AI

Kimi K3 architecture explained: Moonshot's 2.8T open MoE with 16/896 experts, Kimi Delta Attention, 1M context, GPQA 93.5, Terminal-Bench 88.3, pricing and how it compares in 2026.

Prefill/decode disaggregation splits LLM inference into separate compute-bound and memory-bound pools: KV-cache transfer, SLO isolation, and when it beats co-located serving in 2026.

Continuous batching (in-flight batching) for LLM inference: iteration-level scheduling, prefill/decode interleaving, and how it lifts GPU throughput without hurting latency in 2026.

GLM-5.2 architecture explained: Zhipu's 744B MoE with ~40B active, 1M-token IndexShare context, MIT weights, SWE-bench Pro 62.1, pricing, and how it compares in 2026.

LLM model routing architecture: how to route requests across models by cost, quality, and latency with semantic routers, cascades, and eval-driven policies in 2026.

Grok 4.20 architecture explained: the 4-agent council, 2M-token context, benchmarks, pricing, and how xAI's flagship compares to GPT-5 and Claude in 2026.