See what your AI coding subscription actually gives you.

Tokens, models, effort, quota burn, and price—measured across real coding sessions. Optional check-ins tell us whether the output was worth it.

Measure what your plan actually gives you.

Install once, connect each subscription, and track prompt-free token, model, effort, and quota metadata across coding tools.

Open source, local parsing, and opt-in aggregation. No code or prompts collected. View source ↗

isaiokay
  1. 01Install the CLI
    npm install --global @isaiokay/cli

    Same CLI via npm, pnpm, or Bun.

  2. 03Use your normal CLI
    codex

    Keep using Codex, Claude, Grok, OpenCode, or another harness. Run isaiokay usage for the model-and-effort breakdown.

More setup options
Headless setup
isaiokay setup --headless

Open the link on any device. First-time auth still needs GitHub in a browser.

Connect everything detected
isaiokay install --all

Install every supported, unconfigured integration.

Preview without installing
npx --yes @isaiokay/cli --help

Also: pnpm dlx @isaiokay/cli --help or bunx @isaiokay/cli --help.

Measured from coding sessions

Best coding subscriptions right now

Token allowance, model mix, API-equivalent value, and optional result satisfaction—kept separate and confidence-weighted.

“Best” is not the biggest raw token count.Plans rank only after model prices cover ≥80% of tokens and at least 5 independent contributors opt in.Methodology
RankSubscriptionValueObserved allowanceResultsEvidence
ChatGPT GoOpenAI · $8/moPendingCollecting private sampleNot enough contributorsFewer than 5
ChatGPT PlusOpenAI · $20/moPendingCollecting private sampleNot enough contributorsFewer than 5
ChatGPT Pro 20xOpenAI · $200/moPendingCollecting private sampleNot enough contributorsFewer than 5
ChatGPT Pro 5xOpenAI · $100/moPendingCollecting private sampleNot enough contributorsFewer than 5
Claude Max 20xAnthropic · $200/moPendingCollecting private sampleNot enough contributorsFewer than 5
Claude Max 5xAnthropic · $100/moPendingCollecting private sampleNot enough contributorsFewer than 5
Claude ProAnthropic · $20/moPendingCollecting private sampleNot enough contributorsFewer than 5
Cursor ProCursor · $20/moPendingCollecting private sampleNot enough contributorsFewer than 5
Cursor Pro PlusCursor · $60/moPendingCollecting private sampleNot enough contributorsFewer than 5
Cursor Start (India)Cursor · ₹649/moPendingCollecting private sampleNot enough contributorsFewer than 5
Cursor UltraCursor · $200/moPendingCollecting private sampleNot enough contributorsFewer than 5
Devin MaxCognition · $200/moPendingCollecting private sampleNot enough contributorsFewer than 5
Devin ProCognition · $20/moPendingCollecting private sampleNot enough contributorsFewer than 5
GitHub Copilot MaxGitHub · $100/moPendingCollecting private sampleNot enough contributorsFewer than 5
GitHub Copilot ProGitHub · $10/moPendingCollecting private sampleNot enough contributorsFewer than 5
GitHub Copilot Pro+GitHub · $39/moPendingCollecting private sampleNot enough contributorsFewer than 5
Google AI ProGoogle · $20/moPendingCollecting private sampleNot enough contributorsFewer than 5
Google AI UltraGoogle · Price pending/moPendingCollecting private sampleNot enough contributorsFewer than 5
Kimi AllegrettoKimi · CN¥199/moPendingCollecting private sampleNot enough contributorsFewer than 5
Kimi AllegroKimi · CN¥699/moPendingCollecting private sampleNot enough contributorsFewer than 5
Kimi AndanteKimi · CN¥49/moPendingCollecting private sampleNot enough contributorsFewer than 5
Kimi ModeratoKimi · CN¥99/moPendingCollecting private sampleNot enough contributorsFewer than 5
OpenCode GoOpenCode · $10/moPendingCollecting private sampleNot enough contributorsFewer than 5
SuperGrokxAI · $30/moPendingCollecting private sampleNot enough contributorsFewer than 5
SuperGrok HeavyxAI · Price pending/moPendingCollecting private sampleNot enough contributorsFewer than 5
SuperGrok LitexAI · Price pending/moPendingCollecting private sampleNot enough contributorsFewer than 5
SuperGrok PlusxAI · $100/moPendingCollecting private sampleNot enough contributorsFewer than 5

Subscription value methodology

The factual layer is provider-reported token and quota metadata. Price-normalized value, confidence, and occasional satisfaction are calculated separately so a large raw counter cannot win by itself.

1

Smallest reliable usage slice

Requests, messages, or turns retain their actual model, reasoning effort, source, and separate token buckets. Mixed sessions are never assigned to one model.

Exact
Reported directly by the harness.
Inferred / estimated
Shown explicitly and discounted by confidence.
2

Comparable allowance value

Model-specific tokens are converted using prices valid when the usage occurred, then compared with the plan price. At least 80% price coverage is required.

Native view
Input, cache, output, and reasoning tokens.
Comparable view
API-equivalent value ÷ subscription price
3

Privacy and confidence gates

Plans stay Pending until five independent contributors opt in. Confidence grows with contributor breadth, complete quota windows, and exact attribution.

Strongest evidence
Complete reset-to-reset quota windows.
Change label
Observed or possible decrease, never asserted provider intent.

75% allowance value25% satisfactionconfidence shrinkage

Note: Satisfaction is optional and never changes token facts. Effort is part of the model combination—Opus high is not assumed equivalent to Sonnet high. Incomplete windows are lower bounds, not full allowance.