diff --git a/recipes/qwen3-8-flash-next-nvfp4-dgx-spark-gb10-sglang-nextn-mtp/recipe.yaml b/recipes/qwen3-8-flash-next-nvfp4-dgx-spark-gb10-sglang-nextn-mtp/recipe.yaml
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-slug: qwen3-8-flash-next-nvfp4-dgx-spark-gb10-sglang-nextn-mtp
-title: 'Qwen3.8-Flash-Next NVFP4 DGX Spark GB10 SGLang NEXTN MTP'
-engine:
-  name: sglang
-  version: 'image tag qwen38-flash:v1.5 (FROM lmsysorg/sglang:latest)'
-  source_type: docker_image
-  git_url: 'https://github.com/bemlerlabs/qwen3.8-flash-next-dgx-spark-sglang'
-  pinned_commit: 06fd72a673284696e55b52b3adb58aa3cc6daf35
-  image_digest: 'qwen38-flash:v1.5'
-  install_note: 'docker build from the repo Dockerfile @ 06fd72a6: FROM lmsysorg/sglang:latest (UNPINNED upstream base - rebuilds may drift; env TORCH_CUDA_ARCH_LIST=12.0;12.1, ENTRYPOINT python3 -m sglang.launch_server), tagged qwen38-flash:v1.5 locally. launch.sh runs it with --gpus all --memory 110g --shm-size 16g --network host and the NVMe/JIT-cache mounts. No digest pin on the base image - author ships tag-level reproducibility only (honest gap vs the Felliks/YSLAB pin discipline).'
-summary: 'Production single-node DGX Spark (Grace Blackwell GB10, SM121, 128GB unified memory) recipe for Qwen3.8-Flash-Next on SGLang: ModelOpt NVFP4 quantization with zero-copy NVMe mmap of the 47.7 GiB ple_table.bin via --ple-offload-embedding (eliminates 51 GiB of unified-memory footprint), custom Triton FP4 prefill kernels + trtllm_mha decode kernels on SM121, NEXTN MTP (3 verification steps / 4 draft tokens) lifting output to 110-152 tok/s, GDN+QSA hybrid (131,072-token served window, 262k native capacity), 96-slot mamba recurrence buffers, sharp froggeric v22.1 Jinja chat template (-18% response length), persistent Triton/Inductor SM121 JIT caches on NVMe, 8-worker parallel NVMe pre-warm (206 shards in 17s) + 16-core Grace OMP. Author-measured vs same-box 27B dense baseline: 110.4-152.8 tok/s decode w/ MTP (baseline 12.1 base / 21.5 MTP), single-stream CoT 25.1-28.8 tok/s (2.62x speculative gain), TTFT ~347ms radix hit / ~465ms cold, 113 GiB / 121 GiB RAM used (~8 GiB headroom), 103.5 GiB'
-model:
-  name: Qwen3.8-Flash-Next-NVFP4
-  family: qwen3-8-flash-next
-  hf_repo: RadixArk/Qwen3.8-Flash-Next-NVFP4
-  hf_revision: 7b719225242aacd3dbd3f9407468c2ee9a9d2594
-  quant: nvfp4
-hardware:
-  -
-    vendor: nvidia
-    card: 'DGX Spark (GB10, unified memory)'
-    vram_gb: 128
-    device_count: 1
-tasks:
-  - chat
-  - code
-tags:
-  - bemlerlabs
-  - sglang
-  - dgx-spark
-  - gb10
-  - sm121
-  - nvme-ple
-  - mtp-speculative
-  - triton-prefill
-  - trtllm-mha
-config:
-  launch:
-    - python3
-    - '-m'
-    - sglang.launch_server
-    - '--model-path'
-    - RadixArk/Qwen3.8-Flash-Next-NVFP4
-    - '--revision'
-    - 7b719225242aacd3dbd3f9407468c2ee9a9d2594
-    - '--tp-size'
-    - '1'
-    - '--served-model-name'
-    - qwen3.8-flash-next
-    - '--quantization'
-    - modelopt_fp4
-    - '--prefill-attention-backend'
-    - triton
-    - '--decode-attention-backend'
-    - trtllm_mha
-    - '--ple-offload-embedding'
-    - '--mamba-radix-cache-strategy'
-    - extra_buffer
-    - '--max-mamba-cache-size'
-    - '96'
-    - '--mem-fraction-static'
-    - '0.90'
-    - '--context-length'
-    - '131072'
-    - '--chunked-prefill-size'
-    - '4096'
-    - '--enable-mixed-chunk'
-    - '--schedule-conservativeness'
-    - '0.8'
-    - '--max-running-requests'
-    - '4'
-    - '--allow-auto-truncate'
-    - '--speculative-algorithm'
-    - NEXTN
-    - '--speculative-num-steps'
-    - '3'
-    - '--speculative-eagle-topk'
-    - '1'
-    - '--speculative-num-draft-tokens'
-    - '4'
-    - '--speculative-draft-model-quantization'
-    - unquant
-    - '--reasoning-parser'
-    - qwen3
-    - '--tool-call-parser'
-    - qwen3_coder
-    - '--chat-template'
-    - /out/chat-template-flashnext.jinja
-    - '--api-key'
-    - local
-    - '--host'
-    - 0.0.0.0
-    - '--port'
-    - '8000'
-  runtime:
-    env: 'SGLANG_QWEN4_PLE_MMAP_DIR=/ple (47.7 GiB ple_table.bin, zero-copy mmap) | TRITON_CACHE_DIR=/root/.cache/sglang/triton | TORCHINDUCTOR_CACHE_DIR=/root/.cache/sglang/inductor | OMP_NUM_THREADS=16 | MKL_NUM_THREADS=16'
-    notes: "Serve profile = launch.sh @ 06fd72a6 verbatim (docker run --rm --name qwen38-flash --gpus all --memory 110g --memory-swap 110g --shm-size 16g --network host --ipc=host, mounts: HF cache, /out config dir w/ chat-template-flashnext.jinja, /ple PLE dir, sglang cache). Model downloaded at pinned revision (hf snapshot under ~/.cache/huggingface); 8-worker parallel pre-warm cats 206 safetensors shards + 4-worker pre-warm of the PLE table into page cache (<25s) before docker exec. Background health monitor polls :8000/health every 10s x270. Rollback note per README: the 0.90 mem-fraction + full-PLE state is the HEAD 'perfectly working state' (commit subject); systemd unit systemd/qwen38-flash.service provided for 24/7 with crash recovery. Sampling: OpenAI-compatible :8000/v1, api_key 'local' default. Chat template: repo file chat-template-flashnext.jinja (sharp froggeric v22.1, mounted READ-ONLY via /out)."
-performance:
-  claimed_by: submitter
-  metrics:
-    tok_s: 110.4
-    context_len: 131072
-    notes: 'Author-measured (README telemetry table @ 06fd72a6 + Qwen3.8_FlashNext_DGX_Spark_Benchmark_Report.pdf in-repo, single DGX Spark GB10 @ 273 GB/s): decode 110.4-152.8 tok/s with NEXTN MTP; single-stream CoT 25.1-28.8 tok/s (2.62x speculative gain); TTFT ~347ms radix hit / ~465ms cold; total RAM 113 GiB / 121 GiB (~8 GiB headroom); SGLang VRAM allocation 103.5 GiB static 0.90; PLE table 47.7 GiB zero-copy mmap; swap buffer 1.2 GiB / 99 GiB free; cold boot/restart ~8.5 min (51.8s prefetch, zero swap'
-    points:
-      -
-        context_len: 131072
-        concurrency: 1
-        decode_tok_s: 110.4
-        ttft_ms: 465
-        notes: 'README telemetry @ 06fd72a6: MTP decode band 110.4-152.8 tok/s; TTFT ~347ms radix hit / ~465ms cold; NEXTN 3 steps / 4 draft'
-      -
-        context_len: 131072
-        concurrency: 1
-        decode_tok_s: 152.8
-        notes: 'README telemetry: upper end of the measured 110.4-152.8 tok/s MTP band'
-artifacts:
-  -
-    kind: model_weights
-    pointer_type: hf_model
-    pointer: 'https://huggingface.co/RadixArk/Qwen3.8-Flash-Next-NVFP4'
-    pin: "revision 7b719225242aacd3dbd3f9407468c2ee9a9d2594 (MODEL_REVISION default in launch.sh) - 126GB NVFP4 checkpoint shards + 51GB ple_table.bin mmap'd from NVMe"
-  -
-    kind: engine_image
-    pointer_type: docker_digest
-    pointer: 'https://hub.docker.com/r/lmsysorg/sglang'
-    pin: 'FROM lmsysorg/sglang:latest built per repo Dockerfile @ 06fd72a6 -> local tag qwen38-flash:v1.5 (base tag UNPINNED upstream - noted in install_note); TORCH_CUDA_ARCH_LIST=12.0;12.1'
-  -
-    kind: reference
-    pointer_type: git_commit
-    pointer: 'https://github.com/bemlerlabs/qwen3.8-flash-next-dgx-spark-sglang'
-    pin: '06fd72a673284696e55b52b3adb58aa3cc6daf35 - launch.sh (full argv), Dockerfile, chat-template-flashnext.jinja, systemd/qwen38-flash.service, benchmark.py + PDF benchmark report'
-provenance:
-  source_urls:
-    - 'https://github.com/bemlerlabs/qwen3.8-flash-next-dgx-spark-sglang'
-    - 'https://github.com/bemlerlabs/qwen3.8-flash-next-dgx-spark-sglang/blob/main/launch.sh'
-  credit:
-    -
-      name: 'Michael Bemler (Bemler Labs)'
-      url: 'https://github.com/bemlerlabs/qwen3.8-flash-next-dgx-spark-sglang'
-  notes: 'Ingested from GitHub repo bemlerlabs/qwen3.8-flash-next-dgx-spark-sglang @ 06fd72a673284696e55b52b3adb58aa3cc6daf35 (wave 3, kanban t_21a3a083). Recipe architected by Michael Bemler per README. First DGX Spark + first SGLang-serving recipe on the site (new hardware family dgx-spark seeded via 0051). Apache-2.0.'