recipes: qwen38-27b-nvfp4

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

@@ -0,0 +1,82 @@
+# Qwen3.8-27B (RedHatAI NVFP4 + MTP) — 1× DGX Spark / GB10 (sm_121), TP=1.
+#
+# NVFP4 compressed-tensors quant (22 GB) with a separate MTP draft in
+# `model_mtp.safetensors`. Dense 27B, GQA, hybrid DeltaNet+Attention. Text +
+# vision. The vLLM-only quant (lm_head FP8) — SGLang can't load it.
+#
+# Two nearly-identical NVFP4 builds are available:
+#   RedHatAI/Qwen3.8-27B-NVFP4  (this recipe)
+#   unsloth/Qwen3.8-27B-NVFP4   (qwen38-27b-nvfp4-unsloth recipe)
+# Speed/quality are close; benchmark both in the experiment.
+#
+# 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 the qwen3_5 arch + MTP.
+#
+# Model: RedHatAI/Qwen3.8-27B-NVFP4
+#   https://huggingface.co/RedHatAI/Qwen3.8-27B-NVFP4
+#
+# PREREQUISITES:
+#   Weights cached on every node (dgx1 ~/.cache/huggingface → NAS):
+#       huggingface-cli download RedHatAI/Qwen3.8-27B-NVFP4
+#
+# REFERENCE:
+#   https://forums.developer.nvidia.com/t/qwen3-8-27b-on-dual-sparks/380350
+#   https://forums.developer.nvidia.com/t/qwen3-8-27b-nvfp4-on-a-single-dgx-spark-up-to-1m-context-vllm-mtp-measurements/380244
+#   https://forums.developer.nvidia.com/t/qwen3-8-27b-mixedint4-autoround-optimized-for-a-single-dgx-spark/380248
+
+engine = "vllm"
+name = "Qwen3.8-27B (NVFP4, RedHatAI)"
+docker_image = "ghcr.io/timothystewart6/vllm-gb10:v0.27.1-gb10.2"
+model = "RedHatAI/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", "8192",
+    "--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",
+    # MTP speculative decoding (in-checkpoint draft, model_mtp.safetensors)
+    "--speculative-config", """
+'{"method":"mtp","num_speculative_tokens":5}'""",
+    # 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",
+]
+
+[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"