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Calcrivo

Compression Ratio Calculator

Calculate the compression ratio and space savings between an original file size and its compressed size.

Inputs

MB
MB

Compression Ratio

4:1

Space Savings

75.00%

Space Saved

750.00MB

Ratio (decimal)

4.000

Step by step

  1. Values used

    Original Size = 1,000 MB; Compressed Size = 250 MB

  2. Compression ratio and savings

    ratio = original_size / compressed_size; savings = (1 − 1/ratio) × 100%

  3. Compression Ratio

    = 4:1

  4. Space Savings

    = 75.00

  5. Space Saved

    = 750.00 MB

  6. Ratio (decimal)

    = 4.000

How it works

The compression ratio expresses how many times smaller a compressed file is compared to its original, calculated by dividing the original size by the compressed size — a ratio of 4:1 means the compressed file is a quarter of the original. Space savings, expressed as a percentage, is derived from the ratio as one minus its reciprocal, giving an intuitive figure for how much storage or bandwidth was reclaimed.

Formula

Compression ratio and savings

ratio = original_size / compressed_size; savings = (1 − 1/ratio) × 100%

S_o
Original size
S_c
Compressed size

Frequently Asked Questions

What does a compression ratio of 4:1 mean?

A 4:1 ratio means the original file is four times larger than the compressed version — equivalently, the compressed file occupies 25% of the original's storage or transfer footprint, a 75% space saving.

Why do some files compress better than others?

Compression algorithms exploit redundancy and predictable patterns in data. Text and uncompressed formats (BMP, WAV, raw logs) usually compress well because they contain repeated structures, while already-compressed formats (JPEG, MP4, ZIP) compress poorly because their redundancy has already been removed.

Is a higher compression ratio always better?

Not necessarily — very high ratios from lossy compression can degrade quality (images, audio, video), and higher-ratio algorithms often demand more CPU time to compress and decompress, so the right choice balances size, quality, and processing cost for the use case.

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