding?

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 Vendor Onboarding benchmark based on?

These are modeled estimates, not metered bills. Each figure prices a generic, representative Vendor Onboarding 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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