diff --git a/models/deepseek-ai/DeepSeek-V4.1-Flash.yaml b/models/deepseek-ai/DeepSeek-V4.1-Flash.yaml
index 3f994440b..8465f5f88 100644
--- a/models/deepseek-ai/DeepSeek-V4.1-Flash.yaml
+++ b/models/deepseek-ai/DeepSeek-V4.1-Flash.yaml
@@ -167,6 +167,7 @@ strategy_overrides:
     tp:
       default: 4
       h100: 8
+      b200: 2
       b300: 2
     hardware_overrides:
       blackwell:
@@ -177,6 +178,28 @@ strategy_overrides:
           - "fp8"
           - "--max-num-seqs"
           - "128"
+      # TP2 on 180 GB B200 with the Engram tables in pinned host DRAM behind
+      # UVA still leaves ~145 GiB of resident weights per GPU, so the memory
+      # levers from the InferenceX B200 arm apply
+      # (SemiAnalysisAI/InferenceX#3216, AgentX c1-c128 green in run
+      # 35480787586): at the upstream 16384 batched tokens the
+      # sparse-attention indexer's [batched-tokens, 1M] fp8 logits buffer is
+      # 32 GiB and graph capture above 512 tokens pushed the KV budget
+      # negative, so batched tokens are capped at 4096 (8 GiB) and CUDA-graph
+      # capture stops at 512 tokens; larger decode batches run eagerly.
+      # FlashInfer's autotune batches max-num-seqs requests through the DSpark
+      # draft head and picked an invalid MXFP8 tactic below 16 sequences, so
+      # keep --max-num-seqs at 16 or above.
+      b200:
+        extra_args:
+          - "--engram-config"
+          - '{"cpu_offload":true}'
+          - "--max-num-batched-tokens"
+          - "4096"
+          - "--max-cudagraph-capture-size"
+          - "512"
+          - "--max-num-seqs"
+          - "256"
       b300:
         extra_args:
           - "--engram-config"
@@ -503,8 +526,15 @@ guide: |
   settings take precedence over the shared Blackwell defaults. For high
   interactivity, use `--tensor-parallel-size 4`.
 
-  These command settings were updated on 2026-09-20; they have not been rerun
-  on GPUs as part of this recipe update.
+  B200 (180 GB per GPU) also defaults to **TP2** with Engram CPU offload. Its
+  exact-GPU override caps `--max-num-batched-tokens` at 4096 and
+  `--max-cudagraph-capture-size` at 512 and sets `--max-num-seqs 256`, the
+  settings under which the InferenceX AgentX sweep completed concurrency 1
+  through 128 ([InferenceX #3216](https://github.com/SemiAnalysisAI/InferenceX/pull/3216),
+  run 35480787586). For high interactivity, use `--tensor-parallel-size 4`.
+
+  These command settings were updated on 2026-09-20; the B300 settings have not
+  been rerun on GPUs as part of this recipe update.
 
   ## KV cache offloading