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How much does an AI agent cost to run Returns & Refunds?

Token cost benchmark for an autonomous Returns & Refunds agent, across 26 models. Prices as of 26 Jul 2026.

An agent for Returns & Refunds on the clean path costs about $0.0287 to $1.99 per outcome depending on the model, around 25x the cost of a single chat message. At 10,000 outcomes a month that is roughly $287 to $19,870.
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Cost per outcome by model

Model$/1M in$/1M outCost / outcomeCost / month*
GPT-4o mini$0.15$0.60$0.0287$287
Llama 4 Maverick$0.27$0.85$0.0500$500
Gemini 2.5 Flash$0.30$2.50$0.0668$668
GPT-4.1 mini$0.40$1.60$0.0766$766
DeepSeek V4$0.43$0.87$0.0770$770
Mistral Large 3$0.50$1.50$0.0921$922
Qwen3.5 397B$0.60$3.60$0.124$1,235
Kimi K2.6$0.95$4.00$0.183$1,834
Claude Haiku 4.5$1.00$5.00$0.199$1,987
Grok 4.3$1.25$2.50$0.221$2,214
Qwen3.7 Max$1.25$3.75$0.230$2,304
GLM-5.2$1.40$4.40$0.259$2,595
Gemini 2.5 Pro$1.25$10.00$0.275$2,754
Mistral Medium 3.5$1.50$7.50$0.298$2,980
Gemini 3.5 Flash$1.50$9.00$0.309$3,088
GPT-4.1$2.00$8.00$0.383$3,830
Claude Sonnet 5$2.00$10.00$0.397$3,974
GPT-4o$2.50$10.00$0.479$4,788
GPT-5.4$2.50$15.00$0.515$5,148
GPT-5.6 Terra$2.50$15.00$0.515$5,148
Claude Sonnet 4.6$3.00$15.00$0.596$5,961
Kimi K3$3.00$15.00$0.596$5,961
Claude Opus 4.8$5.00$25.00$0.994$9,935
GPT-5.5$5.00$30.00$1.03$10,295
GPT-5.6 Sol$5.00$30.00$1.03$10,295
Claude Fable 5$10.00$50.00$1.99$19,870

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

What this agent does

The clean-path steps this benchmark prices:

  1. Look Up Order
  2. Within policy?
  3. Check Abuse Signals
  4. Abuse risk?
  5. Refund value material?
  6. Confidence high?
  7. Process Refund
  8. Confirm & Notify

What drives the cost

This path runs 8 steps: 4 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 Returns & Refunds outcome costs about 25x a single chat message ($0.596 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 Returns & Refunds 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 Returns & Refunds?

On the clean path with default assumptions, an agent for Returns & Refunds costs about $0.0287 to $1.99 per outcome depending on the model, or roughly $287 to $19,870 per month at 10,000 outcomes. The cheapest model here is GPT-4o mini at $0.0287; the most expensive is Claude Fable 5 at $1.99.

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 Returns & Refunds that adds up to about 25x the cost of a single chat message.

Which model is cheapest for Returns & Refunds?

Across the 26 models benchmarked, GPT-4o mini is cheapest at $0.0287 per outcome and Claude Fable 5 is the most expensive at $1.99. 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 Returns & Refunds?

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 Returns & Refunds benchmark based on?

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