# Pricing transcribed from the provider's own page — see provenance. Numbers are quoted, not derived.
generated: '2026-10-07'
method: searched
source: https://aws.amazon.com/rekognition/pricing/
sources:
- https://aws.amazon.com/rekognition/pricing/
provenance:
  tool: all/0-working/economics/harvest_pricing.py
  run: 20261007T104522
  grounding: every price_text was found verbatim in the fetched page text
audience: developer-api
pricing_basis: per-call
delivery:
  delivery: managed
  method: page
  read: '2026-10-07'
published: true
note: Main pricing tables render via dynamic templates ({priceOf!...}) so unit prices are not visible;
  numeric prices captured come from the page's worked pricing examples and the stated face metadata storage
  rate.
plan_count: 13
currency: USD
plans:
- name: Rekognition Image – Group 2 (DetectLabels), first 1 million images
  price_text: $0.0010 per image
  price: 0.001
  currency: USD
  period: per-use
  unit: image
  included_quota: 'Free Tier: 1,000 images per month for 12 months'
  overage: Next 1.5 million images $0.0008 per image
- name: Rekognition Image – Image Properties, first 1 million images
  price_text: $0.00075 per image
  price: 0.00075
  currency: USD
  period: per-use
  unit: image
  included_quota: Free tier is not offered for Image Properties
  overage: Next 1.5 million images $0.0006 per image
- name: Rekognition Image – higher volume tiers (example)
  price_text: $0.0006 per image
  price: 0.0006
  currency: USD
  period: per-use
  unit: image
  included_quota: Next 30 million images
  overage: Next 32 million images $0.0004 per image; Group 2 next 45 million images $0.00025 per image
- name: Face Metadata Storage
  price_text: $0.00001/face metadata per month
  price: 1.0e-05
  currency: USD
  period: month
  unit: face metadata
  included_quota: 'Free tier: 1,000 face vector objects and 1,000 user vector objects per month'
- name: Streaming video events – Label Detection (US East example)
  price_text: $0.00817/min
  price: 0.00817
  currency: USD
  period: per-use
  unit: minute
  included_quota: 'Free Tier: 60 free minutes of video analysis per month'
- name: Stored video analysis – Label Detection (us-east-1 example)
  price_text: $0.10/min
  price: 0.1
  currency: USD
  period: per-use
  unit: minute
- name: Stored video – Shot Detection (example)
  price_text: $0.05/min
  price: 0.05
  currency: USD
  period: per-use
  unit: minute
- name: Custom Labels – Training (example)
  price_text: $1 per hour
  price: 1
  currency: USD
  period: per-use
  unit: training hour
  included_quota: 'Free Tier: 2 free training hours per month'
- name: Custom Labels – Inference (example)
  price_text: $4 per hour
  price: 4
  currency: USD
  period: per-use
  unit: inference hour
  included_quota: 'Free Tier: 1 free inference hour per month'
- name: Face Liveness – first 500,000 checks (US East)
  price_text: $0.015 per check
  price: 0.015
  currency: USD
  period: per-use
  unit: check
  overage: next 2.5 million checks is $0.0125 per check, and last 1.5 million checks is $0.010 per check
- name: Custom Moderation – Training (example)
  price_text: $5 per hour
  price: 5
  currency: USD
  period: per-use
  unit: training hour
  included_quota: 2 free training hours per month
- name: Custom Moderation – Inference, first 1 million images
  price_text: $0.0012 per image
  price: 0.0012
  currency: USD
  period: per-use
  unit: image
  overage: Next 4 million images $0.00096 per image; Next 30 million images $0.00072 per image; Over 30
    million images $0.0003 per image
- name: AWS Free Tier credits
  price_text: up to $200 in AWS Free Tier credits
  price: 200
  currency: USD
  period: one-time
  unit: credits
  included_quota: Free plan available for 6 months after account creation
rate_limit_statements:
- Models that take more than 72 training hours will be automatically terminated.
- Usage is billed on minute increments, with a minimum of 1 minute.
- can analyze up to 120 seconds of video per event
x-canonical:
  generated: '2026-10-08'
  vocabulary: all/0-working/economics/plans-canonical.yml
  models:
  - hybrid
  - subscription
  units:
  - compute
  - credit
  - object
  - request
  plans:
  - name: Rekognition Image – Group 2 (DetectLabels), first 1 million images
    access: other
    model: hybrid
    model_how: derived
    units:
    - object
    periods:
    - other
  - name: Rekognition Image – Image Properties, first 1 million images
    access: other
    model: hybrid
    model_how: derived
    units:
    - object
    periods:
    - other
  - name: Rekognition Image – higher volume tiers (example)
    access: other
    model: hybrid
    model_how: derived
    units:
    - object
    periods:
    - other
  - name: Face Metadata Storage
    access: other
    model: subscription
    model_how: derived
    units:
    - other
    periods:
    - month
  - name: Streaming video events – Label Detection (US East example)
    access: other
    model: hybrid
    model_how: derived
    units:
    - compute
    periods:
    - other
  - name: Stored video analysis – Label Detection (us-east-1 example)
    access: other
    model: hybrid
    model_how: derived
    units:
    - compute
    periods:
    - other
  - name: Stored video – Shot Detection (example)
    access: other
    model: hybrid
    model_how: derived
    units:
    - compute
    periods:
    - other
  - name: Custom Labels – Training (example)
    access: other
    model: hybrid
    model_how: derived
    units:
    - compute
    periods:
    - other
  - name: Custom Labels – Inference (example)
    access: other
    model: hybrid
    model_how: derived
    units:
    - compute
    periods:
    - other
  - name: Face Liveness – first 500,000 checks (US East)
    access: other
    model: hybrid
    model_how: derived
    units:
    - request
    periods:
    - other
  - name: Custom Moderation – Training (example)
    access: other
    model: hybrid
    model_how: derived
    units:
    - compute
    periods:
    - other
  - name: Custom Moderation – Inference, first 1 million images
    access: other
    model: hybrid
    model_how: derived
    units:
    - object
    periods:
    - other
  - name: AWS Free Tier credits
    access: other
    model: hybrid
    model_how: derived
    units:
    - credit
    periods:
    - one-time