Upstream watch — 2026-10-16 (night shift)

Autonomous pass during the 10-15→16 night shift. Focus: the two queued models (Ling-3.1-flash, Step-5-Preview) + repo/forum deltas. Launcher-side only; no new node deploys (cluster powers off at end of shift).

The two queued models — feasibility (the headline)

Ling-3.1-flash (inclusionAI) — arch SUPPORTED on our base, but no small weights yet

Architecture: BailingMoeV3ForCausalLM (model_type: bailing_hybrid, custom_code, fp8). Ant Group's Ling/Bailing MoE-V3 line.
vLLM v0.31.0 (our kindling base) already registers it: BailingMoeV3ForCausalLM → bailing_moe_v3 AND BailingMoeV3MTPModel → bailing_moe_v3_mtp (MTP head supported). So no nightly vLLM needed — the earlier "requires nightly" note is stale for the arch. A Ling lane can ride a v0.31.0-based image (kindling or stock).
BUT the day-0 NVFP4 cut cbfight/Ling-3.1-flash-NVFP4-lossless8 is an EMPTY repo (only .gitattributes, 0 bytes) — reserved, not populated. So the cheap 4x-lane (NVFP4 ≈ GLM-5.3-Flash class) is not available yet.
The only vLLM-loadable Ling today is the original inclusionAI/Ling-3.1-flash (fp8, 572B total, ~689 GB) → TP8+EP8 = all 8 Sparks. Not a 4x lane.
Other cuts are GGUF/EXL3 (llama.cpp / exllamav3), not our vLLM stack: AtomicChat/Ling-3.1-flash-GGUF, AMAImedia/...-BF16-GGUF, vcruz305/...-EXL3-SAGE-*.
Action: watch cbfight (and inclusionAI) for a real NVFP4/FP8-small cut → then a 4x lane on a v0.31.0 base is straightforward (arch already works). A 572B-fp8 8x lane is possible but heavy (689 GB download + all 8 Sparks); not attempted overnight before power-off. Recipe authored as prep: recipes/ling-31-flash-nvfp4/ (targets the future NVFP4 cut; 4x).

Step-5-Preview-NVFP4 (stepfun-ai) — VL model, needs the dedicated image

Architecture: Step5ForConditionalGeneration (model_type: step5_vl) — a vision-language model (8-bit, modelopt/NVFP4), NOT text-only.
vLLM v0.31.0 registers StepVLForConditionalGeneration (step_vl) but not Step5ForConditionalGeneration (step5_vl) — a different, newer arch. So stock v0.31.0 won't load it; needs the dedicated image vllm/vllm-openai:step-5-preview (or a vLLM new enough to carry step5_vl).
604B, ~473 GB → 8 Sparks (TP8). GB10/sm_121a unverified (kernels, UMA memory gate vLLM #48140, GMU). This is a research probe, not a bench target.
Action: recipe authored as prep recipes/step5-preview-nvfp4/ (dedicated image, 8x). A live GB10 probe needs the 8x cluster up + a 473 GB download — deferred to a supervised window (wasteful to pull overnight before power-off).

Repo deltas (GitHub / Docker)

vLLM: latest stable tag still v0.31.0; v0.32.0 is rc0/rc1/rc2 only (no stable). Our kindling base (v0.31.0) is current. Do NOT re-pin overnight — the v0.32.0 stable re-pin + 38-overlay rebase is a supervised, bench-gated task.
HawkBearPig/dgpp: HEAD moved to d9311e72… (our recipe pin is 3ad63d6b…). DGPP is active daily. Consider bumping the pin after reading the changelog (supervised) — the provisioning marker keys on rev, so a bump triggers a clean rebuild.
kindlingai/gr8: HEAD 3df902dc…, active.
SeraphimSerapis/tool-eval-bench: latest tag v2.8.0 = our pin. No newer release; harness stays pinned (do not upgrade casually — re-baseline anchors).
vllm/vllm-openai (Docker Hub): step-5-preview tag is the Step-5 base (dedicated image, per the model's requirement).

DGPP w2 live-run findings (from the provisioning test, 2nodes-dac)

Provisioning (clone-at-pin → release.sh → install → up) now works end-to-end (4 launcher bugs fixed — see engine-drivers.md). DGPP's own preflight then gates on deployment prereqs the launcher does NOT own:

Checkpoint missing — HawkBearPig/GLM-5.3-Flash-NVFP4-FP8 not in the node HF cache. DGPP: python3 scripts/download_model.py --config <file> on rank 0 (or pre-stage the snapshot). ~GLM-5.3-Flash class size.
RoCE lanes — "the transport supports at most two lanes; select DGPP_ROCE_DEVICES explicitly" on multi-fabric hosts. The site .env needs DGPP_ROCE_DEVICES set to the two fabric devices (per the DGPP thread 383406). Not yet encoded in the launcher's generated .env — a candidate follow-up (derive from config nccl.ib_hca, or a recipe [dgpp].roce_devices).
Preflight is strict: any FAIL → "no services started". So w2 needs BOTH the model and the RoCE selection before it serves.

Forum mining (DGPP thread 383406, 107 posts)

Post #106 (DGPP author, the newest release notes = the HEAD d9311e72 that moved past our 3ad63d6b pin) adds: dense Qwen3.8-27B support, three quantization options across Qwen and full GLM-5.3, DGPP_NO_SWAP=1 (launch ranks in a systemd scope that disallows swap — directly relevant to the GB10 unified-memory swap problem), a 1-second decode-gap target (worst mixed- workload pause 1.8s → 0.5s), and faster long-context GLM prefill. This is a strong reason to bump the DGPP pin (supervised — read the full changelog + re-bench; the marker keys on rev, so a bump cleanly rebuilds).
Post #73 (community 2x DGPP): 2× ASUS GX10, driver 580.173.02, CUDA 13.0.88, one ConnectX-7 RoCE lane per node (200G, GID 3) via a switch — matches our fabric. Confirms DGPP wants an explicit single-lane selection.
The thread does NOT document the exact DGPP_ROCE_DEVICES value syntax (only DGPP_NO_SWAP). The device names come from the preflight output (roceP2p1s0f0/f1, rocep1s0f0/f1); the DGPP repo docs/config are the source of truth for the exact env format. Candidate launcher follow-up: a [dgpp].roce_devices recipe field → emit DGPP_ROCE_DEVICES in the .env.

Not done overnight (deferred, supervised)

Ling 572B-fp8 8x lane (689 GB + all 8 Sparks) and Step-5 8x GB10 probe (473 GB + dedicated image) — both heavy downloads that a power-off would not waste (NVMe caches persist) but are too large/risky to run unsupervised, and the arch/image prerequisites need a supervised base decision.
DGPP w2 full serve — needs model download + DGPP_ROCE_DEVICES; the launcher side is validated.

upstream-watch-2026-10-16.md 6.3 KB Historia Raaka