PHBench
Predict the next Series A from a ProductHunt launch
PHBench launched on May 15, 2026 with 398 votes, #39 of 20,538 launches that month and more than 99% of that year's launches.
In plain words
PHBench is a predictive tool that forecasts Series A funding likelihood based on Product Hunt launch performance. It analyzes data from over 67,000 featured launches linked to 528 verified Series A rounds to identify funding signals. The benchmark identifies team size and community engagement as the strongest predictors, with B2B companies in APIs, payments, and fintech showing three times higher conversion rates. Users can submit their launches on phbench.com and receive weekly predictions of high-probability Series A candidates. The dataset, code, and baseline models are publicly available.
written from the facts on this page · September 2026
From the sources
PHBench: the first public benchmark predicting Series A funding from Product Hunt launch signals. We analyzed 67,292 featured launches over 7 years, linked to 528 verified Series A rounds via Crunchbase. Champion model: 4.7x lift over random. Team size × community engagement is the strongest signal; B2B (API, Payments, Fintech) converts at 3x baseline; Rank #1 raises at 2.2x unranked. Dataset, code, and baselines open. Submit at phbench.com and subscribe for weekly high-probability launches.
An open benchmark for predicting Series A funding from Product Hunt launch signals. 67,292 launches, 528 verified Series A events. Weekly predictions and launch simulator.
Does a similar job
all alternatives →



Product Hunt Success Playbook2023 · mailmodo.com · ▲277Proven tactics & tools to boost your PH launch

More ai this month
the category →



Paintings by AI models: programs run through a simulation of oil paint.
AI · 20d ago · stillwet.art

PixVerse R2▲381A real-time world model you can explore and change
AI · 28d ago · world.pixverse.video
Source: Product Hunt launch ↗
Launched alongside, May 2026
the whole month →

Parallel agents, diff reviewer, and multi-model comparisons
Dev tools · May 2026 · kilo.ai



Hey HN, Henry here from Cactus. We open-sourced Needle, a 26M parameter function-calling (tool use) model. It runs at 6000 tok/s prefill and 1200 tok/s decode on consumer devices. We were always frustrated by the little effort made towards building agentic models that run on budget phones, so we conducted investigations that led to an observation: agentic experiences are built upon tool calling, and massive models are overkill for it. Tool calling is fundamentally retrieval-and-assembly (match query to tool name, extract argument values, emit JSON), not reasoning. Cross-attention…
Life & fun · May 2026 · github.com

🌱 Private, quiet space for thinking. Simple app for .md files. - zakirullin/files.md
Dev tools · May 2026 · github.com