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LoRA Speedrun
A verified speedrun leaderboard for LLM fine-tuning
Fine-tune the same model to the same score on the same GPU — fastest training run wins. Every record is re-run 3x with fresh seeds by a referee before it counts, so no self-reported numbers. The baseline took 11:57; three days and three verified records later, the community has it at 1:44. Attempting is free.
Hey PH! I built this because I fine-tune small models on a budget and could
never tell which speedup claims were real — every technique reports numbers
on different models, data, and hardware.
So I froze one task (train Qwen2.5-1.5B to 57% on GSM8K), one GPU, and made
a rule: your score is your training wall-clock, and nothing counts until a
referee re-runs your code 3x with fresh seeds on identical hardware, in a
locked-down sandbox.
What happened next was the fun part: the baseline was 11:57. Within three
days, outside contributors took it to 1:44 — a 6.9x speedup, every step
verified and explained in a public report. The leaderboard doubles as a lab
notebook of what actually makes fine-tuning fast.
It's free to attempt (runs on Modal's monthly free credits), there's a second
track (different model + task) so tricks have to transfer, and the open lanes
(torch.compile, QLoRA...) are listed as GitHub issues anyone can claim.
Would love feedback — and if you beat 1:44, your name's on the board
permanently.
Tried the 5-minute variant last night and being timed against the wall clock made it way more engaging than my usual Colab sessions. Surprised how tight the leaderboard feels with that referee rerun system.
A public log of every submission attempt would be great, even just the timestamps and which configs were tried even if they failed verification. Right now you only see the records that stuck, but seeing the misses is honestly where half the learning happens for people trying to figure out what actually works.
About LoRA Speedrun on Product Hunt
“A verified speedrun leaderboard for LLM fine-tuning”
LoRA Speedrun was submitted on Product Hunt and earned 6 upvotes and 3 comments, placing #109 on the daily leaderboard. Fine-tune the same model to the same score on the same GPU — fastest training run wins. Every record is re-run 3x with fresh seeds by a referee before it counts, so no self-reported numbers. The baseline took 11:57; three days and three verified records later, the community has it at 1:44. Attempting is free.
LoRA Speedrun was featured in Open Source (68.6k followers), Developer Tools (516.2k followers), Artificial Intelligence (474.1k followers) and GitHub (41.3k followers) on Product Hunt. Together, these topics include over 223.9k products, making this a competitive space to launch in.
Who hunted LoRA Speedrun?
LoRA Speedrun was hunted by Sai Vineeth Arumalla. 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.
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Sai Vineeth Arumalla