# DeepSeek-V4.1-Flash (552B MoE, MXFP4 experts) — 8x DGX Spark, in-memory Engram. # # P2.3 of the 2026-09-18 night: the first 8x trial. Operator's design: at 8x # the Engram table fits in DRAM (406 GB / 8 = 50.7 GB/node) — no disk mode, # no per-node sparse staging, no /engram-local mounts. The engram rows load # from the NAS checkpoint into DRAM once at boot (one-off NFS cost), decode # reads them from memory (no per-token disk reads). # # Memory math per node (121.6 GiB): weights 307.3 GB / 8 = 38.4 GB + engram # rows ~25.4 GB (the real table data is ~203 GB — the two 101.5 GB sparse # shards whose 4x /var/tmp copies of 48 GB real sum to 192 GB) + process # ~12 GB = ~76 GB. # # GMU: the lab DS4.1 policy says 0.91, but the GB10 admission check needs # free >= GMU x 121.63 and the baseline-reserved ~12.8 GiB leaves only # 108.8 GiB free at startup — 0.91 (110.7) fails the admission on GB10 # (first 8x boot, 2026-09-18 16:02: "Free memory on device cuda:0 # (108.78/121.63 GiB) ... less than desired GPU memory utilization"). 0.85 # (103.4) is the GB10-qualified prod value and still leaves ~27.6 GiB of KV # per rank (103.4 - 38.4 - 25.4 - 12), ≈ 3M tokens ≈ 6x 512K. # # Image: dsv41-flash:local (the tonyd2wild prod chain — engram.py patch # baked in; DSV41_ENGRAM_DISK simply NOT set here = memory mode). The # launcher syncs the image to dgx6-8 at serve time (dgx1-5 have it). # # This is also the natural "Boot D" test the 4x r37 bisect could not run: # engram WITHOUT the disk-read path. If the text is clean here while the r37 # 4x disk-mode run garbles, the bisect narrows to the lab tree's engram # disk-read path. engine = "vllm" name = "DeepSeek-V4.1-Flash MXFP4 (dsv41 img, 8x, DSpark k=5, Engram in DRAM)" docker_image = "dsv41-flash:local" docker_image_dir = "dsv41-flash" model = "deepseek-ai/DeepSeek-V4.1-Flash" required_nodes = 8 tensor_parallel_size = 8 pipeline_parallel_size = 1 distributed_backend = "mp" shm_size = "32gb" # NO recipe entrypoint: the base image bakes ENTRYPOINT ["vllm","serve"] # (vllm/vllm-openai), so the launcher's CMD (model + flags) completes it. args = [ # Stable gateway alias — clients/gateways keep the DeepSeek-V4-Flash # model name; no per-deployment config churn. "--served-model-name", "deepseek-v4-flash", "--trust-remote-code", "--distributed-executor-backend", "mp", "--gpu-memory-utilization", "0.85", "--max-model-len", "524288", "--max-num-seqs", "8", "--max-num-batched-tokens", "8192", # boot-4 fix: the V4 indexer backend refuses the smallest-listed block "--block-size", "128", # boot-10: exact capture sizes for DSpark k=5, SEQS=8 (multiples of 5 # and 6 up to 48 — every decode batch gets an exact FULL graph, no padding) "--compilation-config", """ '{"cudagraph_mode":"FULL_AND_PIECEWISE","cudagraph_capture_sizes":[5,6,10,12,15,18,20,24,25,30,35,36,40,42,48]}'""", "--speculative-config", """ '{"method":"dspark","num_speculative_tokens":5,"draft_sample_method":"probabilistic","rejection_sample_method":"block","enable_adaptive_verification":false}'""", "--tool-call-parser", "deepseek_v41", "--enable-auto-tool-choice", "--reasoning-parser", "deepseek_v41", "--default-chat-template-kwargs", """ '{"thinking": true, "reasoning_effort": "max"}'""", ] [env] HF_HUB_OFFLINE = "1" # Engram: MEMORY mode — DSV41_ENGRAM_DISK deliberately NOT set (the baked # engram.py patch defaults to "0" = in-DRAM table). At 8x the table fits: # 406 GB / 8 = 50.7 GB/node. # CUDA graphs: the Engram rows are staged in prepare_inputs (baked # model_state.py prestage patch) so the whole decode step is capturable VLLM_USE_BREAKABLE_CUDAGRAPH = "1" VLLM_HAS_FLASHINFER_CUBIN = "1" VLLM_USE_RUST_FRONTEND = "0" # runtime JIT wedge countermeasure (their boot-3 lesson): kernels are # prebuilt in the image, but any residual JIT must not OOM the box MAX_JOBS = "2" VLLM_ENGINE_READY_TIMEOUT_S = "3600" PYTORCH_CUDA_ALLOC_CONF = "expandable_segments:True" TORCH_CUDA_ARCH_LIST = "12.1a" FLASHINFER_CUDA_ARCH_LIST = "12.1a" OMP_NUM_THREADS = "2" # JIT caches persist per-node (self-namespace by engine version key; the # image prebakes the flashinfer 0.7.0rc1 SM120 kernels, first boots re-JIT # the rest) [[extra_mounts]] host = "~/sm121-cache/jit-121f/flashinfer" container = "/root/.cache/flashinfer" [[extra_mounts]] host = "~/sm121-cache/jit-121f/torchinductor" container = "/root/.cache/torchinductor" [[extra_mounts]] host = "~/sm121-cache/jit-121f/vllm" container = "/root/.cache/vllm"