Methodology

How the charts are estimated

Site charts compare a typical frontier cloud path with Vivral’s on-device path. Numbers are estimates for comparison — not a bill guarantee.

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What we compare

Charts on the home, pricing, and environment pages use one shared model: a full exchange of about ~3,000 tokens (input + output), treated as one “query” or “exchange.”

Usage cost (pricing & home)

  • Vivral Standard is shown at $3.99/month — the monthly subscription price the charts use.
  • Limited frontier plan is a typical consumer chat subscription of about $20/month. These plans are rate-capped / message-limited, not unlimited.
  • Unlimited frontier path uses public API token prices: average of GPT-5-class and Claude flagship rates (~$5 / ~$27.50 per million input/output tokens). At a ~2:1 input:output mix that blends to about $12.50 per million tokens.
  • Daily companion volume: about 40 exchanges/day × ~3,000 tokens ≈ 3.6 million tokens/month → about $45/month, or ~$540/year.
  • That is roughly 11× Vivral Standard’s $47.88/year ($3.99 × 12).

Energy (environment)

  • Frontier models are treated as ~3–4 trillion parameters class (interactive serving with data-center overhead).
  • Cloud path energy is estimated at about 4.0 Wh (0.004 kWh) per exchange, scaled from published large-model energy measurements plus cooling (PUE) and network overhead.
  • Vivral routine inference is modeled as on-device on iPhone GPUs (Neural Engine / GPU path), about 0.14 Wh per exchange under our mobile inference assumptions.
  • That is about 96% less energy per query (~28× lower).

Electricity price

Where we convert on-device energy to dollars, we use average New Jersey residential electricity (about 23.5¢/kWh, EIA). At ~1,200 queries/month that is only about $0.04/month of electricity — negligible next to a $3.99 subscription — so usage-cost charts show the flat Vivral Standard price.

We do not publish internal model size on marketing charts; the point is architecture (remote frontier serving vs local inference), not a parameter count.

Token prices, usage habits, and hardware efficiency change over time. Charts are meant to show the shape of the cost and energy difference for frequent, consumer-scale use.

Nair Engineering