diff --git a/inferencex-e2e/benchmarks/single_node/srt-slurm-recipes/dsr1/sglang/b200-fp4-mtp/8k1k.yaml b/inferencex-e2e/benchmarks/single_node/srt-slurm-recipes/dsr1/sglang/b200-fp4-mtp/8k1k.yaml
index 88ae02628c..3d8245e990 100644
--- a/inferencex-e2e/benchmarks/single_node/srt-slurm-recipes/dsr1/sglang/b200-fp4-mtp/8k1k.yaml
+++ b/inferencex-e2e/benchmarks/single_node/srt-slurm-recipes/dsr1/sglang/b200-fp4-mtp/8k1k.yaml
@@ -3,7 +3,7 @@ base:
   name: dsr1-fp4-b200-sglang-mtp-8k1k
   model:
     path: hf:nvidia/DeepSeek-R1-0528-FP4-V2
-    container: lmsysorg/sglang:v0.5.16-cu130
+    container: lmsysorg/sglang:v0.5.20-cu130@sha256:06e4f2ed21afde4ff513cda65070124e727ba23ccaeff7712b8c40e1097d611f
     precision: fp4
   resources:
     gpu_type: b200
@@ -25,7 +25,7 @@ base:
         trust-remote-code: true
         tensor-parallel-size: 4
         data-parallel-size: 1
-        cuda-graph-max-bs: 256
+        cuda-graph-max-bs-decode: 256
         max-running-requests: 256
         mem-fraction-static: 0.85
         kv-cache-dtype: fp8_e4m3
@@ -34,7 +34,7 @@ base:
         quantization: modelopt_fp4
         enable-flashinfer-allreduce-fusion: true
         scheduler-recv-interval: 10
-        disable-piecewise-cuda-graph: true
+        cuda-graph-backend-prefill: disabled
         attention-backend: trtllm_mla
         moe-runner-backend: flashinfer_trtllm
         stream-interval: 10
diff --git a/inferencex-e2e/configs/nvidia-master.yaml b/inferencex-e2e/configs/nvidia-master.yaml
index 63dcf8fff8..7722745c3d 100644
--- a/inferencex-e2e/configs/nvidia-master.yaml
+++ b/inferencex-e2e/configs/nvidia-master.yaml
@@ -893,7 +893,7 @@ dsr1-fp4-b200-sglang:
     #   - { tp: 8, ep: 8, offloading: none, conc-list: [1, 2, 4, 8, 12, 16, 32, 64, 128, 256, 512] }
 
 dsr1-fp4-b200-sglang-mtp:
-  image: lmsysorg/sglang:v0.5.16-cu130
+  image: lmsysorg/sglang:v0.5.20-cu130@sha256:06e4f2ed21afde4ff513cda65070124e727ba23ccaeff7712b8c40e1097d611f
   model: nvidia/DeepSeek-R1-0528-FP4-V2
   model-prefix: dsr1
   runner: cluster:b200-nscale
diff --git a/inferencex-e2e/perf-changelog.yaml b/inferencex-e2e/perf-changelog.yaml
index 9b9c48a0ef..9bbc7a7c80 100644
--- a/inferencex-e2e/perf-changelog.yaml
+++ b/inferencex-e2e/perf-changelog.yaml
@@ -9168,3 +9168,9 @@
     - "Relevant ATOM changes in the range: V4 decode reuses the sparse prefill ASM (ROCm/ATOM#2271), greedy sampler picks via aiter.topk_select (ROCm/ATOM#2244), and FP8 block scales declared scale_fmt ue8m0 are now stored as E8M0 on gfx950 by default (ROCm/ATOM#2419; previously FP32 unless ATOM_FP8_BLOCKSCALE_USE_E8M0_SCALE=1). The upstream DeepSeek-V4 recipes are unchanged across the range, and every recipe flag and choice (all2all-backend rccl, dp-load-balance least_tokens, moe-backend standard) remains valid."
     - "No data-type or precision change to the DeepSeek-V4-Pro-0813 DSpark draft: no online quantization is configured, so it keeps its checkpoint precision; the E8M0 scale storage represents the checkpoint's power-of-two block scales exactly. kv-cache-dtype and index-cache-dtype touch cache storage only."
   pr-link: https://github.com/SemiAnalysisAI/InferenceX/pull/3605
+
+- config-keys:
+    - dsr1-fp4-b200-sglang-mtp
+  description:
+    - "Update SGLang from v0.5.16-cu130 to v0.5.20-cu130 and rename two CUDA graph flags removed upstream."
+  pr-link: https://github.com/SemiAnalysisAI/InferenceX/pull/3634