This product was not featured by Product Hunt yet. It will not be visible on their landing page and won't be ranked (cannot win product of the day regardless of upvotes).
I built MOLOCH.SH because I kept losing track of which AI models had really shipped and which were only announced, and of how open weights models compare with closed ones on capability and price.
The site has five views. Today shows up to three changes from the latest data collection, picked by a fixed rule that the page publishes, or says nothing significant changed. Models is a sortable table where you can compare up to three models and see the open and closed frontier over time. Releases treats announcement, restricted access, public API and downloadable weights as separate events. The Race looks at the gaps between the US and China, open and closed, and the top two labs. AI 2027 tracks 19 milestones from that scenario, keeping the original prediction intact next to dated author revisions and my own assessment on a fixed scale.
No number is written by hand in the code. A collector script pulls from OpenRouter, Hugging Face, Epoch AI and METR, and each figure stores its value, source, link, data date and retrieval date. Anything that is interpretation is labeled as such. It is plain HTML, CSS and JavaScript with no build step, in Spanish and English, free and with no signup. The code is public on GitHub.
The ideas are mine; AI helped me build it.
I would really value feedback on two things: whether the charts are easy to read, and any number you think is wrong or missing.
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About MOLOCH.SH on Product Hunt
“Observatorio de la carrera por la IA”
MOLOCH.SH was submitted on Product Hunt and earned 3 upvotes and 1 comments, placing #70 on the daily leaderboard. Qué ha salido, qué mejora, cuánto cuesta y dónde comprobarlo: modelos abiertos y cerrados con fuente y fecha en cada cifra.
MOLOCH.SH was featured in Open Source (69k followers), Artificial Intelligence (483.2k followers) and GitHub (41.5k followers) on Product Hunt. Together, these topics include over 188.5k products, making this a competitive space to launch in.
Who hunted MOLOCH.SH?
MOLOCH.SH was hunted by Rolando Fernández. A “hunter” on Product Hunt is the community member who submits a product to the platform — uploading the images, the link, and tagging the makers behind it. Hunters typically write the first comment explaining why a product is worth attention, and their followers are notified the moment they post. Around 79% of featured launches on Product Hunt are self-hunted by their makers, but a well-known hunter still acts as a signal of quality to the rest of the community. See the full all-time top hunters leaderboard to discover who is shaping the Product Hunt ecosystem.
Want to see how MOLOCH.SH stacked up against nearby launches in real time? Check out the live launch dashboard for upvote speed charts, proximity comparisons, and more analytics.
Hi everyone, I'm Rolando.
I built MOLOCH.SH because I kept losing track of which AI models had really shipped and which were only announced, and of how open weights models compare with closed ones on capability and price.
The site has five views. Today shows up to three changes from the latest data collection, picked by a fixed rule that the page publishes, or says nothing significant changed. Models is a sortable table where you can compare up to three models and see the open and closed frontier over time. Releases treats announcement, restricted access, public API and downloadable weights as separate events. The Race looks at the gaps between the US and China, open and closed, and the top two labs. AI 2027 tracks 19 milestones from that scenario, keeping the original prediction intact next to dated author revisions and my own assessment on a fixed scale.
No number is written by hand in the code. A collector script pulls from OpenRouter, Hugging Face, Epoch AI and METR, and each figure stores its value, source, link, data date and retrieval date. Anything that is interpretation is labeled as such. It is plain HTML, CSS and JavaScript with no build step, in Spanish and English, free and with no signup. The code is public on GitHub.
The ideas are mine; AI helped me build it.
I would really value feedback on two things: whether the charts are easy to read, and any number you think is wrong or missing.