README.md

---
license: mit
language:
- en
tags:
- ai
- coding-agents
- pricing
- llm
- open-data
- comparison
pretty_name: AI coding plan prices (tokens and requests per dollar)
task_categories:
- question-answering
size_categories:
- n<1K
configs:
- config_name: default
  data_files:
  - split: train
    path: plans.jsonl
---

# AI coding plan prices (tokens and requests per dollar)

What the flat rate AI coding subscriptions cost, and what you actually get for the money: published
quotas, per model spending caps, included models, and the resulting tokens and requests per dollar
paid. This is the dataset behind [vibeplan.cc](https://vibeplan.cc/coding-plan-comparison/).

Snapshot of this revision: **2026-10-18 11:36 UTC**, 139 plans from 40 providers,
93 of them directly comparable, built from 30 official sources.
Disclosure split: 96 disclosed, 34 reference, 5 partial, 2 reported, 1 undisclosed, 1 measured.

## Files

- `plans.jsonl` - one plan per line, the fields described below (this is the file to load).
- `latest.json` - the complete dataset exactly as the website loads it, including the comparison
  tables, the AI score snapshot, the FX rates and the changelog.

## Columns in `plans.jsonl`

- `id`, `name`, `provider` - plan identity.
- `price` - effective monthly price in US dollars, **fees included**, plus the billing period.
- `meter`, `quotas`, `windowCaps` - the plan's own published limits (messages, tokens, requests,
  hours) and how they reset.
- `modelRows`, `modelStats` - per model rates and the per model spending caps a plan applies.
- `disclosure` - how well the plan documents its limits: `disclosed`, `partial`, `reported`,
  `reference` (kept for context, not comparable) or `undisclosed`.
- `dataTier` - A/B/M/C/D quality tier of the source situation behind that plan.
- `sourceIds`, `verifiedAt` - where each figure came from and when it was last checked.
- `notes`, `priceNote` - the plain language caveats that belong to that row.

Rates are normalised to tokens per US dollar and requests per US dollar of the price actually paid,
at a target comparison price of 1 USD.

## Loading

```python
from datasets import load_dataset
ds = load_dataset("harrytyp/ai-coding-plan-prices", split="train")
ds[0]
```

## How it is built

Rebuilt every day from around 30 official sources (provider pricing pages, docs,
plan pages) by the pipeline in the
[source repository](https://github.com/harrytyp/coding-plan-comparison). The build never guesses a
number: where a provider does not publish a quota, the field stays empty and the plan is marked as
not comparable instead of being estimated. Prices include card and processing fees, so the figure is
what you actually pay.

## Limits, stated plainly

- Only plans that publish a hard recurring limit are comparable, 93 of 139 at this snapshot.
  Providers with vague or unpublished caps stay out of the rankings on purpose.
- `reference` rows are documented plans that cannot be ranked (for example because nothing is
  published about the included amount).
- API prices per token are a different question and are not part of this dataset.
- Promotional pricing exists (first month discounts, annual billing). The dataset keeps the
  effective monthly price and the billing period rather than hiding it in a single number.

## License and citation

MIT, same as the site. Numbers change daily, so cite with a link to
[https://vibeplan.cc/](https://vibeplan.cc/) rather than copying figures.
Corrections and source suggestions: [issues](https://github.com/harrytyp/coding-plan-comparison/issues).