Analyze text encoding characteristics and compatibility

Analyze which Unicode ranges pasted text uses and compare its UTF-8, UTF-16, and UTF-32 storage sizes.

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ToolCharset Detector
Input
Output
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Preview

How it works

The browser has already decoded the paste into a JavaScript string, so code points are grouped as ASCII, Latin-1, other BMP, or supplementary while TextEncoder measures UTF-8 bytes. UTF-16 is estimated as two bytes per code unit and UTF-32 as four bytes per code point; this cannot recover the original byte encoding.

  • The four ranges expose minimum repertoire requirements rather than claiming to identify a source charset.
  • Only leading U+FEFF is reported as a retained Unicode signature; decoded U+FFFE is not labelled a reversed BOM.

Worked example

Detect ASCII
Analyze a pure ASCII string for encoding compatibility
Input
											Hello, World!
Output
												=== Encoding Analysis ===
BOM: None detected

=== Character Distribution ===
Total code points: 13
ASCII (U+0000-U+007F): 13 (100.0%)
Latin-1 (U+0080-U+00FF): 0 (0.0%)
BMP (U+0100-U+FFFF): 0 (0.0%)
Supplementary (U+10000+): 0 (0.0%)
Whitespace characters: 1

=== Encoding Compatibility ===
Compatible with: ASCII, UTF-8, Latin-1, UTF-16, UTF-32
Recommended encoding: ASCII or UTF-8

=== Size Estimates ===
UTF-8: 13 bytes
UTF-16: 26 bytes
UTF-32: 52 bytes

When to use this

Developers check seven-bit compatibility, database migrations compare storage estimates, and import investigations locate a retained leading U+FEFF.

Edge cases

  • Pure ASCII is also valid UTF-8 and ISO-8859-1, so pasted ASCII cannot reveal which compatible encoding supplied it.
  • € requires Unicode here even though Windows-1252 assigns a byte to it; that original byte history disappeared during decoding.
  • 😀 is one supplementary code point, four UTF-8 bytes, two UTF-16 units, and four estimated UTF-32 bytes.

References