nvidia/Qwen3.6-35B-A3B-NVFP4 (modelopt MIXED_PRECISION MoE: NVFP4 gs16
expert FFNs + FP8-static attention + unquantized mtp.* head, 23.4 GB, 3B
active) — sibling of the 27B nvfp4 pair (#603), same authored-blind /
required_sm=9.0 / community-validated pattern. The single slug is the
GB10/DGX-Spark marquee: a 3B-active MoE is the right shape for
big-capacity, lower-bandwidth unified-memory parts — kv-calc says full
262K at 25% of a GB10's budget (MoE KV is tiny, ~1.3 GB @131K).
Two deliberate deltas vs the 27B nvfp4 composes:
- NO MTP (drafter=None): our measured finding on this MoE — the built-in
head shares the MoE forward and is net-negative (-51%); headers forbid
blind re-adding.
- fp8/e4m3 KV at scale=1.0: this checkpoint has NO baked KV scales
(kv_cache_scheme null, unlike the 27B) — same regime the production 27B
fp8 tier quality-tied at (#594); flagged as a known-unknown.
- vllm/qwen-35b-a3b-single-nvfp4 (:8078, 🧪) — 131K default for 5090
32 GB (kv-calc 27.4/29.4 @93%); GB10 raises to 262K via MAX_MODEL_LEN.
- vllm/qwen-35b-a3b-dual-nvfp4 (:8079, 🧪) — TP=2 @262K, 15.7 GB/card
(53%) on 2x 5090.
Wiring mirrors #603: weights entry + weights.py aliases + kv-calc
(weights_nvfp4_gb on the MoE spec, nvfp4 branch, cfg map, aliases) +
registry entries (kvcalc-priced, no DEFAULTS rows) + counts 61/62. Full
scripts/tests suite + kv-calc --calibration green; sm_86 → incompatible-hw
(auto-hidden in c3 per #604), rtx-5090 → fits-clean 27.4/15.7 GB.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01EfF565T9eSLaqGzidyJ1Pm
1ba1a89d7c