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cllm

← use cases · Latency-focused operators

Latency-sensitive serving

Remove the scheduler, the syscall trap, and the userspace boundary so the CPU spends its cycles on the inference path and nothing else.

The problem

On a host OS, an inference process shares the machine with a scheduler, other processes, and a kernel that traps on every syscall. For a workload whose steady state is "do as much math as possible without being interrupted," those interruptions are exactly the tail-latency budget you are trying to protect.

Why cllm fits

  • No scheduler dispatching between unrelated processes — the main loop owns the CPU.
  • No syscall trap and no kernel/userspace transition on the hot path.
  • Deterministic boot and a flat memory model with no page faults.
  • A tractable place to apply ring-0 tricks to the inference path.

Honest caveats

  • Request handling is single-threaded today — one request at a time.
  • Inference itself is a stub until the engine integration lands, so end-to-end latency is not yet measurable.
  • We publish no latency benchmarks because there is no working inference path to benchmark.