diff --git a/benchmarks/single_node/agentic/dsv4_fp4_mi355x_sglang_mtp.sh b/benchmarks/single_node/agentic/dsv4_fp4_mi355x_sglang_mtp.sh
index 61add3eafa..c0f957a7c1 100644
--- a/benchmarks/single_node/agentic/dsv4_fp4_mi355x_sglang_mtp.sh
+++ b/benchmarks/single_node/agentic/dsv4_fp4_mi355x_sglang_mtp.sh
@@ -73,6 +73,12 @@ export SGLANG_DSV4_REASONING_EFFORT=high
 export SGLANG_USE_ROCM700A=0
 export SGLANG_HACK_FLASHMLA_BACKEND=unified_kv_triton
 export AITER_BF16_FP8_MOE_BOUND=0
+# DSv4 kernel fusions carried by the sgl-dev image: aiter batched GEMM for the
+# absorbed MLA projections, native b-preshuffle scale handling, and a fused
+# compress+norm+rope epilogue. All three default off in environ.py.
+export SGLANG_OPT_USE_AITER_BATCHED_GEMM=1
+export SGLANG_OPT_NATIVE_BPRESHUFFLE_SCALE=1
+export SGLANG_OPT_FUSE_COMPRESS_NORM_ROPE=1
 
 # Unified radix tree: per-component (full-attn / SWA) cache management for
 # hybrid-attention models, plus proactive release of out-of-window SWA KV
@@ -130,8 +136,10 @@ SGLANG_BACKEND_PORT="$PORT"
 # cap; same value the multi-node DeepSeek-V4-Pro-AgentX no_dp profile uses.
 CHUNKED_PREFILL_SIZE=8192
 # MTP adds a draft KV pool and extra graph captures on top of the spec-none
-# footprint, which ran at 0.90.
-MEM_FRACTION_STATIC=0.85
+# footprint, which ran at 0.90. 0.89 recovers most of that: the DSv4 compressor
+# state pools are sized from the full-attention pool and allocated after it,
+# outside this budget, so the remainder has to stay large enough to cover them.
+MEM_FRACTION_STATIC=0.89
 PARALLEL_ARGS=(--tensor-parallel-size "$TP")
 if [ "$DP_ATTENTION" = "true" ]; then
     USE_SGLANG_ROUTER=true
@@ -213,7 +221,7 @@ SGLANG_CMD=(
     --page-size 256
     --swa-full-tokens-ratio 0.10
     --kv-cache-dtype fp8_e4m3
-    --disable-shared-experts-fusion
+    --enforce-shared-experts-fusion
     --tool-call-parser deepseekv4
     --reasoning-parser deepseek-v4
     --chunked-prefill-size "$CHUNKED_PREFILL_SIZE"
diff --git a/configs/amd-master.yaml b/configs/amd-master.yaml
index 67a0605398..563d3ffa1c 100644
--- a/configs/amd-master.yaml
+++ b/configs/amd-master.yaml
@@ -1722,12 +1722,17 @@ glm5.2-fp4-mi355x-atom-agentic-mtp:
 # SGLang AgentX coverage removed in de493d859 (PR #2531, which deleted the
 # spec-none dsv4-fp4-mi355x-sglang-agentic-hicache key and its script) so the
 # aggregated SGLang path is comparable with dsv4-fp4-mi355x-vllm-agentic-mtp
-# and dsv4-fp4-mi355x-sglang-disagg-agentic-hicache-mtp. The image matches the
-# already-green disagg AgentX entry. Pure TP8 only: DSA + dp-attention hangs a
-# collective under long-context prefill, so no DEP arm ships until that path is
-# validated. conc 16 appears on both arms to isolate the host KV tier's gain.
+# and dsv4-fp4-mi355x-sglang-disagg-agentic-hicache-mtp. The image is the
+# sgl-dev v0.5.18 build, which carries the DSv4 kernel fusions this key enables
+# via SGLANG_OPT_*. Tensor-parallel only: DSA + dp-attention hangs a collective
+# under long-context prefill, so no DEP arm ships until that path is validated.
+# TP4 owns the low-concurrency end, where halving the GPUs per replica raises
+# throughput per GPU, and TP8 picks up from conc 16; conc 16 appears on both TP8
+# arms to isolate the host KV tier's gain. TP4 doubles per-rank weights, leaving
+# far less room for KV, which is why it stops at conc 10 and carries no host
+# tier.
 dsv4-fp4-mi355x-sglang-agentic-mtp:
-  image: lmsysorg/sglang-rocm:v0.5.17-rocm720-mi35x-20260813
+  image: lmsysorg/sglang-rocm:v0.5.17-rocm720-mi35x-20260822
   model: deepseek-ai/DeepSeek-V4-Pro
   model-prefix: dsv4
   runner: cluster:mi355x-amds
@@ -1738,5 +1743,6 @@ dsv4-fp4-mi355x-sglang-agentic-mtp:
     agentic-coding:
     - dram-utilization: 0.80
       search-space:
-      - { tp: 8, ep: 1, dp-attn: false, kv-offloading: none, conc-list: [1, 2, 4, 8, 16], spec-decoding: mtp }
+      - { tp: 4, ep: 1, dp-attn: false, kv-offloading: none, conc-list: [1, 2, 4, 8, 10], spec-decoding: mtp }
+      - { tp: 8, ep: 1, dp-attn: false, kv-offloading: none, conc-list: [16], spec-decoding: mtp }
       - { tp: 8, ep: 1, dp-attn: false, kv-offloading: dram, kv-offload-backend: { name: hicache }, conc-list: [16, 32, 48], spec-decoding: mtp }
diff --git a/perf-changelog.yaml b/perf-changelog.yaml
index 98eef2c543..a226799e1c 100644
--- a/perf-changelog.yaml
+++ b/perf-changelog.yaml
@@ -6378,3 +6378,15 @@
     - "Serve the TP8 arm with FULL_AND_PIECEWISE cudagraphs, capturing the mixed prefill/decode batches as well as the uniform decode batches. The DEP8 arm is unchanged."
     - "Replace the TP8 concurrency list [1, 4, 8, 16, 24] with [1, 4, 8, 14], dropping the published concurrency 16 and 24 points and adding concurrency 14."
   pr-link: https://github.com/SemiAnalysisAI/InferenceX/pull/2707
+
+- config-keys:
+    - dsv4-fp4-mi355x-sglang-agentic-mtp
+  scenario-type:
+    - agentic-coding
+  description:
+    - "Update image from lmsysorg/sglang-rocm:v0.5.17-rocm720-mi35x-20260813 to rocm/sgl-dev:v0.5.18-rocm720-mi35x-20260822."
+    - "Enable the DSv4 kernel fusions the new image carries, all of which default off: SGLANG_OPT_USE_AITER_BATCHED_GEMM=1 (aiter batched GEMM for the absorbed MLA projections), SGLANG_OPT_NATIVE_BPRESHUFFLE_SCALE=1, SGLANG_OPT_FUSE_COMPRESS_NORM_ROPE=1."
+    - "Raise mem-fraction-static from 0.85 to 0.89, enlarging the full-attention KV pool. The DSv4 compressor state pools are sized from that pool and allocated after it, outside this budget, so the remainder still has to cover them."
+    - "Switch --disable-shared-experts-fusion to --enforce-shared-experts-fusion, which fuses the single shared expert into the routed list. The tuned MoE tables in this image cover the resulting (inter_dim 384, expert 385, topk 7) shape at the token sizes this workload hits."
+    - "Split the parallelism by concurrency: add a TP4 arm at [1, 2, 4, 8, 10] with no host KV tier, where halving the GPUs per replica raises throughput per GPU, and reduce the TP8 no-offload arm from [1, 2, 4, 8, 16] to [16]. This drops the published TP8 concurrency 1, 2, 4 and 8 points and adds TP4 concurrency 1, 2, 4, 8 and 10."
+  pr-link: https://github.com/SemiAnalysisAI/InferenceX/pull/2710