Proof // Free to read 🔬
Guava Research
How I judge AI before I recommend it.
Two benchmarks that score models on the money they protect for a business, the AI
setup I run Guava on, and my own AI usage, live.
At a glance // From the leaderboards 📊
| Models tested | 15 so far, across two private benchmarks of 100 hidden problems each |
|---|---|
| Main Street Bench | Claude Opus 5.5, GPT-6 Astra and GPT-6.1 Sol are tied at the top, protecting $85,989 to $87,578 of $100,000 on average across their runs, with overlapping run ranges |
| MSP Bench | Claude Opus 5.5 protects the most: $883,722 of $1,000,000 on average across its runs |
| Open source | guava-stack, free under the MIT license |
| Live | My Codex, Claude Code and OpenRouter usage, refreshed every minute |
| Updated |
The work
Open any of them to see how it works.
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01 Benchmark // Small business
Main Street Bench
Which AI protects a small business’s money best? Each model is handed everything for a messy neighborhood bakery, with 100 hidden problems and $100,000 at risk. Its score joins four public benchmarks in the Main Street Index, ranked against cost.
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02 Benchmark // Managed IT
MSP Bench
The same test for a managed IT provider: its tickets, billing, backups, client accounts, scripts and contracts, with 100 hidden problems that put $1,000,000 at risk.
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03 Open source // MIT license
guava-stack
The AI setup I run Guava on. One hub in your own Notion holds your context, rules, skills and memories, and every assistant you connect reads it. It’s a small add-on to Notion’s setup guide, with 16 working rules, a free workflow review, and a model router for Claude Code and Codex. Nothing is sent to Guava.
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Live
04 Live // From Elastic
Live AI Dashboard
My own Codex, Claude Code and OpenRouter usage as it happens: model requests, tokens by model and response times. It’s the observability I set up for clients, pointed at myself. Prompts and responses are never captured.
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