diff --git a/benchmarks/single_node/agentic/minimaxm3_fp8_mi300x_mtp.sh b/benchmarks/single_node/agentic/minimaxm3_fp8_mi300x_mtp.sh
new file mode 100755
index 000000000..88d907881
--- /dev/null
+++ b/benchmarks/single_node/agentic/minimaxm3_fp8_mi300x_mtp.sh
@@ -0,0 +1,193 @@
+#!/usr/bin/env bash
+set -eo pipefail
+set -x
+
+# MiniMax-M3 MXFP8 MI300X AgentX with EAGLE3-GQA and optional LMCache MP.
+
+source "$(dirname "$0")/../../benchmark_lib.sh"
+
+export EVAL_FRAMEWORK="lm-eval"
+
+check_env_vars MODEL TP CONC KV_OFFLOADING TOTAL_CPU_DRAM_GB RESULT_DIR DURATION EP_SIZE DP_ATTENTION PORT EVAL_ONLY
+
+DRAFT_MODEL="Inferact/MiniMax-M3-EAGLE3-GQA"
+NUM_SPEC_TOKENS=3
+SYNTHETIC_ACCEPT_LEN=2.78
+
+if [[ -n "$SLURM_JOB_ID" ]]; then
+    echo "JOB $SLURM_JOB_ID running on $SLURMD_NODENAME"
+fi
+if [[ -n "$ROCR_VISIBLE_DEVICES" ]]; then
+    export HIP_VISIBLE_DEVICES="$ROCR_VISIBLE_DEVICES"
+fi
+
+if [[ -n "$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="$MODEL"
+fi
+hf download "$DRAFT_MODEL"
+
+rocm-smi || true
+amd-smi || true
+resolve_trace_source
+install_agentic_deps
+
+export AIPERF_SERVER_METRICS_URLS="http://localhost:${PORT}/metrics"
+export AIPERF_REQUIRED_SERVER_METRIC_PREFIX="vllm:"
+
+SERVER_LOG="$RESULT_DIR/server.log"
+LMCACHE_LOG="$RESULT_DIR/lmcache_server.log"
+mkdir -p "$RESULT_DIR"
+
+SERVER_PID=""
+LMCACHE_PIDS=()
+cleanup_agentic_services() {
+    local exit_code=$?
+    trap - EXIT INT TERM
+    set +e
+    stop_background_process_tree "$SERVER_PID" "vLLM server" 60
+    local i
+    for i in "${!LMCACHE_PIDS[@]}"; do
+        stop_background_process_tree "${LMCACHE_PIDS[$i]}" "LMCache server $i"
+    done
+    exit "$exit_code"
+}
+trap cleanup_agentic_services EXIT
+trap 'exit 130' INT
+trap 'exit 143' TERM
+
+OFFLOAD_ARGS=()
+case "$KV_OFFLOAD_BACKEND" in
+    "")
+        require_agentic_kv_offload_none
+        ;;
+    lmcache)
+        require_agentic_kv_offload_backend lmcache
+        LMCACHE_VERSION="0.5.3"
+        LMCACHE_ROCM_INDEX="https://github.com/LMCache/LMCache/releases/expanded_assets/v${LMCACHE_VERSION}-rocm"
+        agentic_pip_install --quiet --no-cache-dir --no-deps \
+            "sortedcontainers==2.4.0" \
+            "opentelemetry-exporter-prometheus==0.61b0" \
+            "cupy-rocm-7-0==14.1.1" \
+            "lmcache==${LMCACHE_VERSION}" --find-links "$LMCACHE_ROCM_INDEX"
+        python3 -c \
+            "import cupy; import lmcache.integration.vllm.lmcache_mp_connector; import opentelemetry.exporter.prometheus" \
+            >/dev/null
+
+        LMCACHE_L1_SHARD_GB=$((TOTAL_CPU_DRAM_GB / TP))
+        if [ "$LMCACHE_L1_SHARD_GB" -lt 1 ]; then
+            echo "Error: LMCache DRAM budget is less than 1 GB per TP rank." >&2
+            exit 1
+        fi
+
+        LMCACHE_SERVER_URLS=()
+        LMCACHE_HTTP_PORTS=()
+        LMCACHE_LOGS=()
+        : > "$RESULT_DIR/lmcache_command.txt"
+        for shard in $(seq 0 $((TP - 1))); do
+            shard_port=$((5555 + shard))
+            shard_http_port=$((8080 + shard))
+            shard_log="${LMCACHE_LOG%.log}_${shard}.log"
+            LMCACHE_CMD=(
+                lmcache server
+                --host 127.0.0.1
+                --port "$shard_port"
+                --http-host 127.0.0.1
+                --http-port "$shard_http_port"
+                --l1-size-gb "$LMCACHE_L1_SHARD_GB"
+                --l1-init-size-gb 10
+                --l1-read-ttl-seconds 7200
+                --chunk-size 256
+                --max-workers 2
+                --eviction-policy LRU
+                --supported-transfer-mode lmcache_driven
+            )
+            append_command "$RESULT_DIR/lmcache_command.txt" "${LMCACHE_CMD[@]}"
+            "${LMCACHE_CMD[@]}" > "$shard_log" 2>&1 &
+            LMCACHE_PIDS+=($!)
+            LMCACHE_HTTP_PORTS+=("$shard_http_port")
+            LMCACHE_LOGS+=("$shard_log")
+            LMCACHE_SERVER_URLS+=("tcp://127.0.0.1:${shard_port}")
+        done
+        for shard in "${!LMCACHE_PIDS[@]}"; do
+            wait_for_ready \
+                --endpoint "http://127.0.0.1:${LMCACHE_HTTP_PORTS[$shard]}/healthcheck" \
+                --log "${LMCACHE_LOGS[$shard]}" \
+                --pid "${LMCACHE_PIDS[$shard]}" \
+                --sleep-interval 1 \
+                --timeout 600
+        done
+        LMCACHE_SERVER_URLS_CSV=$(IFS=,; echo "${LMCACHE_SERVER_URLS[*]}")
+        OFFLOAD_ARGS=(
+            --kv-transfer-config
+            "{\"kv_connector\":\"LMCacheMPConnector\",\"kv_connector_module_path\":\"lmcache.integration.vllm.lmcache_mp_connector\",\"kv_role\":\"kv_both\",\"kv_connector_extra_config\":{\"lmcache.mp.server_urls\":\"$LMCACHE_SERVER_URLS_CSV\",\"lmcache.mp.mq_timeout\":6000.0}}"
+        )
+        ;;
+    *)
+        echo "Unsupported KV_OFFLOAD_BACKEND: $KV_OFFLOAD_BACKEND" >&2
+        exit 1
+        ;;
+esac
+
+PARALLEL_ARGS=(--tensor-parallel-size "$TP")
+if [ "$EP_SIZE" -gt 1 ]; then
+    PARALLEL_ARGS+=(--enable-expert-parallel)
+fi
+
+if [ "$EVAL_ONLY" = "true" ]; then
+    SPEC_CONFIG="{\"method\":\"eagle3\",\"model\":\"$DRAFT_MODEL\",\"num_speculative_tokens\":$NUM_SPEC_TOKENS,\"attention_backend\":\"TRITON_ATTN\"}"
+else
+    SPEC_CONFIG="{\"method\":\"eagle3\",\"model\":\"$DRAFT_MODEL\",\"num_speculative_tokens\":$NUM_SPEC_TOKENS,\"attention_backend\":\"TRITON_ATTN\",\"rejection_sample_method\":\"synthetic\",\"synthetic_acceptance_length\":$SYNTHETIC_ACCEPT_LEN}"
+fi
+
+export PYTHONNOUSERSITE=1
+export VLLM_ENGINE_READY_TIMEOUT_S=3600
+export VLLM_EXECUTE_MODEL_TIMEOUT_SECONDS=1800
+export VLLM_USE_BREAKABLE_CUDAGRAPH=0
+export VLLM_ROCM_USE_AITER=1
+export VLLM_ROCM_USE_AITER_MHA=0
+export TORCH_BLAS_PREFER_HIPBLASLT=1
+export NCCL_MIN_NCHANNELS=112
+export GPU_MAX_HW_QUEUES=2
+
+VLLM_CMD=(
+    vllm serve "$MODEL_PATH"
+    --served-model-name "$MODEL"
+    --host 0.0.0.0
+    --port "$PORT"
+    "${PARALLEL_ARGS[@]}"
+    --trust-remote-code
+    --block-size 128
+    --gpu-memory-utilization 0.90
+    --enable-chunked-prefill
+    --max-num-batched-tokens 16384
+    --language-model-only
+    --enable-prefix-caching
+    --attention-backend TRITON_ATTN
+    --kv-cache-dtype fp8
+    --tool-call-parser minimax_m3
+    --reasoning-parser minimax_m3
+    --enable-auto-tool-choice
+    --default-chat-template-kwargs '{"thinking_mode":"enabled"}'
+    --max-num-seqs "$((2 * CONC))"
+    --stream-interval 20
+    --speculative-config "$SPEC_CONFIG"
+    "${OFFLOAD_ARGS[@]}"
+)
+write_command "$RESULT_DIR/server_command.txt" "${VLLM_CMD[@]}"
+"${VLLM_CMD[@]}" > "$SERVER_LOG" 2>&1 &
+SERVER_PID=$!
+
+wait_for_server_ready --port "$PORT" --server-log "$SERVER_LOG" --server-pid "$SERVER_PID"
+
+if [ "$EVAL_ONLY" = "true" ]; then
+    run_eval --port "$PORT"
+else
+    build_replay_cmd "$RESULT_DIR"
+    REPLAY_CMD+=" --apply-chat-template"
+    run_agentic_replay_and_write_outputs "$RESULT_DIR"
+fi
diff --git a/configs/amd-master.yaml b/configs/amd-master.yaml
index bb7bcb339..552451fc7 100644
--- a/configs/amd-master.yaml
+++ b/configs/amd-master.yaml
@@ -1522,6 +1522,21 @@ minimaxm3-fp8-mi300x-vllm-agentic:
       - { tp: 8, kv-offloading: dram, kv-offload-backend: { name: mooncake, version: "0.3.11.post1" }, conc-list: [5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 16, 18, 20] }
       - { tp: 8, ep: 8, kv-offloading: dram, kv-offload-backend: { name: mooncake, version: "0.3.11.post1" }, conc-list: [5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 16, 18, 20] }
 
+minimaxm3-fp8-mi300x-vllm-agentic-mtp:
+  image: vllm/vllm-openai-rocm:v0.27.1
+  model: MiniMaxAI/MiniMax-M3-MXFP8
+  model-prefix: minimaxm3
+  runner: cluster:mi300x-amds
+  precision: fp8
+  framework: vllm
+  multinode: false
+  scenarios:
+    agentic-coding:
+    - dram-utilization: 0.80
+      search-space:
+      - { tp: 8, spec-decoding: mtp, kv-offloading: none, conc-list: [2, 4, 6, 8, 10] }
+      - { tp: 8, spec-decoding: mtp, kv-offloading: dram, kv-offload-backend: { name: lmcache, version: "0.5.3" }, conc-list: [16] }
+
 # GLM-5.2 FP8 full-context AgentX refresh on MI325X. This preserves the TP8
 # GPU-resident-KV c1/c2/c3/c4/c5/c6/c8 curve from Actions run 29657732517
 # and enables EAGLE MTP with the committed thinking-on golden AL.
diff --git a/perf-changelog.yaml b/perf-changelog.yaml
index 998671c91..04ba9feb5 100644
--- a/perf-changelog.yaml
+++ b/perf-changelog.yaml
@@ -5926,6 +5926,14 @@
     - "Rides on the NVFP4-V2 checkpoint switch from #2205"
   pr-link: https://github.com/SemiAnalysisAI/InferenceX/pull/2550
 
+- config-keys:
+    - minimaxm3-fp8-mi300x-vllm-agentic-mtp
+  scenario-type:
+    - agentic-coding
+  description:
+    - "Add MI300X MiniMax-M3 MXFP8 AgentX with vLLM EAGLE3-GQA, measured resident TP8 c2-c10, and an LMCache MP DRAM-offload c16 point."
+  pr-link: https://github.com/SemiAnalysisAI/InferenceX/pull/2580
+
 - config-keys:
     - dsv4-fp4-b200-sglang-agentic-hicache-mtp
   scenario-type: