About ClankerBuilder

What We Do

ClankerBuilder helps you design AI/LLM workstation builds from real PC parts with live compatibility checks, tok/s performance ratings, and price comparisons. We solve the unique challenges of local LLM inference: VRAM requirements, multi-GPU configurations, and performance-per-dollar optimization.

Our compatibility engine performs real-time validation across VRAM capacity, PCIe lane allocation, power supply headroom, and NVLink constraints — catching configuration issues before you purchase.

Methodology & Data Sources

Performance ratings aggregate community benchmarks from LocalLLaMA, llama.cpp issue threads, and controlled lab measurements. We never publish our own benchmark numbers — only validated third-party data with clear provenance.

Compatibility rules are derived from hardware specifications, manufacturer documentation, and real-world testing feedback from the community. Rules are versioned and frozen with each build snapshot for reproducibility.

Pricing data comes from retailer feeds via affiliate networks, marked with freshness indicators. Stale prices older than 24 hours are clearly labeled until the next update cycle.

Editorial Independence

ClankerBuilder participates in affiliate programs but editorial recommendations are driven by compatibility data, performance benchmarks, and price — not commission rates. We disclose all affiliate relationships and mark sponsored links appropriately.

Our goal is neutral, data-driven guidance for local LLM hardware decisions. When multiple configurations achieve similar performance, we present the tradeoffs rather than picking winners.

Open Development

ClankerBuilder is developed transparently with community input. Build guides are tested by real users, compatibility rules evolve based on field reports, and feature requests drive our roadmap.

The project maintains detailed methodology documentation, version-controlled compatibility rules, and public issue tracking for bugs and enhancement requests.

Data Quality Standards

• Benchmark validation: Performance data requires multiple independent sources or detailed methodology disclosure
• Price accuracy: Retailer feeds are refreshed multiple times daily with staleness indicators
• Compatibility testing: Rules are validated against real hardware configurations and user feedback
• Version control: All data sources, rules, and methodologies are versioned for reproducible build snapshots

Contact & Feedback

For methodology questions, data corrections, or partnership inquiries, reach out via:

• X/Twitter @clankerbuilder
• Affiliate disclosure and policies
• Detailed tok/s methodology