Deep-Dive LLM Technology
Cutting-edge techniques from DeepSeek, Google, and the open-source frontier — explained with interactive 3D visualizations you can rotate, click, and explore.
How DeepSeek compresses the KV cache into a single latent vector — cutting memory 9× without losing quality. The signature architecture of DeepSeek-V2 and V3.
Inference EfficiencyHow FP8 and INT4 KV cache quantization halves serving memory, and the outlier-preservation tricks (KIVI, KVQuant) that prevent quality collapse at 4-bit.
Inference AccelerationHow a tiny draft model guesses tokens in bulk and a large model verifies them in one pass — 2-3× faster inference with mathematically zero quality loss.
Long ContextHow million-token contexts are split across GPUs in a ring — each GPU computes attention on its shard while KV blocks circulate. Powers Llama 3 and Gemini's long context.