diff --git a/models/deepseek-ai/DeepSeek-V4.1-Flash.yaml b/models/deepseek-ai/DeepSeek-V4.1-Flash.yaml
index 5b059cb8..32e0648a 100644
--- a/models/deepseek-ai/DeepSeek-V4.1-Flash.yaml
+++ b/models/deepseek-ai/DeepSeek-V4.1-Flash.yaml
@@ -5,7 +5,7 @@ meta:
   provider: "DeepSeek"
   description: "DeepSeek V4.1 Flash vision-language MoE (552B backbone; 8B active per prompt token, 16B per output token) combining sliding-window plus compressed sparse attention with a two-level indexer, engram n-gram memory, hyper-connections, and a DSpark multi-token draft head."
   date_added: 2026-09-09
-  date_updated: 2026-09-12
+  date_updated: 2026-09-13
   difficulty: advanced
   tasks:
     - text
@@ -20,6 +20,7 @@ meta:
     gb200: verified
     gb300: verified
     mi350x: verified
+    mi355x: verified
 
 model:
   model_id: "deepseek-ai/DeepSeek-V4.1-Flash"
@@ -27,7 +28,10 @@ model:
   default_frontend: rust
   docker_image:
     nvidia: "vllm/vllm-openai:deepseekv41-flash-0909"
-    amd: "vllm/vllm-openai-rocm:deepseekv41-flash-0909"
+    # ROCm nightly rather than the 0909 tag: 0909 predates
+    # vllm-project/vllm#56503, which moves the mHC delayed pre block off the
+    # eager Torch reference and onto AITER.
+    amd: "vllm/vllm-openai-rocm:nightly-eed1f3d0c6043bd494424a22443ee198dd56f657"
   architecture: moe
   parameter_count: "552B"
   active_parameters: "8-16B"
@@ -39,7 +43,7 @@ model:
     VLLM_ENGINE_READY_TIMEOUT_S: "3600"
   install:
     docker:
-      note: "Serve from the dedicated vllm/vllm-openai:deepseekv41-flash-0909 image — no pip wheel carries the DeepSeek-V4.1 architecture."
+      note: "Serve from the pinned image for your GPU vendor — no pip wheel carries the DeepSeek-V4.1 architecture. NVIDIA pins the 0909 release tag; AMD pins a ROCm nightly (see Prerequisites)."
     pip: false
 
 dependencies: []
@@ -111,11 +115,18 @@ hardware_overrides:
     extra_args:
       - "--gpu-memory-utilization"
       - "0.9"
+      # Plain "aiter" opens vLLM's full MoE priority list, whose head is the
+      # Composable Kernel backend, giving the a8w4 experts. Naming
+      # aiter_triton_mxfp4_bf16 instead pins the Triton W4A16 _moe_gemm_a16w4.
       - "--moe-backend"
-      - "aiter_triton_mxfp4_bf16"
+      - "aiter"
     extra_env:
       VLLM_ROCM_USE_AITER: "1"
       VLLM_ROCM_USE_AITER_MOE: "1"
+      # aiter.ops.triton warns on every call that Gluon is unavailable and it is
+      # falling back to Triton. Gluon is gfx1250-only, so on gfx950 that is a
+      # fixed property, and it was 98% of the lines in a gsm8k server log.
+      AITER_TRITON_LOG_LEVEL: "ERROR"
       # DeepseekV41ForCausalLM does not support torch.compile. The ROCm sparse
       # SWA backend only reports UNIFORM_BATCH, so default FULL_AND_PIECEWISE
       # cannot start unless breakable CUDA graphs are on.
@@ -123,8 +134,17 @@ hardware_overrides:
 
 strategy_overrides:
   single_node_tp:
-    # Verified at TP4 (one GB200 NVL4 tray; 4 of 8 GPUs on an MI350X node).
+    # Verified at TP4 (one GB200 NVL4 tray; 4 of 8 GPUs on an MI350X or
+    # MI355X node).
     tp: 4
+    hardware_overrides:
+      mi355x:
+        # vllm serve defaults max_num_seqs to 1024 on >=160 GiB GPUs, but the
+        # MI355X run this recipe is verified against served 128. Pinned so the
+        # published command reproduces that run, and only for this pairing.
+        extra_args:
+          - "--max-num-seqs"
+          - "128"
   pd_cluster:
     # Verified 1P1D on GB200 NVL4: one tray per role, TP4 each, NIXL transfer.
     env:
@@ -303,12 +323,18 @@ guide: |
 
   ## Prerequisites
 
-  - The `vllm/vllm-openai:deepseekv41-flash-0909` image (vLLM 0.30.0+). No pip wheel serves
-    this architecture, so the Install block only offers Docker.
+  - An image (vLLM 0.30.0+); no pip wheel serves this architecture, so the Install block
+    only offers Docker. On NVIDIA that is `vllm/vllm-openai:deepseekv41-flash-0909`. On AMD
+    it is `vllm/vllm-openai-rocm:nightly-eed1f3d0c6043bd494424a22443ee198dd56f657` — a ROCm
+    nightly rather than the 0909 tag, because 0909 predates
+    [vllm-project/vllm#56503](https://github.com/vllm-project/vllm/pull/56503), which moves
+    the mHC delayed pre block off the eager Torch reference and onto AITER.
   - The Rust OpenAI frontend is selected by default in the command builder. Switch
     to Python if you encounter unsupported features or compatibility issues.
   - Expect a long first load: `VLLM_ENGINE_READY_TIMEOUT_S=3600` is set for that reason.
   - On AMD, the generated command sets `VLLM_USE_BREAKABLE_CUDAGRAPH=1`. DeepSeek-V4.1-Flash does not support `torch.compile`, and the ROCm sparse SWA backend only supports uniform-batch CUDA graphs. Without breakable CUDA graphs, default `FULL_AND_PIECEWISE` dies at capture.
+  - On AMD, the generated command passes `--moe-backend aiter` rather than naming a kernel. Naming `aiter_triton_mxfp4_bf16` pins the Triton W4A16 `_moe_gemm_a16w4` kernel; the plain name lets vLLM select the Composable Kernel a8w4 experts, which measured 4–9% faster per decode step at 131k context on MI355X, with larger gains at higher concurrency. It also sets `AITER_TRITON_LOG_LEVEL=ERROR` to drop AITER's per-call "Gluon unavailable" warning, which is constant on gfx950 and dominated the server log.
+  - On MI355X, **Tensor Parallel** additionally pins `--max-num-seqs 128`, the value the verified run served. Left unset, `vllm serve` defaults to 1024 on GPUs with at least 160 GiB. Raise it if your traffic needs more scheduler capacity than the verified configuration.
   - On AMD, ticking **Speculative decoding** also sets `enable_adaptive_verification:false`. vLLM currently refuses the true flag: `DeepseekV41IndexerBackend.supports_device_cpu_query_lens_mismatch()` is False, and `DeepseekV41ROCMAiterSparseSWABackend` reports `UNIFORM_BATCH` rather than `ALWAYS`. DSpark still drafts 5 tokens per round.
 
   ## Verifying