Humanoid Labor ROI Calculator

The honest payback: realized FTE (scope × utilization × success), effective $/productive-hour, and the AI-ops layer other calculators skip.

Payback period
47 mo
Robot vs human / hr
$11.45 vs $45
Payback = upfront ÷ net annual cash saving. Robot $/hr is all-in per PRODUCTIVE hour — not the marketing $2/hr.
What this calculator does

The honest humanoid-robot ROI: payback period, effective cost per PRODUCTIVE hour vs fully-loaded human labor, realized FTE (scope x utilization x success), and the recurring AI/model-ops layer other calculators omit.

Why use it
  • Every other humanoid-ROI calculator assumes the robot replaces 1.0 FTE at 100% uptime; the 2026 reality is 0.3-1.0 FTE at 60-85% utilization - this models what the robot actually delivers.
  • The marketing figure is ~$2/hr; the honest all-in cost per productive hour is far higher once depreciation, integration, maintenance, and AI-ops are counted - and only that number beats wages.
  • No humanoid calculator prices the recurring AI/model-ops layer; this one pulls it from the AI Robot Fleet Cost engine so the payback is not over-optimistic.

New to this calculator? Start with the ⚡ Playground — a few sliders, instant ballpark. Then switch to the 🧮 Calculator for your exact number.

Two ways to use this: visualize in the Playground, then get your number in the Calculator.

▶Playground A quick, visual way to see which factors move your humanoid payback period the most. Open the playground → ▤Calculator Enter your real workload for a precise humanoid payback period you can apply to your own usage. Go to the calculator →
Humanoid ROI Playground
Drag utilization, FTE replaced, and labor cost to see the payback move.
When does a humanoid robot pay for itself - honestly?

Drag utilization, FTE replaced, and labor cost to see the payback. The full calculator adds price, integration, maintenance, and the AI-ops layer.

5-year net
—
Change the input sliders below to see new estimates.

How we got this estimate
—

💡Realized FTE = scope x utilization x success; higher-wage roles and higher utilization pay back far faster. The headline is the 5-year net; the hero is the payback month.

Full calculator — your exact deployment

Set your robot economics and the labor it actually displaces.
🎮 Interactive Guide & Calculator Playground →
📊 Not sure of a value? Fields with a ▾ Typical pill offer broad industry ballparks (sourced typical ranges; Humanoid ROI (2026): price $16-300K; operating ~$2/hr; loaded labor warehouse $40-60K / mfg $45-156K; robot replaces 0.3-1.0 FTE at 60-85% utilization; payback 6-36mo. * = market midpoint.) so you can move forward now — your result gets more accurate as you replace them with your own measured numbers. Values marked * are rough estimates.
Payback 47 months

Payback in 47 months — long; raise utilization, FTE coverage, or target a higher-wage role.

Robot (effective)
$11.45/productive-hr
all-in incl AI-ops · 0.52 FTE realized
Human (loaded)
$45/hr
fully-loaded labor displaced
Net annual savings
$6007.76
5-year net
$30038.8
5-year ROI
29%
Upfront
$105000

Realized FTE 0.52 = scope 0.7 × utilization × success. Other humanoid-ROI calculators assume 1.0 FTE at 100% uptime — this is the honest number.

Recurring AI/model-ops carried: $223.22/robot/mo (ai-robot-fleet-cost (shared model, fleet of 50)) — the layer no other humanoid calculator includes.

  • Task-scope 0.7 FTE x 78% util x 96% success = 0.52 FTE realized (2026: 0.3-0.5 early, 0.8-1.0 mature); other calculators assume 1.0 at 100% uptime. *
  • Utilization 78% and task success 96% discount raw hours to PRODUCTIVE hours; cost/hr beats wages only above ~60-70% util. *
  • AI/model-ops = $223.22/robot/mo (ai-robot-fleet-cost (shared model, fleet of 50)) — the recurring layer no humanoid-ROI calculator includes. *
  • Operating ~$2/hr (energy/software) + $10000/yr maintenance; integration $15000 can equal hardware. *
  • Excludes Section 179 tax benefit, financing, and non-labor value (e.g. defect reduction, hazardous-task avoidance). *
📖 Data sources & methodology 163 text models · 9 embeddings · 37 vision · 55 audio · 8 vector DBs across 10 vendor pages · last verified 2026-07-28

Methodology

  • All prices are USD per 1 million tokens, current as of 2026-07-28.
  • Vendor-published values have no mark. Inferred/extrapolated values are marked with * and listed below.
  • Batch API discounts are 50% off standard rates across providers that offer Batch mode.
  • Prompt caching discounts vary by provider (typically 80-90% off cached input tokens).
  • Regional data-residency surcharges (Anthropic 1.1x, OpenAI 1.1x, Google regional tiers) are NOT included in base rates.
  • Long-context pricing tiers apply when input exceeds model threshold.
  • Embedding prices are input-only (no output tokens generated).

Primary sources

Last-verified date is the most recent successful daily snapshot (aicost_pricing_snapshots) or, when no snapshot exists yet, the latest successful crawler run (aicost_crawler_runs). 10 of 10 vendors are currently verified. Aggregator services (TokenCost, AI Pricing Guru, etc.) are not listed.

Anthropic
2026-07-28
https://www.anthropic.com/pricing
Daily snapshot since Sep 2023 · 631 days captured
Anthropic Docs
2026-07-28
https://platform.claude.com/docs/en/about-claude/pricing
Daily snapshot since Sep 2023 · 631 days captured
OpenAI
2026-07-28
https://openai.com/api/pricing/
Daily snapshot since Sep 2023 · 632 days captured
Google AI
2026-07-28
https://ai.google.dev/gemini-api/docs/pricing
Daily snapshot since Dec 2023 · 607 days captured
Google Vertex
2026-07-28
https://cloud.google.com/vertex-ai/generative-ai/pricing
Daily snapshot since Dec 2023 · 607 days captured
DeepSeek
2026-07-28
https://api-docs.deepseek.com/quick_start/pricing
Daily snapshot since May 2024 · 546 days captured
xAI
2026-07-28
https://x.ai/api
Daily snapshot since Nov 2024 · 464 days captured
Mistral
2026-07-28
https://mistral.ai/pricing
Daily snapshot since Dec 2023 · 605 days captured
Cohere
2026-07-28
https://cohere.com/pricing
Daily snapshot since Sep 2023 · 631 days captured
Voyage AI
2026-07-28
https://docs.voyageai.com/docs/pricing

Inferred values (marked with * in calculator tables)

Derived from industry conventions, not directly published by the vendor. Typical conventions: cached input = 10% of base (90% off), Batch API = 50% of base (50% off).

Vendor / Model Field Why it’s inferred
Anthropic — Claude Sonnet 4.6 cachedInput Derived at 10% of input rate — Anthropic publishes 90% cache-hit discount on this tier.
Anthropic — Claude Sonnet 4.5 cachedInput Derived at 10% of input rate; same 90% cache-hit convention as Sonnet 4.6.
Anthropic — Claude Sonnet 4.5 batchInput Derived at 50% of standard input — Anthropic documents uniform 50% Batch discount.
Anthropic — Claude Sonnet 4.5 batchOutput Derived at 50% of standard output — Anthropic documents uniform 50% Batch discount.
Anthropic — Claude Haiku 4.5 cachedInput Derived at 10% of input rate — Anthropic 90% cache-hit discount convention.
OpenAI — GPT-5.4 Mini cachedInput Derived at 10% of input — OpenAI documents automatic 90% discount on cache hits across GPT-5.x tier.
OpenAI — GPT-5.4 Nano cachedInput Derived at 10% of input — OpenAI 90% cache-hit convention.
OpenAI — GPT-5.4 Nano batchInput Derived at 50% of input — OpenAI Batch API uniform 50% discount.
OpenAI — GPT-5.4 Nano batchOutput Derived at 50% of output — OpenAI Batch API uniform 50% discount.
OpenAI — GPT-5.4 Pro cachedInput Derived at 10% of input — OpenAI 90% cache-hit convention.
OpenAI — GPT-5.4 Pro batchInput Derived at 50% of input — OpenAI Batch API uniform 50% discount.
OpenAI — GPT-5.4 Pro batchOutput Derived at 50% of output — OpenAI Batch API uniform 50% discount.
OpenAI — GPT-5.2 cachedInput Derived at 10% of input; no residency uplift.
OpenAI — GPT-5.2 batchInput Derived at 50% of input.
OpenAI — GPT-5.2 batchOutput Derived at 50% of output.
OpenAI — GPT-5 cachedInput Derived at 10% of input.
OpenAI — GPT-5 batchInput Derived at 50% of input.
OpenAI — GPT-5 batchOutput Derived at 50% of output.
OpenAI — GPT-5.5 Pro cachedInput Derived at 10% of input — OpenAI does not publish a cached rate for *-pro models; using the family convention.
OpenAI — GPT-5.5 Pro batchInput Derived at 50% of input.
OpenAI — GPT-5.5 Pro batchOutput Derived at 50% of output.
OpenAI — GPT-5.2 Pro cachedInput Derived at 10% of input — pro-tier convention.
OpenAI — GPT-5.2 Pro batchInput Derived at 50% of input.
OpenAI — GPT-5.2 Pro batchOutput Derived at 50% of output.
OpenAI — GPT-5.1 batchInput Derived at 50% of input.
OpenAI — GPT-5.1 batchOutput Derived at 50% of output.
OpenAI — GPT-5 Pro batchInput Derived at 50% of input.
OpenAI — GPT-5 Pro batchOutput Derived at 50% of output.
OpenAI — GPT-5 Nano cachedInput Derived at 10% of input.
OpenAI — GPT-5 Nano batchInput Derived at 50% of input.
OpenAI — GPT-5 Nano batchOutput Derived at 50% of output.
Google — Gemini 3 Flash cachedInput Derived at 10% of input — Google caching discount convention ~90%.
Google — Gemini 3.1 Flash-Lite cachedInput Derived at 10% of input — Google caching convention.
Google — Gemini 3.1 Flash-Lite batchInput Derived at 50% of input — Google Batch API uniform 50% discount.
Google — Gemini 3.1 Flash-Lite batchOutput Derived at 50% of output — Google Batch API uniform 50% discount.
Google — Gemini 2.5 Pro cachedInput Derived at 10% of input.
Google — Gemini 2.5 Flash cachedInput Derived at 10% of input.
Google — Gemini 2.5 Flash-Lite cachedInput Derived at 10% of input — Google caching convention.
Google — Gemini 2.5 Flash-Lite batchInput Derived at 50% of input — Google Batch API uniform 50% discount.
Google — Gemini 2.5 Flash-Lite batchOutput Derived at 50% of output — Google Batch API uniform 50% discount.
Google — Gemini 2.0 Flash cachedInput Derived at 25% of input per Google 2.0 family caching rates.
Google — Gemini 2.0 Flash batchInput Derived at 50% of input — Google Batch API uniform 50% discount.
Google — Gemini 2.0 Flash batchOutput Derived at 50% of output — Google Batch API uniform 50% discount.
Google — Gemini 2.0 Flash-Lite cachedInput Derived at 10% of input — Google caching convention.
Google — Gemini 2.0 Flash-Lite batchInput Derived at 50% of input — Google Batch API uniform 50% discount.
Google — Gemini 2.0 Flash-Lite batchOutput Derived at 50% of output — Google Batch API uniform 50% discount.
xAI — Grok 4 (legacy) cachedInput Extrapolated at 25% of base.

Pricing is cross-verified against the LiteLLM community registry when available. Daily snapshots are kept in aicost_pricing_snapshots; every change is logged to aicost_price_changelog with old & new values for full audit trail. Read the full methodology →