diff --git a/.github/workflows/benchmark-multinode-tmpl.yml b/.github/workflows/benchmark-multinode-tmpl.yml
index ac4347b3fe..de76e89d9e 100644
--- a/.github/workflows/benchmark-multinode-tmpl.yml
+++ b/.github/workflows/benchmark-multinode-tmpl.yml
@@ -283,7 +283,7 @@ jobs:
       - name: Prepare launcher Python
         env: *uv-setup-env
         run: |
-          launch_venv="$RUNNER_TEMP/infx-launch-venv"
+          launch_venv="$(mktemp -d "$RUNNER_TEMP/infx-launch-venv.XXXXXX")"
           uv venv --quiet --python 3.12 "$launch_venv"
           uv pip install --quiet --exclude-newer PT12H --python "$launch_venv/bin/python" \
             -r "$GITHUB_WORKSPACE/.result-tooling/inferencex-e2e/pyproject.toml"
diff --git a/inferencex-e2e/benchmarks/multi_node/srt-slurm-recipes/dsv41flash/vllm/gb300-fp4/agentx/disagg-variants.yaml b/inferencex-e2e/benchmarks/multi_node/srt-slurm-recipes/dsv41flash/vllm/gb300-fp4/agentx/disagg-variants.yaml
index fe8a0cbe8c..8969c6fb1c 100644
--- a/inferencex-e2e/benchmarks/multi_node/srt-slurm-recipes/dsv41flash/vllm/gb300-fp4/agentx/disagg-variants.yaml
+++ b/inferencex-e2e/benchmarks/multi_node/srt-slurm-recipes/dsv41flash/vllm/gb300-fp4/agentx/disagg-variants.yaml
@@ -217,3 +217,27 @@ override_8p1d_dep2_dep16_c4096:
         max-num-seqs: 72
         max-num-batched-tokens: 720
         compilation-config: '{"cudagraph_mode":"FULL_DECODE_ONLY","max_cudagraph_capture_size":432,"cudagraph_capture_sizes":[6,12,18,24,30,36,42,48,54,60,66,72,78,84,90,96,102,108,114,120,126,132,138,144,150,156,162,168,174,180,186,192,198,204,210,216,222,228,234,240,246,252,258,264,270,276,282,288,294,300,306,312,318,324,330,336,342,348,354,360,366,372,378,384,390,396,402,408,414,420,426,432]}'
+
+override_10p1d_dep2_dep16_c6656:
+  name: "dsv41flash-fp4-gb300-dynamo-vllm-agentx-disagg-10p1d-dep2-dep16-c6656"
+  roles:
+    prefill:
+      nodes: 5
+      workers: 10
+    decode:
+      args:
+        max-num-seqs: 132
+        max-num-batched-tokens: 1320
+        compilation-config: '{"cudagraph_mode":"FULL_DECODE_ONLY","max_cudagraph_capture_size":792,"cudagraph_capture_sizes":[6,12,18,24,30,36,42,48,54,60,66,72,78,84,90,96,102,108,114,120,126,132,138,144,150,156,162,168,174,180,186,192,198,204,210,216,222,228,234,240,246,252,258,264,270,276,282,288,294,300,306,312,318,324,330,336,342,348,354,360,366,372,378,384,390,396,402,408,414,420,426,432,438,444,450,456,462,468,474,480,486,492,498,504,510,516,522,528,534,540,546,552,558,564,570,576,582,588,594,600,606,612,618,624,630,636,642,648,654,660,666,672,678,684,690,696,702,708,714,720,726,732,738,744,750,756,762,768,774,780,786,792]}'
+
+override_8p1d_dep2_dep16_c5120:
+  name: "dsv41flash-fp4-gb300-dynamo-vllm-agentx-disagg-8p1d-dep2-dep16-c5120"
+  roles:
+    prefill:
+      nodes: 4
+      workers: 8
+    decode:
+      args:
+        max-num-seqs: 70
+        max-num-batched-tokens: 700
+        compilation-config: '{"cudagraph_mode":"FULL_DECODE_ONLY","max_cudagraph_capture_size":420,"cudagraph_capture_sizes":[6,12,18,24,30,36,42,48,54,60,66,72,78,84,90,96,102,108,114,120,126,132,138,144,150,156,162,168,174,180,186,192,198,204,210,216,222,228,234,240,246,252,258,264,270,276,282,288,294,300,306,312,318,324,330,336,342,348,354,360,366,372,378,384,390,396,402,408,414,420]}'
diff --git a/inferencex-e2e/configs/nvidia-master.yaml b/inferencex-e2e/configs/nvidia-master.yaml
index 1fc173c6a4..69dc0904bd 100644
--- a/inferencex-e2e/configs/nvidia-master.yaml
+++ b/inferencex-e2e/configs/nvidia-master.yaml
@@ -9187,6 +9187,36 @@ dsv41flash-fp4-gb300-dynamo-vllm-agentic-dspark-disagg:
           tp: 16
           ep: 16
           dp-attn: true
+      - spec-decoding: mtp
+        kv-offloading: dram
+        kv-offload-backend: { name: vllm-simple }
+        srt-recipe: disagg-variants.yaml:override_8p1d_dep2_dep16_c5120
+        conc-list: [5120]
+        prefill:
+          num-worker: 8
+          tp: 2
+          ep: 2
+          dp-attn: true
+        decode:
+          num-worker: 1
+          tp: 16
+          ep: 16
+          dp-attn: true
+      - spec-decoding: mtp
+        kv-offloading: dram
+        kv-offload-backend: { name: vllm-simple }
+        srt-recipe: disagg-variants.yaml:override_10p1d_dep2_dep16_c6656
+        conc-list: [6656]
+        prefill:
+          num-worker: 10
+          tp: 2
+          ep: 2
+          dp-attn: true
+        decode:
+          num-worker: 1
+          tp: 16
+          ep: 16
+          dp-attn: true
 
 # One serving GPU, stock ARM64 release, native AgentX client and proportional host cache.
 qwen3.8next-fp4-gb300-sglang-agentic-mtp:
diff --git a/inferencex-e2e/perf-changelog.yaml b/inferencex-e2e/perf-changelog.yaml
index 8ec368892e..fefd7900d2 100644
--- a/inferencex-e2e/perf-changelog.yaml
+++ b/inferencex-e2e/perf-changelog.yaml
@@ -10013,3 +10013,12 @@
     - "Add a HiCache host-DRAM KV offload arm at concurrency 2, 4 and 8 with 160 GB per rank, alongside the GPU-resident sweep; the few-GB GPU KV pool left by 67 GB of weights per H100 evicts agentic prefixes between turns."
     - "Keep the batch-8 cap on running requests and decode graphs from the GPU-resident sweep."
   pr-link: https://github.com/SemiAnalysisAI/InferenceX/pull/4181
+
+- config-keys:
+    - dsv41flash-fp4-gb300-dynamo-vllm-agentic-dspark-disagg
+  scenario-type:
+    - agentic-coding
+  description:
+    - "Append GB300 DeepSeek-V4.1-Flash Dynamo + vLLM AgentX c5120 (8P1D) and c6656 (10P1D) points using the agentx-harness 1.0.10 release already pinned on main."
+  pr-link: https://github.com/SemiAnalysisAI/InferenceX/pull/4126
+  append-only: true