The name now matches the model. `coder` serves
Qwen3-Coder-30B-A3B-Instruct, a 30.5B MoE with 3.3B active, quantized to
4-bit GPTQ. It is measured working on this node, not assumed.
Measured, on worker-1, driver 580.159.04, compute capability 7.0:
GET /v1/models -> id=coder, root=ModelCloud/Qwen3-Coder-30B-A3B-Instruct-GPTQMODEL-W4A16-A
POST /v1/chat/completions model=coder -> 200 in 3.18s,
"fn main() { println!(\"hi\"); }"
POST /v1/chat/completions model=reasoning -> 200 in 0.21s
Weights loaded in 15.61 GiB. torch.compile took 78s. The pod reached
1/1 Ready. `kubectl diff -f coder.yaml` returns empty, so the manifest
matches live state.
Two names are served on purpose: `coder` and `reasoning`. The rename
therefore needs no change to poimen-memory's LLM_MODEL, only its host.
That keeps the client working through the cutover.
Why not Qwen3-Coder-Next, the model in the original plan. It cannot run
here, and that is measured too. A v0.15.0 image on this free V100 gave:
TORCH 2.9.1+cu129
ARCH_LIST [] <- empty
RuntimeError: cudaGetDeviceCount() ... Error 803
fla: ModuleNotFoundError <- no GatedDeltaNet kernels
vLLM 0.15.0 requires compute capability 7.5 or higher and fails here
before it loads a model. Qwen3-Next's hybrid attention needs the `fla`
module, which the image does not ship. So this stays on the pinned
v0.11.0 image, which reports sm_70..sm_120 and works.
Qwen publishes this model as BF16 (61.1 GB) and FP8 only. V100 has no
FP8, and 61.1 GB does not fit 32 GB, so 4-bit GPTQ is the only form that
fits one card. The checkpoint is a community quant; the manifest says so
and names the reason.
reasoning.yaml stays listed until poimen-memory's LLM_CHAT_BASE moves
from reasoning-predictor to coder-predictor. Two GPUs are free, so coder
rolled out beside reasoning with no downtime.
## Summary
Replaces hand-applied `llm-serving-default-deny` NetworkPolicy with a git-managed, namespace-scoped policy that only allows traffic from the api-gateway.
**Issue:** #13
Co-authored-by: rock <[email protected]>
reasoning keeps its 2 GPUs untouched. verifier's freed GPU goes to a second ornith replica instead of a standalone qwen-only pod -- both replicas load ornith:35b + qwen2.5:3b-instruct, k8s Service load-balances across them, so 2 concurrent implementer-style calls get independent instances.
Frees verifier's GPU from an underused vLLM PRM deployment. qwen2.5:3b-instruct moves off ornith-predictor's shared pod onto its own dedicated GPU (grm.yaml), so verification/judge traffic stops contending with ornith:35b's agent traffic. /v1/qwen/chat/completions now points at grm-predictor; path unchanged.
rock
Story Crater Bot