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LLM Eval Suite
Structured evaluation of Apple Foundation Models on macOS
Structured scoring, leaderboard tracking, repeatable evals, and bring-your-own judge providers. Evaluate Apple Intelligence Foundation Models on macOS.
Hey everyone — I’m a solo iOS/macOS dev, and I recently built a macOS app called LLM Eval Suite.
It came out of a problem I kept running into while building AI features in my own apps.
I’d tweak a prompt or change generation settings, run the same examples again, and think:
“Okay… this seems better?”
But I didn’t have a good way to compare versions or see what actually improved.
Sometimes the output was cleaner, but less complete.
Sometimes it was more detailed, but added things it shouldn’t.
Sometimes I just liked the wording more, which isn’t really enough to ship a change confidently.
So I built LLM Eval Suite as a native macOS app to help compare prompt/config variants, review outputs side by side, and score them with custom judges and scoring guides.
I recently used it on another app I’m building, AI Doctor Notes, to improve a doctor visit summary feature. I wrote up the workflow here:
https://medium.com/@dreamlab.sol...
About LLM Eval Suite on Product Hunt
“Structured evaluation of Apple Foundation Models on macOS”
LLM Eval Suite was submitted on Product Hunt and earned 1 upvotes and 1 comments, placing #111 on the daily leaderboard. Structured scoring, leaderboard tracking, repeatable evals, and bring-your-own judge providers. Evaluate Apple Intelligence Foundation Models on macOS.
On the analytics side, LLM Eval Suite competes within Mac, Artificial Intelligence and Apple — topics that collectively have 587.5k followers on Product Hunt. The dashboard above tracks how LLM Eval Suite performed against the three products that launched closest to it on the same day.
Who hunted LLM Eval Suite?
LLM Eval Suite was hunted by Francisco Mendoza. 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.
For a complete overview of LLM Eval Suite including community comment highlights and product details, visit the product overview.
Francisco Mendoza