Hardware buying calculator for local LLM speed

What to build

A free calculator-style web tool (like Llmspeed) that lets a hobbyist pick a GPU/CPU + model + quantization and see estimated tokens-per-second before buying hardware, monetized via affiliate GPU/RAM links and a 'pro' tier with saved builds, multi-backend comparisons (llama.cpp, Ollama, vLLM), and deeper model coverage.

Llmspeed's 257-point, 77-comment HN launch shows real appetite for a pre-purchase local-LLM speed estimator; the opportunity is to extend that into a monetizable benchmark database rather than a one-off demo.

Demand

Hobbyists and devs assembling PCs specifically to run Llama/Mistral locally want to avoid buying the wrong GPU, and they're vocal about it on HN and r/LocalLLaMA where tokens-per-second threads are a recurring topic.

• Hacker News (Show HN)Engagement

  Show HN: Llmspeed - feel how fast a local LLM runs before you buy the hardware - 257 points, 77 comments on HN; high engagement at the source.

• Hacker News (Show HN)News

  Show HN post indicates a tool exists to preview local LLM inference performance prior to hardware purchase, validating the underlying need.

Stack

• Next.js
• Benchmark dataset (llama.cpp/Ollama community results)
• PostgreSQL or Supabase
• Stripe for pro tier
• Amazon/Newegg affiliate API
• Discord Bot API for community bot

Solo + AI difficulty

The hard part is sourcing and maintaining an accurate, backend- and quantization-aware benchmark dataset that doesn't go stale as new models and runtimes ship; the UI, affiliate links, and Stripe paywall are straightforward for a solo builder with AI help. Rough MVP: 1-2 weeks for a basic estimator using scraped/crowdsourced numbers, longer if you want it to stay credible over time.

Entry threshold

Low barrier: a solo developer can scrape or crowdsource benchmark data and build a simple calculator or web tool in days, though building real credibility requires accumulating enough real-world benchmark data points.

Window

6-12 months

Where to find first users

• r/LocalLLaMA
• Hacker News (Show HN follow-up or relevant threads)
• Reddit r/MachineLearning and r/buildapc (LLM rig threads)
• Discord servers for Ollama/LM Studio/llama.cpp

Counter-signals & risks

• Hardware vendors and community wikis (e.g. r/LocalLLaMA benchmark threads, llama.cpp discussions) already provide free crowd-sourced tokens-per-second benchmarks, reducing willingness to pay for a dedicated service.

• Inference speed varies significantly by quantization, context length, backend (llama.cpp, vLLM, Ollama), and model version, making a simple hardware-to-speed estimator potentially inaccurate or quickly outdated.

• The target market of hobbyists building local LLM rigs may be too small and price-sensitive to sustain a paid tier or generate meaningful affiliate revenue.