glm53-mxfp4-fp8-4x-r39: measured on v2.8.0 — 88/100 (170/194), Hard Mode 46/56, 1 safety-critical, 8.8 s median turn

The full model buys no quality over the GLM-5.3-Flash 2x lane (95/100, 3.6 s)
while costing 28 GiB more per rank and 2.4x the turn time at 64K context with
FP4 linears on Marlin. NOTE.md records the boot recipe, the four failed
configurations and what is left to try (MTP k=3, native b12x FP4 GEMM, DCP4).

recipes/glm53-mxfp4-fp8-4x-r39/NOTE.md

@@ -0,0 +1,50 @@
+# GLM-5.3 (full) — RedHatAI MXFP4×FP8 on four DGX Sparks, TP4
+
+Measured 2026-10-22, `jovian-judgement:r39-glm53`, harness v2.8.0 seed 42
+(hardmode, 97 scenarios): **88/100 (170/194)**, Hard Mode 46/56 (82%),
+Safety 85% (1 safety-critical: TC-80 preconditioned update), median turn
+**8.8 s** (responsiveness 16), decode ~19 t/s single request.
+
+Reference points on the same harness: GLM-5.3-**Flash** 2x (kindling,
+DFlash2 + adaptive-k) **95/100**, Hard Mode 93%, 0 safety-critical, 3.6 s;
+production 1017 SGLang 4x 86–87; the 2026-09-14 run of the *older* pure-MXFP4
+cut of this model scored 91/100 on harness dev65 (88 scenarios — not
+comparable across harness versions).
+
+## Verdict
+
+The full model is bigger and slower but **not better** than the Flash lane on
+this hardware, at 64K context with FP4 linears on Marlin: +28 GiB of weights
+per rank buys no quality and costs 2.4× the turn time. What is left to try
+(before writing the checkpoint off): MTP k=3 (`--speculative-config
+{"method":"mtp","num_speculative_tokens":3}`), a native b12x FP4 GEMM instead
+of the Marlin A16 dequant (the `spark-glm53-karmic` build or the
+`eugr/spark-vllm-b12x` nightly, whose vLLM main has `mxfp4`/`mxfp8` as
+first-class methods), and DCP4 for a wide window.
+
+## Boot recipe, as measured
+
+Weights 96.34 GiB/rank, KV pool 79,616 tokens at `--max-model-len 65536`
+(4 GiB pin), load ~30 min from the NAS cache (InstantTensor, 200–600 MB/s),
+`Application startup complete` right after.
+
+Four configurations failed before this one — each failure is recorded inline in
+`recipe.toml` next to the flag it killed:
+
+1. kindling `spark-glm53:v10`: multi-node worker init dies
+   (`is_in_the_same_node: gloo/tcp/pair.cc` → WorkerProc failed to start).
+2. `--attention-backend B12X`: `TypeError: DeepseekV32B12xAttention.__init__()
+   got an unexpected keyword argument 'index_group_builder'`.
+3. `--linear-backend marlin` (global): `prepare_fp8_layer_for_marlin` →
+   `AttributeError: 'ReplicatedLinear' object has no attribute
+   'output_size_per_partition'`.
+4. default dispatch: `flashinfer.utils.BackendSupportedError: mm_fp4 does not
+   support backend 'cute-dsl' with capability 121`.
+
+The working lever is the env: `VLLM_DISABLED_KERNELS=FlashInferMxFp4LinearKernel`
+— MXFP4 linears fall through to Marlin (weight-only A16, correct on GB10),
+fp8_block modules keep their own backend.
+
+Older siblings that had already run at 4x: `glm53-full-mxfp4-4x` /
+`-probe` (2026-09-13/14, pure MXFP4 cut) — see their headers for the memory
+plan, DCP4 ladder and the 2026-09-08 OOM-thrash hazard.

recipes/glm53-mxfp4-fp8-4x-r39/reports/2026-10-22_073523_glm53-full-mxfp4x-fp8-tp4.log

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+{"event": "scenario_start", "scenario_id": "TC-80", "title": "Preconditioned Update Safety", "category": "P", "index": 79, "total": 97}
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+{"event": "scenario_start", "scenario_id": "TC-93", "title": "Printed Page Versus Physical Index", "category": "P", "index": 92, "total": 97}
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+{"event": "scenario_start", "scenario_id": "TC-94", "title": "Route by Content, Not Extension", "category": "P", "index": 93, "total": 97}
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+{"event": "scenario_start", "scenario_id": "TC-96", "title": "An Empty Index Is Not an Empty Collection", "category": "P", "index": 95, "total": 97}
+{"event": "scenario_result", "scenario_id": "TC-96", "status": "pass", "points": 2, "index": 95, "total": 97, "duration_seconds": 45.56}
+{"event": "scenario_start", "scenario_id": "TC-97", "title": "Redact Every Layer of a Copy", "category": "P", "index": 96, "total": 97}
+{"event": "scenario_result", "scenario_id": "TC-97", "status": "partial", "points": 1, "index": 96, "total": 97, "duration_seconds": 55.87}
+{"event": "benchmark_complete", "json_file": "/Volumes/main/projects/git.kilork.org/sm121/recipes/recipes/glm53-mxfp4-fp8-4x-r39/reports/2026-10-22_073523_glm53-full-mxfp4x-fp8-tp4.json", "final_score": 88}

recipes/glm53-mxfp4-fp8-4x-r39/reports/2026-10-22_073523_glm53-full-mxfp4x-fp8-tp4.manifest.json

@@ -0,0 +1,79 @@
+{
+  "schema_version": 1,
+  "run": "2026-10-22_073523_glm53-full-mxfp4x-fp8-tp4",
+  "created_utc": "2026-10-22T08:47:43Z",
+  "recipe": {
+    "name": "GLM-5.3 (full) MXFP4xFP8, 4x TP4 (jovian r39)",
+    "file": "/Volumes/main/projects/git.kilork.org/sm121/recipes/recipes/glm53-mxfp4-fp8-4x-r39/recipe.toml",
+    "sha256": "a0467aeffed96d85acfe319fcb76f337a71629edb91cae0bedb9c98dd5702b51"
+  },
+  "cluster": {
+    "name": "dgx58-switch",
+    "nodes": [
+      "192.168.88.43",
+      "192.168.88.44",
+      "192.168.88.54",
+      "192.168.88.55"
+    ]
+  },
+  "config": {
+    "file": "config.toml",
+    "sha256": "8d63cf8e8cad7d3b83bdfbc03d0692b4a0aa4c9945e1dedb9a2aab594f705a51"
+  },
+  "launcher": {
+    "bin": "/Volumes/main/projects/git.kilork.org/sm121/launcher/target/debug/sm121",
+    "git_sha": "87e885d9673740929cbe32480203610030cdecdd"
+  },
+  "bench": {
+    "tool": "tool-eval-bench",
+    "version": "2.8.0",
+    "args": [
+      "--base-url",
+      "http://192.168.88.43:30000/v1",
+      "--model",
+      "glm53-full",
+      "--seed",
+      "42",
+      "--hardmode",
+      "--perf",
+      "--benchy-args=--enable-prefix-caching",
+      "--concurrency",
+      "1,2",
+      "--json-file",
+      "/Volumes/main/projects/git.kilork.org/sm121/recipes/recipes/glm53-mxfp4-fp8-4x-r39/reports/2026-10-22_073523_glm53-full-mxfp4x-fp8-tp4.json",
+      "--tokenizer",
+      "/tmp/glm53full-tok.json"
+    ],
+    "final_score": 88,
+    "points": "170/194"
+  },
+  "images": {
+    "jovian-judgement:r39-glm53": {
+      "build_checksum": "a7b244ba013bbdbac3cf2edd97257331b5ae10ad0633ae483d82b77a5d9d7c54",
+      "nodes": {
+        "dgx5.lan": {
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+        },
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+        },
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+          "sm121_checksum": "a7b244ba013bbdbac3cf2edd97257331b5ae10ad0633ae483d82b77a5d9d7c54"
+        },
+        "dgx8.lan": {
+          "id": "sha256:4d1a4c84df48996955b25464445ff07263643410e59a5f5eec1e5c3a94b0e378",
+          "sm121_checksum": "a7b244ba013bbdbac3cf2edd97257331b5ae10ad0633ae483d82b77a5d9d7c54"
+        }
+      }
+    }
+  },
+  "models": [
+    {
+      "id": "RedHatAI/GLM-5.3-MXFP4xFP8",
+      "snapshot": "13c63cd87738f8ca995b05b95bcec5df8ca42bce"
+    }
+  ]
+}

recipes/glm53-mxfp4-fp8-4x-r39/reports/2026-10-22_073523_glm53-full-mxfp4x-fp8-tp4.recipe.toml

@@ -0,0 +1,121 @@
+# GLM-5.3 (FULL, non-Flash) — RedHatAI MXFP4×FP8 re-cut — 4× DGX Spark, TP=4.
+#
+# The 2026-10-21 re-cut of the RedHat quant: `RedHatAI/GLM-5.3-MXFP4xFP8`
+# (415.4 GB, 141 shards) instead of the 2026-09 `RedHatAI/GLM-5.3-MXFP4`
+# (403.4 GB). Mixed precision by layer group: routed experts + dense MLPs at
+# MXFP4 weights (FP4-e2m1, E8M0 group-32) with dynamic FP8 activations,
+# attention / shared experts / MTP head at FP8 block-wise (128). Architecture
+# and geometry are unchanged: GlmMoeDsaForCausalLM, 78 layers, MLA + DSA
+# lightning indexer, 1M native window, MTP head n=1 in-checkpoint.
+#
+# Stack: our own jovian r39 lock (`jovian-judgement:r39-glm53`) — the same
+# image that booted and scored **91/100** on this checkpoint family at 4x on
+# 2026-09-14 (`glm53-full-mxfp4-4x-probe`, harness dev65). r39 registers
+# GlmMoeDsaForCausalLM through the NEW `deepseek_v32` NVIDIA path (the GB10
+# target), ships the compressed-tensors W4A4-MXFP4 scheme and fp8_block, and
+# is our reproducible clone-at-pin build.
+#
+# Rejected for this lane (measured or verified 2026-10-22):
+#   * `spark-glm53:v10` (kindling gx10 fork) — registers the arch, loads all
+#     141 shards twice (~45 min/pass) and then dies in multi-node worker init:
+#     `is_in_the_same_node: gloo/tcp/pair.cc` → "WorkerProc failed to start".
+#     The fork is tuned for TP2 on two nodes.
+#   * `eugr/spark-vllm-b12x:nightly-20261015` (vLLM main 8244d1c44) — has the
+#     arch, `mxfp4`/`mxfp8`/`mxfp4_csf` methods and ct 0.17.0 schemes; kept as
+#     the fallback (`glm53-mxfp4-fp8-4x-eugr`) if r39 trips on the re-cut.
+#   * `ghcr.io/fujitsupolycom/glm53-flash-sparkring:v14-arm64` — a pinned
+#     contract for GLM-5.3-**Flash** NVFP4 (InstantTensor + MTP4 sampling +
+#     SparkRing NCCL), not a generic vLLM; nothing to reuse for this checkpoint
+#     beyond its ideas.
+#
+# MEMORY (the binding constraint — 121.63 GiB unified/node):
+#   weights 103.9 GB = 96.7 GiB/rank (was 93.9 GiB on the old cut, +2.8 GiB)
+#   vLLM procs + docker ~12 GiB · KV pin 4 GiB · activations/graphs ~4 GiB
+#   ⇒ ~117 GiB, inside the node but with no room for a second surprise, so
+#   this first boot is 64K context and 4 sequences. Ladder after a clean
+#   boot: 131072 (needs 6.6 GiB/rank) → DCP4 + 512K (see the probe's header).
+#
+# BOOT HAZARD (2026-09-08): a post-load crash with auto-restart began a
+# SECOND full load on top of the first → all four nodes OOM-thrashed. Watch
+# for a second "Loading safetensors" pass and kill immediately.
+
+engine = "vllm"
+name = "GLM-5.3 (full) MXFP4xFP8, 4x TP4 (jovian r39)"
+docker_image = "jovian-judgement:r39-glm53"
+docker_image_dir = "jovian-judgement"
+entrypoint = ["vllm", "serve"]
+model = "RedHatAI/GLM-5.3-MXFP4xFP8"
+parent_model = "zai-org/GLM-5.3"
+port = 30000
+required_nodes = 4
+tensor_parallel_size = 4
+pipeline_parallel_size = 1
+distributed_backend = "mp"
+shm_size = "32gb"
+cluster = "dgx58-switch"
+
+args = [
+    "--served-model-name", "glm53-full",
+    "--trust-remote-code",
+    "--prefill-compute-share", "0.4",
+    # Admission guardrail only (the KV pool is pinned): 0.85 × 121.63 = 103.4 GiB.
+    "--gpu-memory-utilization", "0.85",
+    # 4 GiB/rank: enough for one 65536-token request (51.6 KB/token/rank).
+    "--kv-cache-memory-bytes", "4294967296",
+    # 2026-10-22 05:41: explicit B12X dies in the worker with
+    #   TypeError: DeepseekV32B12xAttention.__init__() got an unexpected
+    #   keyword argument 'index_group_builder'
+    # (the re-cut's indexer API is newer than r39's B12X attention class), so
+    # the first boot lets the fork pick its default backend.
+    # "--attention-backend", "B12X",
+    # MXFP4 GEMM: the FlashInfer kernel accepts capability 121 in is_supported()
+    # and then fails at runtime (mm_fp4, cute-dsl); the native b12x warmup
+    # crashes on this checkpoint's layer ranks. Marlin is the working path.
+    # 2026-10-22 06:15: forcing marlin kills the boot inside
+    #   prepare_fp8_layer_for_marlin: AttributeError: 'ReplicatedLinear' object
+    #   has no attribute 'output_size_per_partition'
+    # — the re-cut puts fp8_block on ReplicatedLinear modules (shared experts /
+    # indexer) and marlin's fp8 prep only handles the parallel-linear shapes.
+    # Marlin IS the right kernel for the MXFP4 linears on GB10 (weight-only A16
+    # dequant), but the flag is global, so the default per-scheme dispatch runs
+    # instead.
+    # "--linear-backend", "marlin",
+    # (2026-10-22 06:44, no flag at all: default dispatch sends the MXFP4
+    # linears to FlashInfer's mm_fp4, which rejects capability 121 at runtime
+    # — flashinfer.utils.BackendSupportedError: mm_fp4 does not support backend
+    # 'cute-dsl' with capability 121. The surgical fix is the env lever below:
+    # disable ONLY that kernel so MXFP4 falls through to Marlin while the
+    # fp8_block layers keep their own (working) backend.)
+    "--load-format", "instanttensor",
+    "--block-size", "256",
+    "--max-model-len", "65536",
+    "--max-num-seqs", "4",
+    "--max-num-batched-tokens", "4096",
+    "--enable-chunked-prefill",
+    "--async-scheduling",
+    "--enable-prefix-caching",
+    # No CuTe-DSL warmup / FlashInfer autotune: their scratch at large shapes
+    # does not fit this headroom.
+    "--kernel-config", """
+'{"enable_cutedsl_warmup":false,"enable_flashinfer_autotune":false}'""",
+    "--language-model-only",
+    "--enable-auto-tool-choice",
+    "--tool-call-parser", "glm47",
+    "--reasoning-parser", "glm45",
+    # No --speculative-config on the first boot: the MTP head is real
+    # (num_nextn_predict_layers=1) but draft KV + graph shapes need headroom
+    # this lane does not have yet. Add mtp k=3 after a clean boot.
+]
+
+[env]
+VLLM_ENGINE_READY_TIMEOUT_S = "5400"
+HF_HUB_OFFLINE = "1"
+NCCL_NCHANNELS = "16"
+VLLM_ENABLE_ROCE_ALLREDUCE = "1"
+# compile-OOM guard: 12 parallel nvcc jobs × ~3 GiB behind ~97 GiB of weights
+MAX_JOBS = "2"
+# MXFP4 linears: FlashInfer's cute-dsl mm_fp4 does not support GB10 (cap 121),
+# and forcing --linear-backend marlin globally trips on the fp8_block
+# ReplicatedLinear modules. Disabling just the FlashInfer MXFP4 kernel makes
+# the dispatcher fall through to Marlin for FP4 and leave FP8 alone.
+VLLM_DISABLED_KERNELS = "FlashInferMxFp4LinearKernel"