BotBrowser Performance Benchmark

Performance data comparing BotBrowser fingerprint protection overhead against stock Chromium, and evaluating Per-Context Fingerprint scalability.

Key Findings

Question	Answer
How much overhead does BotBrowser add?	Near-zero. Speedometer 3.0 shows <1% difference in both headed and headless modes, within run-to-run variance.
Are fingerprint APIs slower?	No. Canvas, WebGL, Navigator, Screen, and Font APIs show identical latency with or without fingerprint profiles on macOS, Linux, and Windows.
How does Per-Context Fingerprint scale?	At 50 concurrent profiles: 29% less memory, 57% fewer processes, 2x faster creation vs launching 50 separate browser instances. Full fingerprint isolation verified.

Single Instance Performance

Standard Benchmark Suites

All benchmarks run locally (no network dependency). Each test runs 3 times; median reported.

Test Environment: macOS (Apple M4 Max, 16 cores, 64GB RAM)

Mode	Benchmark	Stock Chrome	BotBrowser + Android	Difference
Headless	Speedometer 3.0	42.8 (±0.31)	42.7 (±0.25)	-0.2%
Headed	Speedometer 3.0	41.8 (±0.21)	42.1 (±0.17)	+0.7%

Methodology: Warm-up run (discarded) + 3 measurement runs with interleaved test order (Stock → BB → Stock → BB → Stock → BB) to eliminate thermal/cache bias. Scores shown as median ± stddev.

Result: BotBrowser's fingerprint protection adds no measurable overhead to JavaScript and DOM performance. Differences of 0.1-0.3 points are well within run-to-run variance. Consistent across both headed and headless modes.

Fingerprint API Overhead

Individual API latency measured over 1,000 iterations each, median reported (milliseconds).

API	Stock Chrome	BB + Android	BB + Windows	BB + macOS
Canvas2D `toDataURL()`	0.5	0.5	0.5	0.5
Canvas2D `getImageData()`	0.0	0.0	0.0	0.0
WebGL `getParameter(RENDERER)`	0.0	0.0	0.0	0.0
WebGL `getSupportedExtensions()`	0.0	0.0	0.0	0.0
WebGL `getShaderPrecisionFormat()`	0.0	0.0	0.0	0.0
WebGL `readPixels()`	0.2	0.2	0.2	0.2
AudioContext Offline Render + Hash	3.9	2.9	3.2	3.7
Navigator `userAgent`	0.0	0.0	0.0	0.0
Navigator `platform`	0.0	0.0	0.0	0.0
Screen `width` + `height`	0.0	0.0	0.0	0.0
`performance.now()`	0.0	0.0	0.0	0.0
Font `measureText()` (50 fonts)	0.0	0.0	0.0	0.0
Intl `DateTimeFormat.resolvedOptions`	0.0	0.0	0.0	0.0

Result: Fingerprint protection adds zero overhead on all tested APIs. Canvas, WebGL, Navigator, Screen, and Font APIs show identical latency with or without a fingerprint profile. AudioContext variance (2.9-3.9ms) is within normal fluctuation.

Page Load Time

Median load time for a locally-intercepted page (milliseconds).

Configuration	Load Time	vs Stock
Stock Chrome (no profile)	29.7ms	-
BotBrowser + Android	101.6ms	+72ms
BotBrowser + Windows	102.9ms	+73ms
BotBrowser + macOS	105.9ms	+76ms

Note: The additional ~72-76ms comes from one-time profile initialization (reading and applying fingerprint configuration on first page load). All three profile types show similar overhead, indicating no significant difference between cross-platform profiles.

Scale Performance: Per-Context vs Multi-Instance

The core value proposition for enterprise users: running N different fingerprint profiles simultaneously.

Architecture Comparison

Architecture	How It Works
Multi-Instance	Launch N separate browser processes, each with a different `--bot-profile`
Per-Context (ENT Tier 3)	Launch 1 browser, create N BrowserContexts, each assigned a different profile via CDP `BotBrowser.setBrowserContextFlags`

Resource Usage at Scale

Test Environment: macOS (Apple M4 Max, 16 cores, 64GB RAM), Headless mode

Scale	MI Memory	PC Memory	Savings	MI Processes	PC Processes	MI Create Time	PC Create Time	Speedup
1	16,055 MB	14,022 MB	13%	140	136	1,667ms	627ms	2.7x
10	23,345 MB	19,586 MB	16%	212	150	11,434ms	4,854ms	2.4x
25	30,133 MB	23,781 MB	21%	320	174	28,205ms	14,415ms	2.0x
50	40,218 MB	28,553 MB	29%	492	210	57,891ms	28,946ms	2.0x

Per-Context memory savings increase with scale as the shared browser/GPU/network processes are amortized across more contexts.

Canvas Fingerprint Isolation

Each context/instance receives a unique noise seed, producing distinct canvas fingerprints. Verified across all scale levels:

Architecture	Scale	Unique Hashes	Status
Multi-Instance	10	10/10	PASS
Multi-Instance	25	10/10	PASS
Multi-Instance	50	10/10	PASS
Per-Context	10	10/10	PASS
Per-Context	25	10/10	PASS
Per-Context	50	10/10	PASS

Per-Context Fingerprint provides the same fingerprint isolation as running separate browser instances, while sharing infrastructure resources.

Scaling Characteristics

Multi-Instance (N browsers):

Memory grows linearly: each browser adds ~400-800MB
Process count grows linearly: ~7-10 processes per browser
Creation time grows linearly: ~1s per browser

Per-Context (1 browser, N contexts):

Memory grows sub-linearly: contexts share browser/GPU/network processes
Process count grows more slowly: shared processes are reused
Creation time grows sub-linearly: no browser startup overhead per context

At 50 Concurrent Profiles

Multi-Instance:  40,218 MB memory | 492 processes | 57.9s to create
Per-Context:     28,553 MB memory | 210 processes | 28.9s to create
                 ──────────────────────────────────────────────────
Savings:           29% memory     | 57% processes  |  2.0x faster

Context Lifecycle Performance

Continuous create/destroy cycle test (200 iterations):

Metric	Value
Context creation (median)	278ms
Context creation (p95)	369ms
Context destruction (median)	7.9ms
Context destruction (p95)	16ms
Memory trend (200 cycles)	Stable (no persistent growth)

Context creation is lightweight (~280ms) and destruction is near-instant (~8ms). Memory remains stable over 200 create/destroy cycles with no persistent memory leaks observed.

Cross-Platform Verification

BotBrowser supports applying any platform's fingerprint on any host OS. Tested on macOS, Linux, and Windows.

Fingerprint API Latency: macOS Host

All values in milliseconds (median of 1,000 iterations). Headless mode.

API	Stock Chrome	BB + Android	BB + Windows	BB + macOS
Canvas2D `toDataURL()`	0.5	0.5	0.5	0.5
WebGL `readPixels()`	0.2	0.2	0.2	0.2
AudioContext Render	3.9	2.9	3.2	3.7
All other APIs	0.0	0.0	0.0	0.0

Fingerprint API Latency: Linux Host

Tested in both headless and headed modes.

API	Headless Stock	Headless BB	Headed Stock	Headed BB
Canvas2D `toDataURL()`	0.3	0.3	0.3	0.3
WebGL `readPixels()`	0.1	0.1	0.1	0.1
AudioContext Render	8.5	7.1	9.0	7.7
Font `measureText()`	0.1	0.1	0.1	0.1
All other APIs	0.0	0.0	0.0	0.0

Fingerprint API Latency: Windows Host

Tested in both headless and headed modes.

API	Headless Stock	Headless BB	Headed Stock	Headed BB
Canvas2D `toDataURL()`	1.8	1.8	1.6	1.5
Canvas2D `getImageData()`	0.7	0.6	0.6	0.6
WebGL `readPixels()`	0.5	0.7	0.6	0.6
AudioContext Render	10.5	9.1	8.9	10.8
Font `measureText()`	0.3	0.3	0.3	0.3
All other APIs	0.0	0.0	0.0	0.0

Note: The Windows test environment uses software rendering (no discrete GPU), resulting in higher Canvas/WebGL baseline latency compared to macOS. The relative overhead between Stock and BotBrowser remains zero.

Page Load: Windows Host

Mode	Stock Chrome	BotBrowser + Android
Headless	28.7ms	27.9ms (-0.8ms)
Headed	27.9ms	27.1ms (-0.8ms)

Page Load: Linux Host

Mode	Stock Chrome	BotBrowser + Android
Headless	7.4ms	8.4ms (+1.0ms)
Headed	8.6ms	6.9ms (-1.7ms)

Result: Fingerprint protection overhead is zero for all core APIs across all three platforms and both rendering modes.

Methodology

Test Configuration

Setting	Value
Chrome version	145
Automation	Playwright (playwright-core)
Benchmark deployment	Local HTTP server (no network dependency)
Test categories	Speedometer 3.0, Fingerprint API micro-benchmarks (13 APIs), Page load timing, Per-Context vs Multi-Instance scale

How to Reproduce

All benchmark scripts are available in docs/benchmarks/:

Script	Purpose
`bench-baseline.js`	Single-instance benchmark (Speedometer + Fingerprint API + Page load)
`bench-scale.js`	Per-Context vs Multi-Instance scale test
`run-all.js`	Full automated orchestration
`fingerprint-bench.html`	Fingerprint API overhead test page
`config.js`	Platform detection and path configuration
`utils.js`	Shared utilities (stats, memory sampling)

To run them:

# 1. Clone benchmark suites locally
cd docs/benchmarks
./setup-benchmarks.sh

# 2. Install dependencies
npm install

# 3. Set environment variables
export BROWSER_PATH=/path/to/botbrowser/chrome
export PROFILES_BASE=/path/to/your/profiles

# 4. Run baseline benchmark (single instance)
node scripts/bench-baseline.js --mode headless

# 5. Run scale benchmark (per-context vs multi-instance)
node scripts/bench-scale.js --mode headless --max-scale 50

Statistical Method

Benchmark suites: Warm-up run (discarded) + 3 interleaved measurement runs per configuration, median ± stddev reported
Fingerprint APIs: 1,000 iterations per API, median reported
Page loads: 10 measurements per configuration, median reported
Scale tests: Single run per scale level (deterministic setup)

Environment Details

macOS (primary test platform):

Apple M4 Max (16 cores), 64GB RAM
macOS 15.3, arm64

Linux (cross-platform verification):

Ubuntu 22.04, x64

Windows (cross-platform verification):

Intel Xeon (20 cores / 40 threads), 64GB RAM
Windows 11, x64

Summary

BotBrowser's fingerprint protection engine is designed for production workloads:

Zero measurable overhead on Speedometer 3.0: headless 42.7 vs 42.8 (-0.2%), headed 42.1 vs 41.8 (+0.7%)
Zero fingerprint API overhead. Canvas, WebGL, Navigator, Screen, Font APIs show identical latency on macOS, Linux, and Windows, in both headed and headless modes
Per-Context Fingerprint provides resource savings at scale with full fingerprint isolation:
- 29% less memory at 50 concurrent profiles
- 2x faster profile creation
- 57% fewer OS processes
- 100% canvas fingerprint isolation verified (each context produces a unique hash)
Consistent across platforms, tested on macOS arm64, Linux x64, and Windows x64 with identical results

For enterprise users running concurrent fingerprint profiles, Per-Context Fingerprint (ENT Tier 3) delivers the same privacy protection with lower infrastructure cost and verified fingerprint isolation between contexts.

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BotBrowser Performance Benchmark

Key Findings

Single Instance Performance

Standard Benchmark Suites

Fingerprint API Overhead

Page Load Time

Scale Performance: Per-Context vs Multi-Instance

Architecture Comparison

Resource Usage at Scale

Canvas Fingerprint Isolation

Scaling Characteristics

At 50 Concurrent Profiles

Context Lifecycle Performance

Cross-Platform Verification

Fingerprint API Latency: macOS Host

Fingerprint API Latency: Linux Host

Fingerprint API Latency: Windows Host

Page Load: Windows Host

Page Load: Linux Host

Methodology

Test Configuration

How to Reproduce

Statistical Method

Environment Details

Summary

Related Documentation

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BotBrowser Performance Benchmark

Key Findings

Single Instance Performance

Standard Benchmark Suites

Fingerprint API Overhead

Page Load Time

Scale Performance: Per-Context vs Multi-Instance

Architecture Comparison

Resource Usage at Scale

Canvas Fingerprint Isolation

Scaling Characteristics

At 50 Concurrent Profiles

Context Lifecycle Performance

Cross-Platform Verification

Fingerprint API Latency: macOS Host

Fingerprint API Latency: Linux Host

Fingerprint API Latency: Windows Host

Page Load: Windows Host

Page Load: Linux Host

Methodology

Test Configuration

How to Reproduce

Statistical Method

Environment Details

Summary

Related Documentation