The State of Agentic AI Costs 2026

78 workflows x 14 models, one transparent cost engine. Prices as of 7 Jul 2026.

One agent-produced outcome costs between $0.0065 and $3.85 in 2026 depending on the workflow and model, a median of 20x the cost of a single chat message. This report benchmarks the token cost of 78 common business workflows across 14 frontier and efficient models and identifies what actually drives the bill.

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Key findings

• An outcome is not a chat message. On a balanced-tier model the median workflow costs $0.473 per outcome (range $0.137 to $1.16), because the agent plans, calls tools and re-reads a growing context on every step. Multipliers vs one chat turn run from 6x (a 3-step check) to 49x (17-step Accounts Payable).
• Model choice is the biggest rate lever: a 69x median spread. On the same workflow, the dearest model costs a median of 69x the cheapest. On Accounts Payable that is $0.0559 (GPT-4o mini) vs $3.85 (Claude Fable 5) for one invoice.
• But the cheapest model is not always cheapest per successful outcome. Weaker models fail and retry more; at an 85%% first-pass success rate a model costs ~18%% more per successful outcome than its clean-run price suggests (1/0.85), while a 97%%-success frontier model adds only ~3%%. Rank models on cost per successful outcome, not per clean run.
• Complexity is the usage lever. Step count in this set runs 3 to 17; cost scales superlinearly with steps because every added call re-reads a larger context. The dearest categories by median are IT Security / SecOps, Software Engineering / DevOps and Customer Support.
• At production volume the range is a budget line. At 10,000 outcomes a month, the same workflow costs $559 to $38500 a month depending only on model choice (Accounts Payable example).
• Prompt caching remains the single biggest usage-side saving, cutting the re-read base context by ~90%% on every call.

The ten costliest workflows (balanced tier)

Median cost per outcome by business area

Method

Every figure is a modeled estimate from the ProcessRaven cost engine: generic, representative workflow graphs priced step by step (planning loops, tool calls, retrieval, sub-agents, growing context), at each model’s published list price (checked 7 Jul 2026), on documented default assumptions with prompt caching off and the clean path. Balanced tier figures use Claude Sonnet 4.6. These are illustrative pre-deployment estimates, not metered bills or financial advice; actual costs vary by configuration and workload, and token cost is one part of total AI cost. Full per-workflow, per-model figures: download the CSV or browse the live benchmark pages. Estimate your own process in the free estimator (no sign-up).

Citing this report. Please cite as “ProcessRaven, The State of Agentic AI Costs 2026” with a link to this page. The dataset is free to reuse with attribution.

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