# KitBench

> Simple &amp; Transparent CPU and RAM Benchmark — all on-device, offline.

Canonical page: [https://chrome-stats.com/d/com.vitkit.kitbench](https://chrome-stats.com/d/com.vitkit.kitbench)

## Overview

- **ID:** `com.vitkit.kitbench`
- **Platform:** Android
- **Type:** Android app
- **Status:** Available
- **Publisher:** VitKit
- **Category:** TOOLS
- **Downloads:** 85
- **Version:** 1.1.54
- **Last updated:** 2026-09-07
- **First published:** 2025-08-16
- **Publisher country:** UA
- **Size:** 4.24 MB
- **Data as of:** 2026-09-14
- **Store listing:** [Google Play Store](https://play.google.com/store/apps/details?id=com.vitkit.kitbench)
- **Website:** [https://vitkit.com.ua](https://vitkit.com.ua/)
- **Privacy policy:** [https://docs.google.com/document/d/14ukQUh3bBdvgE8IXgSK5dHoPJejbokITluOS9uUafzY/view?usp=sharing](https://docs.google.com/document/d/14ukQUh3bBdvgE8IXgSK5dHoPJejbokITluOS9uUafzY/view?usp=sharing)

## Description

KitBench is a straightforward Android benchmark that measures real CPU and memory performance — no synthetic tricks or hidden formulas.<br><br>KEY FEATURES<br>• Open methodology. The app shows the exact algorithms and pseudocode used in each test.<br>• CPU, FPU, NEON &amp; native ALU. Separate tests for integer (JVM/ART), floating-point (JVM), native ALU and SIMD/NEON — each in single-thread and multi-thread modes.<br>• RAM bandwidth. Measures large-buffer copy throughput with cache-aware safeguards.<br>• Memory latency (LAT). Pointer-chasing over a ring of 64-B nodes; L1 and DRAM presets; results in ns per dependent load.<br>• Thermals &amp; throttling. Temperature readouts and a “Throttling (~NN%)” badge; in Run all the app cools down to &lt; 65 °C before each test.<br>• Repeatable results. Fixed durations, consistent buffer sizes and clear units (ops/s, GB/s).<br>• Private by design. No accounts, no ads, no analytics — everything runs locally.<br>• Fast &amp; lightweight. Minimal UI, instant start, no unnecessary permissions.<br>• Modern device support. Works on ARM devices; uses NEON/ASM where available.<br><br>HOW IT WORKS<br>KitBench runs standardized loops directly on your device:<br>• CPU tests: integer &amp; floating-point math, logic and array access, with separate single-core and multi-core runs.<br>• RAM test: large-buffer copy to measure effective bandwidth while reducing unrealistic cache effects.<br><br>SCORING METHODOLOGY<br>• Domains: ST (single-thread), MT (multi-thread), BW (RAM bandwidth), LAT (memory latency). Each domain is a geometric mean of normalized sub-tests.<br>• Normalization: value/ref for higher-is-better (CPU/FPU/ASM/NEON, BW) and ref/value for lower-is-better (LAT).<br>• Reference anchors (ST): CPU = 0.65e9, FPU = 0.24e9, ASM = 8.0e9, NEON = 6.0e9 ops/s; RAM-copy ST = 27 GB/s.<br>• MT scaling addendum: MT sub-tests are normalized against an expected scaling model ref_MT(T) = base_per_thread × T^α. Exponents: α_CPU = 0.85, α_VEC (ASM/NEON) = 0.90. ≈1.0× means “as expected”; &gt;1.0× means “better-than-expected scaling”.<br>• Latency refs: L1 = 1.2 ns, DRAM = 100 ns.<br>• Aggregate: weighted geometric mean with wST = 0.35, wMT = 0.30, wBW = 0.20, wLAT = 0.15; final score = round(1000 × Aggregate).<br><br>TIPS FOR CONSISTENT RESULTS<br>• Let the device cool and avoid charging during a run.<br>• Close heavy background apps.<br>• Watch the badge: “Throttling (~NN%)” usually implies performance loss.<br><br>PRIVACY &amp; PERMISSIONS<br>• Data collection: none.<br>• Network: not required.<br>• Permissions: none beyond basics needed for operation.<br><br>WHY KITBENCH?<br>• Objective, repeatable numbers — not “gamified” scores.<br>• Clear methodology you can verify.<br>• Useful for enthusiasts, developers and anyone curious about real-world device performance.<br><br>FAQ<br>Q: Why isn’t MT = ST × cores?<br>A: Real systems scale sub-linearly (memory/cache limits, scheduler overhead, big.LITTLE, thermal throttling, sync).<br><br>Q: What is threads^α and why α = 0.85 / 0.90?<br>A: It’s expected scaling: CPU/FPU α=0.85, ASM/NEON α=0.90. ≈1.0× means “as expected”; &gt;1.0× means “better-than-expected scaling”.<br><br>Q: Why reference anchors at all?<br>A: Sub-tests have different units (ops/s, GB/s, ns). Anchors map them to dimensionless multipliers so domains can be aggregated fairly.<br><br>Q: Do anchors favor a particular chipset?<br>A: No. They set the scale. Devices exceeding expectations get &gt;1.0× and score higher.<br><br>Q: Why geometric means and domain weights?<br>A: To reflect multiplicative effects and avoid domination by one outlier; weights (ST 0.35, MT 0.30, BW 0.20, LAT 0.15) define balance.<br><br>Q: Why keep a Java test if ASM/NEON exist?<br>A: To reflect real JVM/ART behavior (bounds checks, JIT/GC, branches, interpreter↔JIT).<br><br>Q: Why do results vary between runs?<br>A: Background activity, DVFS, temperature, affinity, OS power policies. Keep conditions consistent.<br><br>COMPATIBILITY<br>Android 8.0+ (API 26+); ASM runs in the bitness of the current ABI (armeabi-v7a = 32-bit, arm64-v8a = 64-bit); NEON required on ARMv7-A (present by default on ARM64).

## Rankings

- #2,043,583 — Overall

## Permissions and access

### Permissions

- `com.android.vending.CHECK_LICENSE`
- `com.vitkit.kitbench.DYNAMIC_RECEIVER_NOT_EXPORTED_PERMISSION`

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Source: [Chrome-Stats](https://chrome-stats.com/d/com.vitkit.kitbench)
