AI tool comparison
Genspark for Excel 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
Genspark for Excel
Write Excel formulas, build charts, analyze data — in plain English
75%
Panel ship
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Community
Free
Entry
Genspark for Excel is an AI assistant embedded directly inside Microsoft Excel that lets users complete spreadsheet tasks through natural language commands. It writes formulas including advanced array functions and XLOOKUP, builds charts, generates pivot tables, analyzes datasets, and even pulls live web research — all without leaving the spreadsheet. The tool is designed for analysts, operations teams, and business users who live in spreadsheets but don't want to become Excel formula experts. Instead of googling syntax or copying StackOverflow answers, users describe what they need in plain English and the AI translates it into working Excel operations in place. Genspark has been building AI-native productivity tools since 2024. The Excel add-in is their most focused product yet — going deep on a single high-value workflow rather than building a general assistant. With a free tier available, the barrier to trying it is low for any Excel power user.
AI Productivity
Sup AI
Runs 339 LLMs in parallel and downweights the hallucinating ones.
50%
Panel ship
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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
“I've watched non-technical teammates struggle with XLOOKUP syntax for years. An AI that lives inside the spreadsheet and writes the formula for you in context is genuinely useful — especially since it can see the actual data structure to avoid type mismatches.”
“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.”
“Excel AI add-ins are a crowded category — Copilot in Microsoft 365 does most of this, and it's bundled for enterprise users. Unless the web research pull is meaningfully better than Copilot's, this faces a brutal incumbent.”
“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.”
“The most profound AI applications are the ones that meet users in their existing tools rather than forcing workflow changes. Embedding AI inside Excel — where billions of hours of knowledge work happen — has compounding impact that standalone AI apps can't match.”
“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.”
“For content creators managing editorial calendars, audience data, and campaign analytics in spreadsheets, this is a practical daily-driver upgrade. Web research pulls inside Excel changes how you build data-backed content briefs.”
“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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