Calculator
Paste a JSON payload, choose output assumptions, and estimate compact, formatted, encoded, compressed, and batch transfer sizes.
Example Data Table
| Example Payload | Compact Size | Pretty Size | Formatting Increase | Notes |
|---|---|---|---|---|
| User Profile API | 146 bytes | 231 bytes | 85 bytes | Small nested document with short strings. |
| Catalog Payload | 648 bytes | 1,578 bytes | 930 bytes | Repeated product objects raise total payload bytes. |
| Event Log Batch | 1,120 bytes | 2,018 bytes | 898 bytes | Frequent log batches benefit strongly from compression. |
Formula Used
Compact Size = byte length of the minified JSON string after applying the selected escaping rules.
Pretty Size = byte length of formatted JSON with indentation and line breaks.
Encoded Size = byte length after converting compact JSON into the selected encoding, plus BOM when enabled.
Base64 Size = 4 × ceil(Encoded Size ÷ 3)
Batch Total = (Encoded Size + Transport Overhead) × Payload Count
Savings % = ((Compact Size − Gzip Size) ÷ Compact Size) × 100
How to Use This Calculator
- Paste a valid JSON document into the payload box.
- Select the target encoding used by your database, API, or file export flow.
- Enter the number of repeated payloads for batch estimation.
- Add any per-payload protocol overhead, such as headers or framing bytes.
- Choose whether to include a BOM and whether to keep Unicode or slashes unescaped.
- Press Estimate JSON Size to view results above the form.
- Review the size cards, structure metrics, and graph.
- Download the calculation report as CSV or PDF when needed.
FAQs
1. What affects JSON size the most?
Repeated keys, long string values, nested structures, whitespace, and escaping rules usually create the largest size changes. Encoding choice and protocol overhead also matter during transmission.
2. Why is pretty JSON larger than compact JSON?
Pretty JSON adds spaces, indentation, and line breaks. Those characters improve readability for humans, but they increase byte count for files, APIs, and message queues.
3. Does UTF-16 always double the size?
Often, but not always. ASCII-heavy content commonly grows because characters use more bytes. Some character sets may behave differently depending on the payload and encoding details.
4. What does Base64 estimation show?
It estimates payload size after binary-safe text wrapping. Base64 is convenient for transport, but it expands the encoded data and usually increases storage or transfer cost.
5. Why include transport overhead?
Real systems send more than raw payload bytes. Framing, wrappers, queue metadata, or custom envelopes can add fixed cost to every transmitted JSON document.
6. Is gzip size exact?
It is a practical estimate based on compressed compact JSON. Actual network compression can vary with headers, server settings, dictionaries, and combined payload behavior.
7. Can this help with API optimization?
Yes. You can compare compact, encoded, and compressed sizes to decide whether trimming keys, removing fields, batching differently, or changing transport settings saves bandwidth.
8. Does invalid JSON work here?
No. The parser validates the payload first. If syntax is broken, the calculator shows an error so you can fix the input before estimating size.