recipes: qwen38-27b-nvfp4-unsloth-dspark

recipes/qwen38-27b-nvfp4-unsloth-dspark/recipe.toml

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+# Qwen3.8-27B (unsloth NVFP4 + DSpark) — 1× DGX Spark / GB10 (sm_121), TP=1.
+#
+# NVFP4 compressed-tensors quant (22 GB) with a dedicated DSpark draft model
+# (RadixArk, 2.6 GB, block_size 7) for speculative decoding. Dense 27B, GQA,
+# hybrid DeltaNet+Attention. Text + vision. Unsloth Dynamic V3.0 (preview)
+# quant — SOTA quality for NVFP4. vLLM-only (lm_head FP8).
+#
+# DSpark vs the in-checkpoint MTP head (qwen38-27b-nvfp4-unsloth recipe): the
+# draft is 3× cheaper per guess and edits/rewrites much faster, at the cost of
+# a 2.6 GB draft + a local arch-patched copy. Benchmark both.
+#
+# Image: ghcr.io/timothystewart6/vllm-gb10:v0.27.1-gb10.2
+#   vLLM 0.27.1, torch 2.13+cuda130, FlashInfer built from source,
+#   instanttensor. Stock vLLM — supports qwen3_5 arch + method "dspark".
+#
+# Model: unsloth/Qwen3.8-27B-NVFP4
+#   https://huggingface.co/unsloth/Qwen3.8-27B-NVFP4
+#
+# PREREQUISITES:
+#   Weights cached on every node (dgx1 ~/.cache/huggingface → NAS):
+#       huggingface-cli download unsloth/Qwen3.8-27B-NVFP4
+#       hfrs download RadixArk/Qwen3.8-27B-DSpark  (then cp -aL + patch arch → /home/kilork/dspark-draft)
+#
+# REFERENCE:
+#   https://blog.kubesimplify.com/qwen3-8-27b-on-dgx-spark  (DSpark section)
+
+engine = "vllm"
+name = "Qwen3.8-27B (NVFP4 unsloth + DSpark)"
+docker_image = "ghcr.io/timothystewart6/vllm-gb10:v0.27.1-gb10.2"
+model = "unsloth/Qwen3.8-27B-NVFP4"
+parent_model = "Qwen/Qwen3.8-27B"
+required_nodes = 1
+tensor_parallel_size = 1
+pipeline_parallel_size = 1
+distributed_backend = "mp"
+shm_size = "32gb"
+
+entrypoint = ["vllm", "serve"]
+
+args = [
+    # KV cache & memory
+    "--kv-cache-dtype", "fp8",
+    "--max-model-len", "262144",
+    "--max-num-seqs", "6",
+    "--max-num-batched-tokens", "16384",
+    "--gpu-memory-utilization", "0.75",
+    "--served-model-name", "qwen3.8-27b",
+    # Engine backends (dense GQA — FlashInfer; NVFP4 route via compressed-tensors)
+    "--attention-backend", "flashinfer",
+    # Compilation / perf
+    "--optimization-level", "3",
+    "--performance-mode", "throughput",
+    # Chunked prefill + prefix caching
+    "--enable-chunked-prefill",
+    "--enable-prefix-caching",
+    "--enable-flashinfer-autotune",
+    # DSpark speculative decoding — dedicated draft model (arch-patched local
+    # copy of RadixArk/Qwen3.8-27B-DSpark, re-labelled `Qwen3DSparkModel` so
+    # vLLM routes it to qwen3_dspark not the DeepSeek-V4 path). block_size 7.
+    # batched-tokens raised to 16384 to fit the draft token slots (warn:
+    # max_num_scheduled_tokens=8156 at 8192).
+    "--speculative-config", """
+'{"method":"dspark","model":"/dspark-draft","num_speculative_tokens":7}'""",
+    # Tokenizer / reasoning (Qwen3 family)
+    "--tool-call-parser", "qwen3_xml",
+    "--reasoning-parser", "qwen3",
+    "--enable-auto-tool-choice",
+    "--generation-config", "auto",
+    "--default-chat-template-kwargs.preserve_thinking=true",
+    # Proven generation defaults (thinking mode; Qwen3.8 model-card best
+    # practices)
+    "--override-generation-config", """
+'{"temperature":1.0,"top_p":0.95,"top_k":20,"min_p":0.0,"presence_penalty":0.0,"repetition_penalty":1.0}'""",
+    "--trust-remote-code",
+]
+
+# DSpark draft model — arch-patched local copy of RadixArk/Qwen3.8-27B-DSpark.
+[[extra_mounts]]
+host = "/home/kilork/dspark-draft"
+container = "/dspark-draft"
+
+
+[env]
+HF_HUB_OFFLINE = "1"
+TORCH_CUDA_ARCH_LIST = "12.1a"
+CUTE_DSL_ARCH = "sm_121a"
+OMP_NUM_THREADS = "4"
+PYTORCH_CUDA_ALLOC_CONF = "expandable_segments:True"
+CUDA_VISIBLE_DEVICES = "0"
+CUDA_DEVICE_ORDER = "PCI_BUS_ID"
+CUDA_CACHE_MAXSIZE = "4294967296"