Cache Hit Rate Calculator
Measure cache hit rate and the origin requests it avoids.
About Cache Hit Rate Calculator
The cache hit rate is the share of total lookups that cache hits represents, expressed as a percentage. The same figure is also shown per 1,000 and as a "one in every N" odds statement, which is easier to reason about when the rate is very small. Absolute counts hide scale — a rate normalises the number so you can compare periods, channels or cohorts of different sizes, where higher is better.
Formula
Cache Hit Rate
Cache Hit Rate = Cache hits ÷ Total lookups × 100
- Cache hits
- The subset being measured
- Total lookups
- The full population it is drawn from
Worked example
With the default values below, Cache Hit Rate Calculator returns Cache Hit Rate of 91.50%. Change any input above and every figure here is recalculated in your browser.
Inputs used
- Cache hitsminimum 0
- 91,500
- Total lookupsminimum 0
- 100,000
Results
- Cache Hit Rate
- 91.50%
- Remaining (whole minus part)
- 8,500
- Equivalent per 1,000
- 915.0
- One in Every
- 1.1
Step by step
- 1Values used
- 2Cache Hit Rate
- 3Cache Hit Rate= 91.50
- 4Remaining (whole minus part)= 8,500
- 5Equivalent per 1,000= 915.0
- 6One in Every= 1.1
Assumptions and limits
- The result is derived only from the 2 inputs listed above. Anything not among them is not part of the calculation.
- In particular, this calculator does not take inflation, tax, fees or charges or compounding frequency into account.
- Figures are rounded for display to 2 decimal places, so totals built from several rounded parts can differ slightly from the unrounded arithmetic.
How these calculators are built and tested is described on the Methodology page. If a figure looks wrong, please report it.
Frequently Asked Questions
How is Cache Hit Rate calculated?
Cache Hit Rate = Cache hits ÷ Total lookups × 100 The cache hit rate is the share of total lookups that cache hits represents, expressed as a percentage. The same figure is also shown per 1,000 and as a "one in every N" odds statement, which is easier to reason about when the rate is very small.
Why does Cache Hit Rate matter?
Absolute counts hide scale — a rate normalises the number so you can compare periods, channels or cohorts of different sizes, where higher is better.
What values do I need to enter?
This calculator takes 2 inputs: Cache hits, Total lookups. The pre-filled defaults are a realistic starting point — replace them with figures from your own environment for a result you can act on.