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ExpertMesh v0.2.0 — Kimi K2 target integration

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@manishklach manishklach released this 21 Jul 13:46
v0.2.0
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ExpertMesh v0.2.0 — Kimi K2 target integration path

This release turns ExpertMesh from a generic stationary-expert reference into a strict target path
for the official open-weight moonshotai/Kimi-K2-Thinking family.

Included

  • A fail-closed Kimi K2 configuration and Safetensors inventory adapter.
  • Immutable checkpoint manifests and deterministic stationary-expert owner plans.
  • A checked-in target profile for the documented 61-layer, 384-expert, top-8 MLA/SwiGLU design.
  • Paged KV-cache allocation and one-token decode semantic oracle.
  • Bounded continuous batching, runtime counters/latencies, and retry/cooldown failure semantics.
  • A fused packed-INT4 SwiGLU HIP correctness ABI, source, and build integration.
  • A K2 artifact-admission command: expertmesh-kimi-k2-inspect.

Validation

  • 18 CPU unit and integration tests pass.
  • Ruff static checks pass.
  • Source distribution and wheel build successfully.
  • GitHub Actions cpu-reference passed for pull request #4.

Important compatibility and performance boundary

v0.2.0 does not certify that Kimi K2 runs on ExpertMesh hardware. It intentionally refuses
incompatible checkpoint artifacts, but target compatibility remains gated on an official full
checkpoint, tokenizer/chat-template parity, MLA/RoPE/reference-output fixtures, native INT4 packing
verification, and ROCm GPU results.

Likewise, the HIP fused kernel is a correctness fallback—not a benchmarked MFMA implementation—and
TCP is a validated process-boundary transport, not GPU-direct RoCE. The documented release gates
must pass before either performance label is used.

Operator starting point

Read docs/KIMI_K2_TARGET.md, retain the official model license and revision, then run:

expertmesh-kimi-k2-inspect /models/Kimi-K2-Thinking --workers 32 --write-manifest

The command validates before GPU allocation and writes an immutable deployment manifest and owner
plan. See the release gates before treating any deployment as production-ready.

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