diff --git a/benchmarks/single_node/agentic/dsv4_fp4_mi355x_vllm.sh b/benchmarks/single_node/agentic/dsv4_fp4_mi355x_vllm.sh
new file mode 100644
index 0000000000..8d8ba1f791
--- /dev/null
+++ b/benchmarks/single_node/agentic/dsv4_fp4_mi355x_vllm.sh
@@ -0,0 +1,441 @@
+#!/usr/bin/env bash
+set -euo pipefail
+set -x
+
+# Agentic trace replay benchmark for DeepSeek-V4-Pro FP4 on MI355X using vLLM.
+# Mirrors the fixed-seq-len parallelism options (pure TP and DEP) so the
+# agentic sweep can probe both interactivity and throughput regimes:
+#   pure TP (DP_ATTENTION=false, EP_SIZE=1):  attention TP-sharded across
+#       all $TP GPUs in a single engine. Lower TPOT, lower batch.
+#   TP+EP   (DP_ATTENTION=false, EP_SIZE>1):  attention TP-sharded, MoE
+#       experts EP-sharded within the TP group.
+#   DEP     (DP_ATTENTION=true, EP_SIZE>1):   per-DP-rank attention with
+#       experts EP-sharded across DP ranks (per the vLLM blog recipe).
+#       Highest aggregate throughput at large CONC.
+#
+# Serving flags follow the validated MI355X recipe from
+# https://recipes.vllm.ai/deepseek-ai/DeepSeek-V4-Pro?hardware=mi355x
+# https://github.com/SemiAnalysisAI/InferenceX/blob/main/benchmarks/single_node/fixed_seq_len/dsv4_fp4_mi355x_vllm.sh
+# Image is configured in amd-master.yaml.
+#
+# Required env vars:
+#   MODEL, TP, CONC, KV_OFFLOADING, TOTAL_CPU_DRAM_GB, RESULT_DIR
+#
+# KV_OFFLOADING=dram requires one of these. 
+#   KV_OFFLOAD_BACKEND=native.
+#   KV_OFFLOAD_BACKEND=mooncake.
+#   KV_OFFLOAD_BACKEND=lmcache.
+#   KV_OFFLOAD_BACKEND=hicache.
+
+source "$(dirname "$0")/../../benchmark_lib.sh"
+
+check_env_vars MODEL TP CONC KV_OFFLOADING TOTAL_CPU_DRAM_GB RESULT_DIR DURATION EP_SIZE DP_ATTENTION
+
+if [[ -n "${SLURM_JOB_ID:-}" ]]; then
+    echo "JOB $SLURM_JOB_ID running on ${SLURMD_NODENAME:-unknown}"
+fi
+
+# `hf download` creates the target dir if missing and is itself idempotent.
+# When MODEL_PATH is unset (stand-alone runs), fall back to the HF_HUB_CACHE
+# Either way, MODEL_PATH is what the server is launched with.
+if [[ -n "${MODEL_PATH:-}" ]]; then
+    if [[ ! -d "$MODEL_PATH" || -z "$(ls -A "$MODEL_PATH" 2>/dev/null)" ]]; then
+        hf download "$MODEL" --local-dir "$MODEL_PATH"
+    fi
+else
+    hf download "$MODEL"
+    export MODEL_PATH="$MODEL"
+fi
+
+if [ -n "${ROCR_VISIBLE_DEVICES:-}" ]; then
+    export HIP_VISIBLE_DEVICES="$ROCR_VISIBLE_DEVICES"
+fi
+
+# ---- Resolve traces and install deps ----------------------------------------
+resolve_trace_source
+install_agentic_deps
+
+# Nightly ROCm image may be missing runtime deps; ensure they are present.
+agentic_pip_install --quiet Pillow fastapi uvicorn
+
+# default
+export AIPERF_AGENTIC_CACHE_WARMUP_DURATION=600
+# tune
+#export AIPERF_AGENTIC_CACHE_WARMUP_DURATION=60
+#export AIPERF_AGENTIC_CACHE_WARMUP_DURATION=1200
+# tune
+export AIPERF_HTTP_TCP_USER_TIMEOUT=900000
+
+# vllm-project/router expands the one HTTP backend into one logical worker per
+# DP rank and sends X-data-parallel-rank on forwarded requests. aiperf's
+# X-Correlation-ID is stable for every turn of a conversation; alias it to the
+# router's preferred X-Session-ID header.
+USE_VLLM_ROUTER=false
+VLLM_BACKEND_PORT="$PORT"
+if [ "$DP_ATTENTION" = "true" ]; then
+    USE_VLLM_ROUTER=true
+    VLLM_BACKEND_PORT=$((PORT + 1))
+    VLLM_ROUTER_VERSION=0.1.14
+    VLLM_ROUTER_POLICY=consistent_hash
+    VLLM_ROUTER_METRICS_PORT=$((PORT + 10000))
+    export AIPERF_HTTP_X_SESSION_ID_FROM_CORRELATION_ID=1
+    agentic_pip_install --quiet "vllm-router==$VLLM_ROUTER_VERSION"
+fi
+
+# DeepSeek-V4-Pro weights are large; engine startup can exceed default 600s.
+export VLLM_ENGINE_READY_TIMEOUT_S=3600
+
+# vllm-project/vllm#43447 keeps local SWA prefix-cache tails sparsely, while
+# vllm-project/vllm#44774 applies the same reachability policy to Mooncake's
+# store mask. 32k matches the trace-replay tuning validated for this workload.
+export VLLM_PREFIX_CACHE_RETENTION_INTERVAL=32768
+
+# VLLM_PREFIX_CACHE_RETENTION_INTERVAL only applies to sliding-window/Mamba
+# models; this vLLM build raises ValueError if it is set for DSv4.
+
+# ---- Server config ----------------------------------------------------------
+SERVER_LOG="$RESULT_DIR/server.log"
+ROUTER_LOG="$RESULT_DIR/router.log"
+MOONCAKE_MASTER_LOG="$RESULT_DIR/mooncake_master.log"
+LMCACHE_LOG="$RESULT_DIR/lmcache_server.log"
+mkdir -p "$RESULT_DIR"
+
+SERVER_PID=""
+ROUTER_PID=""
+MOONCAKE_MASTER_PID=""
+
+OFFLOAD_ARGS=()
+
+if agentic_kv_offload_enabled; then
+case "${KV_OFFLOAD_BACKEND:-}" in
+  native)
+    require_agentic_kv_offload_backend native
+    # ---- vLLM native config ----------------------------------------------------------
+    unset VLLM_USE_SIMPLE_KV_OFFLOAD
+    # MI355X nodes have ~2.7 TiB of host DRAM available for offload;
+    # reserve 2.5 TB for the offload pool (leaves ~200 GB headroom for
+    # worker RSS / page cache / slurm cgroup).
+    TOTAL_CPU_DRAM_PARTITION_GB="$((TOTAL_CPU_DRAM_GB / (8 / TP)))"
+    # Use vLLM's regular native KV-offload path (OffloadingConnector),
+    # NOT the SimpleCPUOffloadConnector. The "native" backend resolves to
+    # OffloadingConnector by default; setting VLLM_USE_SIMPLE_KV_OFFLOAD=1
+    # would switch it to SimpleCPUOffloadConnector. We intentionally leave
+    # that env var UNSET here so the regular OffloadingConnector path is
+    # used. The shortcut --kv_offloading_backend native + --kv_offloading_size
+    # form constructs the KVTransferConfig at engine startup
+    # (vllm/config/vllm.py:662).
+
+    # Remove --disable-hybrid-kv-cache-manager and enable hybrid kv cache manager (default)
+    # This gives extra cache hit than disabling hybrid kv cache manager
+    OFFLOAD_ARGS=(
+        --kv_offloading_backend native
+        --kv_offloading_size "$TOTAL_CPU_DRAM_PARTITION_GB"
+    )
+
+    ;;
+  mooncake)
+    require_agentic_kv_offload_backend mooncake
+    # ---- Mooncake config ----------------------------------------------------------
+        # Embedded mode contributes one segment per GPU rank to a shared
+        # distributed store, so pre-divide the aggregate host-memory budget.
+        PER_RANK_GB=$((TOTAL_CPU_DRAM_GB / TP))
+
+        #MOONCAKE_VERSION=0.3.11.post1
+        #apt-get update && apt-get install -y libcurl4 libibverbs1 rdma-core librdmacm1 libnuma1 liburing2
+        #agentic_pip_install --quiet --no-cache-dir --no-deps \
+        #    --force-reinstall "mooncake-transfer-engine-non-cuda==$MOONCAKE_VERSION"
+
+        git clone https://github.com/kvcache-ai/Mooncake.git
+        cd Mooncake
+        bash dependencies.sh
+        mkdir build
+        cd build
+        cmake ..
+        make -j
+        sudo make install # optional, make it ready to be used by vLLM/SGLang
+        cd ..
+        cd ..
+
+        python3 -c "from mooncake.store import MooncakeDistributedStore" >/dev/null
+        export INFERENCEX_MOONCAKE_MAX_TRANSFER_BATCH_KEYS=32
+        python3 "$(dirname "$0")/patch_vllm_mooncake_transfer_batches.py"
+
+        MOONCAKE_MASTER_PORT=$((PORT + 12000))
+        MOONCAKE_CONFIG_PATH="$RESULT_DIR/mooncake_config.json"
+        cat > "$MOONCAKE_CONFIG_PATH" <<EOF
+{
+  "mode": "embedded",
+  "metadata_server": "P2PHANDSHAKE",
+  "master_server_address": "127.0.0.1:$MOONCAKE_MASTER_PORT",
+  "global_segment_size": "${PER_RANK_GB}GB",
+  "local_buffer_size": "2GB",
+  "protocol": "tcp",
+  "device_name": "",
+  "enable_offload": false
+}
+EOF
+# (srok)
+  #"protocol": "rdma",
+  #"device_name": "mlx5_0",
+  #"local_buffer_size": "4GB",
+        export MOONCAKE_CONFIG_PATH
+        export MC_ENABLE_DEST_DEVICE_AFFINITY=1
+        export PYTHONHASHSEED=0
+        export MC_SLICE_SIZE=1048576
+        # (srok)
+        #export MC_WORKERS_PER_CTX=4
+        export MC_WORKERS_PER_CTX=8
+
+        MOONCAKE_EVICTION_HIGH_WATERMARK_RATIO=0.80
+        MOONCAKE_EVICTION_RATIO=0.10
+        MOONCAKE_KV_LEASE_TTL=60s
+        #MOONCAKE_KV_LEASE_TTL=3600s
+
+        echo "Starting Mooncake master on port $MOONCAKE_MASTER_PORT..."
+        mooncake_master --port "$MOONCAKE_MASTER_PORT" \
+            --eviction_high_watermark_ratio="$MOONCAKE_EVICTION_HIGH_WATERMARK_RATIO" \
+            --eviction_ratio="$MOONCAKE_EVICTION_RATIO" \
+            --default_kv_lease_ttl="$MOONCAKE_KV_LEASE_TTL" \
+            > "$MOONCAKE_MASTER_LOG" 2>&1 &
+
+        sleep 10
+        MOONCAKE_MASTER_PID=$!
+        if ! kill -0 "$MOONCAKE_MASTER_PID" 2>/dev/null; then
+            echo "Mooncake master died during startup." >&2
+            cat "$MOONCAKE_MASTER_LOG" >&2
+            exit 1
+        fi
+        unset VLLM_USE_SIMPLE_KV_OFFLOAD
+        OFFLOAD_ARGS=(
+            --kv-transfer-config
+            '{"kv_connector":"MooncakeStoreConnector","kv_role":"kv_both","kv_connector_extra_config":{"load_async":true}}'
+        )
+
+    ;;
+  lmcache)
+    require_agentic_kv_offload_backend lmcache
+    # ---- Lmcache config ----------------------------------------------------------
+    LMCACHE_PID=""
+
+    cleanup_lmcache_server() {
+        if [[ -n "$LMCACHE_PID" ]] && kill -0 "$LMCACHE_PID" 2>/dev/null; then
+            kill "$LMCACHE_PID" 2>/dev/null || true
+            wait "$LMCACHE_PID" 2>/dev/null || true
+        fi
+    }
+
+    trap cleanup_lmcache_server EXIT
+
+    cleanup_agentic_services() {
+        local exit_code=$?
+        trap - EXIT INT TERM
+        set +e
+        stop_background_process_tree "$ROUTER_PID" "vLLM router"
+        stop_background_process_tree "$SERVER_PID" "vLLM server" 60
+        stop_background_process_tree "$MOONCAKE_MASTER_PID" "Mooncake master"
+        exit "$exit_code"
+    }
+    trap cleanup_agentic_services EXIT
+    trap 'exit 130' INT
+    trap 'exit 143' TERM
+
+    wait_for_lmcache_ready() {
+        { set +x; } 2>/dev/null
+        local attempts="${LMCACHE_READY_ATTEMPTS:-120}"
+        local tail_pid=""
+
+        while [ ! -f "$LMCACHE_LOG" ]; do
+            if [[ -n "$LMCACHE_PID" ]] && ! kill -0 "$LMCACHE_PID" 2>/dev/null; then
+                echo "LMCache server died before creating log file. Exiting." >&2
+                exit 1
+            fi
+            sleep 10
+        done
+
+        tail -f -n +1 "$LMCACHE_LOG" &
+        tail_pid=$!
+
+        for ((i = 1; i <= attempts; i++)); do
+            if curl --output /dev/null --silent --fail "http://127.0.0.1:${LMCACHE_HTTP_PORT}/healthcheck"; then
+                kill "$tail_pid" 2>/dev/null || true
+                wait "$tail_pid" 2>/dev/null || true
+                return 0
+            fi
+            if [[ -n "$LMCACHE_PID" ]] && ! kill -0 "$LMCACHE_PID" 2>/dev/null; then
+                echo "LMCache server died before becoming healthy. Log follows:" >&2
+                kill "$tail_pid" 2>/dev/null || true
+                wait "$tail_pid" 2>/dev/null || true
+                cat "$LMCACHE_LOG" >&2 || true
+                exit 1
+            fi
+            sleep 1
+        done
+
+        echo "Timed out waiting for LMCache server healthcheck. Log follows:" >&2
+        kill "$tail_pid" 2>/dev/null || true
+        wait "$tail_pid" 2>/dev/null || true
+        cat "$LMCACHE_LOG" >&2 || true
+        exit 1
+    }
+        { set +x; } 2>/dev/null
+        unset VLLM_USE_SIMPLE_KV_OFFLOAD
+
+        git clone https://github.com/LMCache/LMCache.git
+        cd LMCache
+        # https://github.com/LMCache/LMCache/pull/3853
+        git checkout dev
+        pip install -r requirements/build.txt
+        pip install grpcio==1.78.0
+        CXX=hipcc BUILD_WITH_HIP=1 pip install -e .   --no-build-isolation
+        cd ..
+
+        python3 -c "import lmcache.integration.vllm.lmcache_mp_connector" >/dev/null
+
+        TOTAL_CPU_DRAM_PARTITION_GB="$((TOTAL_CPU_DRAM_GB / (8 / TP)))"
+        # Match the B200 Kimi LMCache setup: keep a 2.5 TB semantic CPU KV
+        # pool, but let the external MP server own that pool so vLLM does not
+        # split --kv-offloading-size across TP ranks through the integrated
+        # LMCache backend.
+        LMCACHE_HOST="${LMCACHE_HOST:-127.0.0.1}"
+        LMCACHE_PORT="${LMCACHE_PORT:-5555}"
+        LMCACHE_HTTP_PORT="${LMCACHE_HTTP_PORT:-8080}"
+        # LMCacheMPConnector concatenates lmcache.mp.host and port into the
+        # ZMQ endpoint. Bind the server to a raw host, but pass the connector a
+        # ZMQ-style host string.
+        LMCACHE_CONNECT_HOST="${LMCACHE_CONNECT_HOST:-tcp://$LMCACHE_HOST}"
+        LMCACHE_L1_SIZE_GB="${TOTAL_CPU_DRAM_PARTITION_GB}"
+        if [ "$LMCACHE_L1_SIZE_GB" -gt "$TOTAL_CPU_DRAM_GB" ]; then
+            echo "Error: LMCACHE_L1_SIZE_GB=$LMCACHE_L1_SIZE_GB exceeds configured capacity $TOTAL_CPU_DRAM_GB" >&2
+            exit 1
+        fi
+        LMCACHE_L1_INIT_SIZE_GB="${LMCACHE_L1_INIT_SIZE_GB:-20}"
+        # LMCache read locks are leases on chunks that lookup has promised
+        # vLLM can retrieve. The default 300s TTL is too short for this
+        # long-context agentic queue: TP8/conc32 can spend >300s between
+        # lookup and retrieve while GPU KV is saturated, which leaves the
+        # object present in L1 but no longer readable. Keep the 2.5 TB pool
+        # size unchanged and only extend the lookup-to-retrieve lease.
+        LMCACHE_L1_READ_TTL_SECONDS="${LMCACHE_L1_READ_TTL_SECONDS:-7200}"
+        LMCACHE_CHUNK_SIZE="${LMCACHE_CHUNK_SIZE:-256}"
+        LMCACHE_MAX_WORKERS="${LMCACHE_MAX_WORKERS:-$TP}"
+        export PYTHONHASHSEED="${PYTHONHASHSEED:-0}"
+        export LMCACHE_BLOCKING_TIMEOUT_SECS=1200
+        LMCACHE_TX_MODE="lmcache_driven"
+
+        echo "Starting LMCache MP server..."
+        LMCACHE_CMD=(
+            lmcache server
+            --host "$LMCACHE_HOST"
+            --port "$LMCACHE_PORT"
+            --http-host "$LMCACHE_HOST"
+            --http-port "$LMCACHE_HTTP_PORT"
+            --l1-size-gb "$LMCACHE_L1_SIZE_GB"
+            --l1-init-size-gb "$LMCACHE_L1_INIT_SIZE_GB"
+            --l1-read-ttl-seconds "$LMCACHE_L1_READ_TTL_SECONDS"
+            --chunk-size "$LMCACHE_CHUNK_SIZE"
+            --max-workers "$LMCACHE_MAX_WORKERS"
+            --eviction-policy LRU
+            --supported-transfer-mode "$LMCACHE_TX_MODE"
+        )
+        printf '%q ' "${LMCACHE_CMD[@]}" > "$RESULT_DIR/lmcache_command.txt"
+        printf '\n' >> "$RESULT_DIR/lmcache_command.txt"
+        "${LMCACHE_CMD[@]}" > "$LMCACHE_LOG" 2>&1 &
+        LMCACHE_PID=$!
+        echo "LMCache server PID: $LMCACHE_PID"
+        wait_for_lmcache_ready
+
+        PREFIX_CACHE_ARGS=(--enable-prefix-caching)
+        OFFLOAD_ARGS=(
+            --kv-transfer-config
+            "{\"kv_connector\":\"LMCacheMPConnector\",\"kv_connector_module_path\":\"lmcache.integration.vllm.lmcache_mp_connector\",\"kv_role\":\"kv_both\",\"kv_connector_extra_config\":{\"lmcache.mp.host\":\"$LMCACHE_CONNECT_HOST\",\"lmcache.mp.port\":$LMCACHE_PORT,\"lmcache.mp.mq_timeout\":6000.0}}"
+        )
+    ;;
+  *)
+    echo "Error: unsupported KV_OFFLOAD_BACKEND '${KV_OFFLOAD_BACKEND:-}' (expected: native, mooncake, lmcache)" >&2
+    exit 1
+    ;;
+esac
+fi
+
+PARALLEL_ARGS=(--tensor-parallel-size "$TP" --data-parallel-size 1)
+if [ "$DP_ATTENTION" = "true" ]; then
+    PARALLEL_ARGS=(--tensor-parallel-size 1 --data-parallel-size "$TP")
+fi
+
+EP_ARGS=()
+if [ "$EP_SIZE" -gt 1 ]; then
+    EP_ARGS=(--enable-expert-parallel)
+fi
+
+# AgentX concurrency counts live session trees, not individual requests.
+# Subagent fan-out can push instantaneous request concurrency above CONC, so
+# leave 2x headroom rather than clipping those bursts at the scheduler.
+MAX_NUM_SEQS=$((2 * CONC))
+
+echo "Starting vllm server..."
+set -x
+export VLLM_ROCM_USE_AITER=1
+#export VLLM_ROCM_QUICK_REDUCE_QUANTIZATION=INT4
+export VLLM_ROCM_USE_AITER_MOE=1
+
+sleep 180
+
+# https://github.com/vllm-project/vllm/pull/45497
+git clone https://gist.github.com/seungrokj/a37ff4d9a52db31752e2d5fa5b192e00
+cp a37ff4d9a52db31752e2d5fa5b192e00/gistfile1.txt /usr/local/lib/python3.12/dist-packages/vllm/v1/core/sched/scheduler.py
+
+{ set +x; } 2>/dev/null
+VLLM_CMD=(
+    vllm serve "$MODEL_PATH" --served-model-name "$MODEL"
+    --host 0.0.0.0
+    --port "$VLLM_BACKEND_PORT"
+    --trust-remote-code
+    --async-scheduling
+    --distributed-executor-backend mp
+    --kv-cache-dtype fp8
+    "${PARALLEL_ARGS[@]}"
+    "${EP_ARGS[@]}"
+    --gpu-memory-utilization 0.8 
+    --moe-backend aiter
+    --compilation-config '{"mode":3,"cudagraph_mode":"FULL_AND_PIECEWISE"}'
+    --tokenizer-mode deepseek_v4
+    --tool-call-parser deepseek_v4
+    --reasoning-parser deepseek_v4
+    --enable-auto-tool-choice
+    --enable-prefix-caching
+    --no-disable-hybrid-kv-cache-manager
+    --max-num-seqs "$MAX_NUM_SEQS"
+    "${OFFLOAD_ARGS[@]}"
+)
+
+# (srok), not yet
+    #--attention_config.use_fp4_indexer_cache=True
+printf '%q ' "${VLLM_CMD[@]}" | tee "$RESULT_DIR/vllm_command.txt"
+printf '\n' | tee -a "$RESULT_DIR/vllm_command.txt"
+"${VLLM_CMD[@]}" > "$SERVER_LOG" 2>&1 &
+SERVER_PID=$!
+echo "Server PID: $SERVER_PID"
+
+wait_for_server_ready --port "$VLLM_BACKEND_PORT" --server-log "$SERVER_LOG" --server-pid "$SERVER_PID"
+
+if [ "$USE_VLLM_ROUTER" = "true" ]; then
+    echo "Starting native vLLM router on port $PORT for $TP DP ranks..."
+    vllm-router \
+        --worker-urls "http://localhost:$VLLM_BACKEND_PORT" \
+        --policy "$VLLM_ROUTER_POLICY" \
+        --intra-node-data-parallel-size "$TP" \
+        --host 0.0.0.0 \
+        --port "$PORT" \
+        --prometheus-host 127.0.0.1 \
+        --prometheus-port "$VLLM_ROUTER_METRICS_PORT" \
+        --request-timeout-secs 14400 \
+        --disable-retries > "$ROUTER_LOG" 2>&1 &
+    ROUTER_PID=$!
+    echo "Router PID: $ROUTER_PID"
+    wait_for_server_ready --port "$PORT" --server-log "$ROUTER_LOG" --server-pid "$ROUTER_PID"
+fi
+
+# ---- Run benchmark ----------------------------------------------------------
+build_replay_cmd "$RESULT_DIR"
+
+run_agentic_replay_and_write_outputs "$RESULT_DIR"
diff --git a/configs/amd-master.yaml b/configs/amd-master.yaml
index 72514a7756..6174746534 100644
--- a/configs/amd-master.yaml
+++ b/configs/amd-master.yaml
@@ -2027,11 +2027,8 @@ qwen3.5-fp8-mi355x-sglang-agentic-hicache:
 # image tag, so bumping sglang is just an image tag bump here. Sweeps
 # DP-attention on/off and EP=8.
 
-# CONC ranges mirror dsv4-fp4-b200-vllm-agentic for cross-hardware
-# comparability. Offload sweep is none-only (SGLang has no equivalent of
-# vLLM's SimpleCPUOffloadConnector path that we exercise on b200).
 dsv4-fp4-mi355x-vllm-agentic:
-  image: vllm/vllm-openai-rocm:v0.22.0
+  image: vllm/vllm-openai-rocm:nightly-09663abde0f50944a8d5ea30120666024b503faa
   model: deepseek-ai/DeepSeek-V4-Pro
   model-prefix: dsv4
   runner: cluster:mi355x-amds
@@ -2040,10 +2037,11 @@ dsv4-fp4-mi355x-vllm-agentic:
   multinode: false
   scenarios:
     agentic-coding:
-    - search-space:
-      - { tp: 8, kv-offloading: none, conc-list: [1, 2, 4] }
-      - { tp: 4, kv-offloading: none, conc-list: [1, 2, 4, 8, 10, 12, 16] }
-      - { tp: 4, ep: 4, dp-attn: true, kv-offloading: none, conc-list: [16, 24, 32, 40, 48] }
+    - dram-utilization: 0.60
+      search-space:
+      - { tp: 8, ep: 1, dp-attn: false, kv-offloading: none, conc-list: [1, 4, 8, 16, 32, 40, 48] }
+      - { tp: 8, ep: 1, dp-attn: true, kv-offloading: none, conc-list: [64, 72] }
+      - { tp: 8, ep: 1, dp-attn: false, kv-offloading: dram, kv-offload-backend: lmcache, conc-list: [32, 40, 48] }
 
 # DSv4-Pro FP4 on MI355X via SGLang. Uses a rocm720 mi35x image built off the
 # amd/deepseek_v4 branch in sgl-project/sglang; the SHA is encoded in the
diff --git a/perf-changelog.yaml b/perf-changelog.yaml
index 3425fd7c7c..164612b309 100644
--- a/perf-changelog.yaml
+++ b/perf-changelog.yaml
@@ -4587,6 +4587,14 @@
     - "Add high concurrency configs"
   pr-link: https://github.com/SemiAnalysisAI/InferenceX/pull/1994
 
+- config-keys:
+    - dsv4-fp4-mi355x-vllm-agentic
+  description:
+    - "Update vLLM ROCm image from v0.22.0 to nightly-09663abde0f50944a8d5ea30120666024b503faa"
+    - "Pin LMCache to commit 1720917e to fix scheduler ValueError with hybrid KV cache manager"
+    - "Add LMCache KV offload backend with tuned config (blocking timeout, transfer mode)"
+  pr-link: https://github.com/SemiAnalysisAI/InferenceX/pull/2109
+
 - config-keys:
     - minimaxm3-fp8-mi355x-vllm-mtp
   description: