HomeBenchmarksData & Analytics › Report Generation
Data & Analytics

How much does an AI agent cost to run Report Generation?

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

An agent for Report Generation on the clean path costs about $0.0212 to $1.48 per outcome depending on the model, around 19x the cost of a single chat message. At 10,000 outcomes a month that is roughly $212 to $14,750.
Estimate your own numbers →

Cost per outcome by model

Model$/1M in$/1M outCost / outcomeCost / month*
GPT-4o mini$0.15$0.60$0.0212$212
Llama 4 Maverick$0.27$0.85$0.0368$368
Gemini 2.5 Flash$0.30$2.50$0.0503$503
DeepSeek V4$0.43$0.87$0.0563$563
GPT-4.1 mini$0.40$1.60$0.0566$566
Mistral Large 3$0.50$1.50$0.0677$677
Qwen3.5 397B$0.60$3.60$0.0921$921
Kimi K2.6$0.95$4.00$0.136$1,356
Claude Haiku 4.5$1.00$5.00$0.148$1,475
Grok 4.3$1.25$2.50$0.162$1,619
Qwen3.7 Max$1.25$3.75$0.169$1,694
GLM-5.2$1.40$4.40$0.191$1,909
Gemini 2.5 Pro$1.25$10.00$0.207$2,069
Mistral Medium 3.5$1.50$7.50$0.221$2,213
Gemini 3.5 Flash$1.50$9.00$0.230$2,302
GPT-4.1$2.00$8.00$0.283$2,830
Claude Sonnet 5$2.00$10.00$0.295$2,950
GPT-4o$2.50$10.00$0.354$3,538
GPT-5.4$2.50$15.00$0.384$3,838
GPT-5.6 Terra$2.50$15.00$0.384$3,838
Claude Sonnet 4.6$3.00$15.00$0.443$4,425
Kimi K3$3.00$15.00$0.443$4,425
Claude Opus 4.8$5.00$25.00$0.738$7,375
GPT-5.5$5.00$30.00$0.768$7,675
GPT-5.6 Sol$5.00$30.00$0.768$7,675
Claude Fable 5$10.00$50.00$1.48$14,750

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

What this agent does

The clean-path steps this benchmark prices:

  1. Resolve Metrics & Sources
  2. Query Data
  3. Data available?
  4. Build Report & Viz
  5. Sanity check passed?
  6. Confidence high?
  7. Publish Report

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 Report Generation outcome costs about 19x a single chat message ($0.443 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 Report Generation 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 Report Generation?

On the clean path with default assumptions, an agent for Report Generation costs about $0.0212 to $1.48 per outcome depending on the model, or roughly $212 to $14,750 per month at 10,000 outcomes. The cheapest model here is GPT-4o mini at $0.0212; the most expensive is Claude Fable 5 at $1.48.

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 Report Generation that adds up to about 19x the cost of a single chat message.

Which model is cheapest for Report Generation?

Across the 26 models benchmarked, GPT-4o mini is cheapest at $0.0212 per outcome and Claude Fable 5 is the most expensive at $1.48. 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 Report Generation?

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 Report Generation benchmark based on?

These are modeled estimates, not metered bills. Each figure prices a generic, representative Report Generation 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.

More Data & Analytics benchmarks

Beyond cost: is it ready, and can you govern it?

Cost is one axis. Before you build, check the process is ready for AI and that you can prove you govern it. See how governed AI process animations work →

Open Report Generation in the live estimator →