I built a lite LPU that can do inference on Karpathy's MicroGPT
We had no guide or course that teaches chip design at our university. We had taken a digital logic course, but were disappointed with the fact that the most complex project we did was building a full adder in Quartus using logic blocks, not even in RTL!5 Therefore, we decided to challenge ourselves to dive deep into machine learning (ML) hardware and learn as much as we could on our own. We wanted to prove that basic math (like y = mx + b) and basic logic circuits are enough to help anyone understand how modern AI hardware works. Our goal was to design our own version of the LPU from scratch…
I built a lite LPU that can do inference on Karpathy's MicroGPT launched on August 24, 2026 with 18 votes, #769 of 23,274 launches that month and more than 90% of that year's launches.
In plain words
LPU Lite is a language processing unit designed by students to run inference on small transformer models like MicroGPT. Built from scratch without prior chip design experience, it demonstrates that fundamental mathematics and logic circuits are sufficient to understand AI hardware architecture. The project aims to demystify specialized processor design by recreating a simplified version of Groq's proprietary LPU, proving that basic knowledge of digital logic can enable anyone to build functional machine learning hardware.
written from the facts on this page · September 2026
From the sources
LPU Lite: a language processing unit built from first principles.
a lite language processing unit by Saksham Batra, Michael Trbovic, and Arjun Harinath. With no previous chip design knowledge, we decided to figure it out ourselves and see how far we could get! We wanted to demystify AI hardware by reinventing a fully functional LPU from scratch to run a Transformer! LPU stands for Language Processing Unit. It is a specialized computer chip developed by Groq 1 specifically for running large language models such as ChatGPT and Claude. Groq has kept the secret of their LPU closed-source and only left small hints in their research paper. 2 , 3 The LPU differs from a traditional chip in many ways, but the overarching idea is “deterministic execution.”…from lpulite.com
In the maker’s words, at launch
We had no guide or course that teaches chip design at our university. We had taken a digital logic course, but were disappointed with the fact that the most complex project we did was building a full adder in Quartus using logic blocks, not even in RTL!5 Therefore, we decided to challenge ourselves to dive deep into…
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I built a tiny LLM to demystify how language models workApr 2026 · github.com · ▲915Built a ~9M param LLM from scratch to understand how they actually work. Vanilla transformer, 60K synthetic conversations, ~130 lines of PyTorch. Trains in 5 min on a free Colab T4. The fish thinks the meaning of life is food. Fork it and swap the personality for your own character.
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We wanted to do something very challenging to prove to ourselves that we can do anything we put our mind to. The reasoning for why we chose to build a toy TPU specifically is fairly simple: - Building a chip for ML workloads seemed cool - There was no well-documented open source repo for an ML accelerator that performed both inference and training None of us have real professional experience in hardware design, which, in a way, made the TPU even more appealing since we weren't able to estimate exactly how difficult it would be. As we worked on the initial stages of this project, we…


- ATA tiny LLM running at 21,000 tok/s on a $250 FPGA (Live Demo)Aug 2026 · mikeayles.com · ▲79
A 3.16M-parameter INT4 transformer running entirely in the on-chip memory of a Xilinx Kria KV260. Zero DRAM in the token loop, 59,965 tok/s on the fabric, bit-exact. Chat with it live.
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