ALTERNATIVE

Best Cold-Boot LLM Inference Alternative

Standard inference without state preservation

What is Cold-Boot LLM Inference?

Traditional approach where each agent branch re-runs prefill over shared context

✅ What Cold-Boot LLM Inference does well

  • • Simple
  • • Standard approach

❌ Limitations for Agents

  • • Wasteful for branching
  • • Re-prefills same context N times
  • • Expensive for RL rollouts and parallel attempts

Why AI Agents are replacing Cold-Boot LLM Inference

Thaw snapshots inference state (weights, KV cache, scheduler) to fork branches near-free, achieving ~400× speedup over cold-boot equivalents

Common Use Cases

RL agent trainingBest-of-N samplingParallel coding attempts