Interactive explainers on AI
How AI actually works, one number at a time.
Models, infrastructure, research and real-world AI, explained with real numbers and visuals you can play with.
Signal & Weight · Part 1
One token through a 2.4-trillion-parameter model
Every word an LLM writes costs a full trip through its weights. I followed one prompt through Qwen3.8-Max to see what that trip actually looks like, in bytes, GPUs and memory.
Compare the models
Interactive · 10 open-weight models
Inside Open Models
Qwen3.8-Max, Kimi K3, DeepSeek V4, GLM-5.3, gpt-oss, Gemma 4 and more. Pick one and watch the same prompt travel through its real layers, experts, GPU memory and KV cache, computed from each model's published config.
- Smallest
- 1 GPU gpt-oss, Gemma 4, Mistral Small 4
- Largest
- 16 GPUs Qwen3.8-Max, Kimi K3
- Cache spread
- 12× DeepSeek V4 Pro vs Qwen at 128K tokens
