Cache Hit Latency
Calculator
Results
- Effective latency (ms)
- 19.7
- Latency saved (ms)
- 100.3
- Speed-up factor
- 6.09137
- Cache miss ratio (%)
- 15
Computing results
| Effective latency (ms) | 19.7 |
| Latency saved (ms) | 100.3 |
| Speed-up factor | 6.09137 |
| Cache miss ratio (%) | 15 |
formula-map diagram
- Effective latency (ms)
- 19.7
- Latency saved (ms)
- 100.3
- Speed-up factor
- 6.09137
- Cache miss ratio (%)
- 15
Computing relationship
Formula
L = h × L_hit + (1 − h) × L_miss= 19.7
Note
This is a simplified model: it applies the standard computing formula to the numbers you entered and ignores protocol overhead, compression variability, retries, contention and other real-world effects. Size your systems with measured data.
More in Technology and computing
See all →Frequently asked questions
What does this calculator compute?+
It computes the effective average latency of a system that uses caching, by combining the (fast) latency of cache hits and the (slower) latency of cache misses, weighted by the cache hit rate — the percentage of requests successfully served from cache.
Why does a small change in hit rate make such a big difference?+
Because miss latency is typically many times larger than hit latency, even a modest drop in hit rate shifts a disproportionate share of requests onto the slow path. Going from a 95% to a 90% hit rate can noticeably increase average latency, especially when the miss penalty is large.
What's a good cache hit rate to aim for?+
It depends heavily on the workload and the type of cache, but many production systems target 80-95% or higher for effective caching layers. What matters most is whether the achieved hit rate meaningfully reduces the effective latency compared to having no cache at all.
Why would effective latency still be high even with a high hit rate?+
If the miss penalty is extremely large — for example, a database query or a cross-region network call — even a small percentage of misses can dominate the average. In such cases, further reducing miss latency (not just increasing hit rate) may be the more effective optimization.
Does this calculator account for cache warm-up or cold-start effects?+
No, it assumes a steady-state hit rate that stays constant. In practice, a newly started or recently cleared cache will have a much lower hit rate until it 'warms up' with frequently accessed data, so effective latency will be temporarily worse than this steady-state estimate.