The local ds4-server is an sm_86 build against CUDA 13 and the local
colibri has no GPU backend: neither could be copied into a pod. The new
engines image compiles both, plus kimi-k3-in-c, in a CUDA 12.8 stage for
sm_80/86/89/90/120a (ds4's Blackwell kernels need the arch-specific
target; plain sm_120 fails in ptxas) on a portable x86-64-v3 baseline,
and fails the build if a binary cannot find its libraries.

A RunPod-only model names the engine on its runpod block (backend:
runpod takes the pin slot); a local model pinned to the engine and
bursting carries the pin. Either way the pod arrives with the engine
enabled and this install's settings forwarded (CODERAI_<ENG>_CONFIG),
and volume_path points it at weights already on the network volume —
the only sane way to run 150 GB+ models. The model page warns loudly
the moment one of these engines is picked. ktransformers is refused
with a reason: it has no pod image.

Also: the batch build/publish scripts no longer list core-light and
venv profiles as images.
Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_0182DhR1eFNPQyGmDrpHbedY