AI tool comparison
MiniAi vs Sup AI
Which one should you ship with? Here is the side-by-side panel verdict, pricing read, reviewer split, and community vote comparison.
Productivity
MiniAi
Select any text on Mac, press ⌥Space, get AI in a floating panel
75%
Panel ship
—
Community
Free
Entry
MiniAi is a macOS menu bar app with exactly one job: explain selected text without breaking your focus. Highlight any text on your Mac — in a PDF, email, code file, web page, or document — press Option+Space, and a floating AI explanation panel appears. No app switching, no copy-paste, no context loss. Built by a medical student who needed to stay in reading flow while looking up terms in research papers, MiniAi uses Claude Haiku under the hood for fast, accurate explanations. The floating panel dismisses with Escape and leaves no trace in your task switcher. The scope is deliberately minimal: one gesture, one action, instant result. No chat history, no threads, no settings overwhelm. Free to use with your own Anthropic API key. Launched today on Product Hunt where it resonated strongly with students, researchers, and professionals who live in document-heavy workflows.
AI Productivity
Sup AI
Runs 339 LLMs in parallel and downweights the hallucinating ones.
50%
Panel ship
—
Community
Free
Entry
Sup AI is an ensemble AI assistant that runs your query through 339 language models simultaneously, measures per-segment confidence across all responses, and synthesizes a final answer that amplifies agreement and suppresses likely hallucinations. The team claims a 52.15% score on Humanity's Last Exam (HLE) — 7.41 percentage points above the single best model — which, if verified, would make it the highest-scoring system on the benchmark to date. The underlying mechanism works like an LLM panel: each model votes on sub-claims within the response, confidence is estimated by agreement density, and the final output surfaces high-confidence segments while flagging uncertain ones. It's designed to reduce hallucination rate on factual tasks, not improve reasoning per se — the models in the ensemble aren't doing collaborative chain-of-thought, they're voting on outputs. Sup AI was built by Ken Mueller (Stanford, CEO) and Scott Mueller (AI Research Scientist) and launched on Product Hunt today. Pricing starts with $10 in free credits, no auto-charge, with a credit card required to start. The HLE benchmark claim is the headline and will face scrutiny — if verified, this is a meaningful research result. If it's cherry-picked, it's still a usable product with a differentiated architecture.
Reviewer scorecard
“The Option+Space shortcut is muscle memory within 10 minutes. BYOK with Haiku means it's essentially free at typical usage — Haiku is fast and accurate enough for term lookups and quick explanations. The zero-UI-overhead philosophy is exactly right for a tool you invoke 20 times a day.”
“The HLE claim needs independent verification, but the underlying ensemble approach is architecturally sound for factual Q&A tasks. Running 339 models is expensive — pricing will be the gating factor for production use. The $10 free credit is a fair trial.”
“Apple's own Writing Tools in macOS 15 already has a 'Summarize' action in the right-click menu, and it's free with no API key. PopClip has been doing triggered text actions for a decade with a rich ecosystem of extensions. MiniAi needs a clearer differentiator beyond the keyboard shortcut.”
“Extraordinary claims require extraordinary evidence. A 7.41 point jump on HLE via ensembling — without publishing methodology — smells like benchmark gaming. The latency of running 339 models in parallel is also a real concern for anything other than async research tasks.”
“Tools like MiniAi are training users to expect ambient AI assistance — intelligence available at any moment without mode-switching. This behavioral shift is significant: once people get used to instant contextual explanation, the bar for every reading and research tool permanently rises.”
“Model ensembling is an underexplored direction in the race to reduce hallucination. If Sup AI's approach scales, it could be more durable than fine-tuning individual models — you get the wisdom of the crowd across model families, training data, and architectures simultaneously.”
“The story behind MiniAi — built by a med student to stay in flow during paper reading — is authentic and the design reflects genuine user empathy. For writers, researchers, and anyone working with dense material, this is the kind of tool you install and forget you installed because it just works.”
“For creative work, ensemble outputs tend to regress toward the mean — you get the most-agreed-upon version of something, which is usually the least interesting version. This is a tool for factual accuracy, not creativity. I'd stick with a single strong model for writing.”
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