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Show HN: NanoEuler – GPT-2 scale model in pure C/CUDA from scratch
GPT-2 scale model in pure C/CUDA from scratch. Working on LLM with a very low-level layer to understand the correlation between parameters and data and growth of the model and how the GPU works and how some layers can be optimized. Not using any intermediary between the model in training and inference.
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GPT-2 scale model in pure C/CUDA from scratch. Working on LLM with a very low-level layer to understand the correlation between parameters and data and growth of the model and how the GPU works and how some layers can be optimized. Not using any intermediary between the model in training and inference.
NanoEuler represents a deep dive into foundational LLM architecture, built from scratch in C/CUDA. While not a direct B2B SaaS offering, its existence highlights a critical trend: the increasing need for granular understanding and optimization of AI models at the hardware level. For B2B SaaS providers integrating or developing proprietary LLMs, this low-level approach offers insights into performance bottlenecks, cost efficiencies, and custom hardware acceleration. The drive to understand 'how the GPU works' and 'how some layers can be optimized' directly impacts the operational expenditure and latency of AI services. This project underscores the value of fundamental research and engineering in AI, which can translate into competitive advantages for SaaS companies through highly optimized, specialized models or more efficient inference engines.
Hi everyone,I started working on nanoeuler after the ban of anthropic's fable because my ambition and dream is to work in the AI field in anthropic. The two interesting reasons that led me to create nanoeuler were (1) interfacing with llm does not mean understanding how they are composed and (2), working on llm with a very low-level layer to understand the correlation between parameters and data and growth of the model and how the GPU works and how some layers can be optimized.So I started working on it with a research aspect by making nanoeuler grow more and more but doing one step after another starting from Shakespeare.txt and understanding what a text generation model understands at 23 million parameters. For example, nanoeuler at that number had understood that Name: started a line and wrote that line with sense.I wrote everything in CUDA because I wanted to not use any intermediary between the model in training and inference and what it had to do. Then the use of SFT and much more, even if in small ways, were really useful to understand the various step to make an llm like a chatbot.Any feedback, help, or suggestions are absolutely welcome!
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What is NanoEuler – GPT-2 scale model in pure C/CUDA from scratch?
NanoEuler – GPT-2 scale model in pure C/CUDA from scratch is analyzed by our AI as: GPT-2 scale model in pure C/CUDA from scratch. Working on LLM with a very low-level layer to understand the correlation between parameters and data and growth of the model and how the GPU works and how some layers can be optimized. Not using any intermediary between the model in training and inference.. It focuses on NanoEuler represents a deep dive into foundational LLM architecture, built from scratch in C/CUDA. While not a direct B2B SaaS offering, its existe...
Where did NanoEuler – GPT-2 scale model in pure C/CUDA from scratch originate?
Data for NanoEuler – GPT-2 scale model in pure C/CUDA from scratch was aggregated directly from the Hacker News community ecosystem, representing raw developer and early-adopter sentiment.
When was NanoEuler – GPT-2 scale model in pure C/CUDA from scratch publicly launched?
The initial public indexing or launch date for NanoEuler – GPT-2 scale model in pure C/CUDA from scratch within our tracked developer communities was recorded on June 29, 2026.
How popular is NanoEuler – GPT-2 scale model in pure C/CUDA from scratch?
NanoEuler – GPT-2 scale model in pure C/CUDA from scratch has achieved measurable traction, logging over 39 traction score and facilitating 9 recorded discussions or engagements.
Which technical categories define NanoEuler – GPT-2 scale model in pure C/CUDA from scratch?
Based on metadata extraction, NanoEuler – GPT-2 scale model in pure C/CUDA from scratch is categorized under topics such as: GPT-2 scale model, pure C/CUDA, low-level layer, parameters and data.
How does the creator describe NanoEuler – GPT-2 scale model in pure C/CUDA from scratch?
The original author or development team describes the product as follows: "Hi everyone,I started working on nanoeuler after the ban of anthropic's fable because my ambition and dream is to work in the AI field in anthropic. The two interesting reasons that led me to cre..."
Community Voice & Feedback
I'm genuinely curious how much of this is LLM generated?
Mentioning neural ODE doesn't make sense here, as this is unrelated. Basically any implementation of transformer uses residuals, but you're not really training a neural ODE here.Also consider getting rid of the em-dashes. I don't know if you mostly vibe-coded this or not, but the README is pretty clearly AI generated.
How long was it trained for? How many tokens?
Very weird coding style, did you run astyle --style=python on C code?Also, your LLM left a comment in the cuda source that it is untested, does the cuda stuff work?
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