Ever wondered what a GPU goes through during a massive language model inference run? While you type a query and wait for tokens, the silicon under the hood is holding together a fragile house of cards: balancing context window limits, scheduling activations, managing weights, and evading malicious adversarial attacks.
To teach you how LLMs behave (and fall apart) under load, I built an interactive game:
Play in Fullscreen Mode (if the embed sizing is tight) Before initiating your run, choose your difficulty configuration (each represented by a unique retro pixel chip sprite and custom parameters):
2.8
), boosted damage, and a wide collection window. You get +25%
XP gains and start with both the Attention Beam and the Softmax Aura active.2.5
), standard damage, and standard 100%
XP gains. Starts with the Attention Beam active.2.1
), reduced damage, and a -20%
XP penalty. Starts with a single Attention head active.This isn't just a homage to Vampire Survivors—every upgrade, weapon, and enemy represents a real-world concept in modern machine learning. Here is how the in-game mechanics map directly to how Large Language Models operate, fail, and optimize in production:
At exactly 15:00, all standard enemies are swept away, and the unkillable red boss Hardware Degradation arrives. You cannot harm it.
Can you survive a 1T parameter inference run?
Welcome to GPU Survivors, an interactive 2D retro action-roguelike built to simulate the architectural limits, failure modes, and optimization hyperparameters of running a Large Language Model under load.
In the digital deep, bad data and chaotic vectors threaten inference stability. You are a GPU Core initializing a new language model. Survive the endless incoming waves of training loads (OOD outliers, prompt injections, and data biases), gather FLOPs (XP), and scale your architecture to 1T parameters!
WASD
or Arrow Keys
.Escape
or P
to the run, resume, or exit.Select your inference endpoint difficulty at startup:
Disclaimer: AI was used throughout this project, it is just fitting that it would co-author with me, so special thanks to the Foundry for its tireless hours toiling away and Gemini for producing the cover image.