diff --git a/benchmarks/single_node/agentic/minimaxm3_fp8_h200_mtp.sh b/benchmarks/single_node/agentic/minimaxm3_fp8_h200_mtp.sh
new file mode 100755
index 000000000..28e7adc4a
--- /dev/null
+++ b/benchmarks/single_node/agentic/minimaxm3_fp8_h200_mtp.sh
@@ -0,0 +1,209 @@
+#!/usr/bin/env bash
+set -eo pipefail
+set -x
+
+# H200 MiniMax-M3 MXFP8 AgentX with EAGLE3 and optional Mooncake DRAM KV offload.
+
+source "$(dirname "$0")/../../benchmark_lib.sh"
+
+check_env_vars MODEL TP CONC KV_OFFLOADING TOTAL_CPU_DRAM_GB RESULT_DIR DURATION PORT EVAL_ONLY
+
+DRAFT_MODEL="Inferact/MiniMax-M3-EAGLE3-GQA"
+
+resolve_complete_model_snapshot() {
+    python3 - "$1" <<'PY'
+import json
+import sys
+from pathlib import Path
+
+model_cache_dir = Path(sys.argv[1])
+try:
+    revision = model_cache_dir.joinpath("refs/main").read_text().strip()
+except OSError:
+    raise SystemExit
+
+if not revision or Path(revision).name != revision:
+    raise SystemExit
+
+snapshot = model_cache_dir / "snapshots" / revision
+index_path = snapshot / "model.safetensors.index.json"
+required_files = (
+    snapshot / "config.json",
+    snapshot / "tokenizer_config.json",
+    index_path,
+)
+if not all(path.is_file() for path in required_files):
+    raise SystemExit
+try:
+    weight_map = json.loads(index_path.read_text())["weight_map"]
+except (KeyError, json.JSONDecodeError, OSError):
+    raise SystemExit
+shards = {snapshot / filename for filename in weight_map.values()}
+if shards and all(path.is_file() for path in shards):
+    print(snapshot)
+PY
+}
+
+if [[ -n "${MODEL_PATH:-}" ]]; then
+    if [[ ! -d "$MODEL_PATH" || -z "$(ls -A "$MODEL_PATH" 2>/dev/null)" ]]; then
+        hf download "$MODEL" --local-dir "$MODEL_PATH"
+    fi
+else
+    MODEL_CACHE_ROOT="${HF_HUB_CACHE:-${HF_HOME:-$HOME/.cache/huggingface/hub}}"
+    MODEL_CACHE_DIR="$MODEL_CACHE_ROOT/models--${MODEL//\//--}"
+    mkdir -p "$MODEL_CACHE_ROOT"
+    MODEL_PATH=$(resolve_complete_model_snapshot "$MODEL_CACHE_DIR")
+    if [[ -z "$MODEL_PATH" ]]; then
+        exec 9>"$MODEL_CACHE_ROOT/.minimaxm3-download.lock"
+        flock -w 3600 9
+        MODEL_PATH=$(resolve_complete_model_snapshot "$MODEL_CACHE_DIR")
+        if [[ -z "$MODEL_PATH" ]]; then
+            DOWNLOADED_MODEL_PATH=$(hf download "$MODEL")
+            MODEL_PATH=$(resolve_complete_model_snapshot "$MODEL_CACHE_DIR")
+            if [[ -z "$MODEL_PATH" ]]; then
+                echo "Downloaded model snapshot is incomplete: $DOWNLOADED_MODEL_PATH" >&2
+                exit 1
+            fi
+        fi
+        flock -u 9
+    fi
+    echo "Using complete cached model snapshot: $MODEL_PATH"
+    export MODEL_PATH
+fi
+
+# Concurrent downloads on the shared HF cache can hit transient stale handles.
+for attempt in 1 2 3 4 5; do
+    hf download "$DRAFT_MODEL" && break
+    if [ "$attempt" = 5 ]; then echo "hf download of $DRAFT_MODEL failed after $attempt attempts" >&2; exit 1; fi
+    echo "hf download attempt $attempt failed; retrying in 60s" >&2
+    sleep 60
+done
+nvidia-smi
+
+export WEKA_LOADER_OVERRIDE=semianalysis_cc_traces_weka_062126
+resolve_trace_source
+install_agentic_deps
+
+export VLLM_ENGINE_READY_TIMEOUT_S=3600
+export PYTHONNOUSERSITE=1
+
+SERVER_LOG="$RESULT_DIR/server.log"
+MOONCAKE_MASTER_LOG="$RESULT_DIR/mooncake_master.log"
+mkdir -p "$RESULT_DIR"
+
+SERVER_PID=""
+MOONCAKE_MASTER_PID=""
+cleanup_services() {
+    local exit_code=$?
+    trap - EXIT INT TERM
+    set +e
+    stop_background_process_tree "$SERVER_PID" "vLLM server" 60
+    stop_background_process_tree "$MOONCAKE_MASTER_PID" "Mooncake master" 30
+    exit "$exit_code"
+}
+trap cleanup_services EXIT
+trap 'exit 130' INT
+trap 'exit 143' TERM
+
+OFFLOAD_ARGS=()
+MODEL_CHECKPOINT_PAGE_CACHE_GIB=414
+MOONCAKE_LOCAL_BUFFER_GIB=4
+if [ "$KV_OFFLOADING" = "none" ]; then
+    require_agentic_kv_offload_none
+elif [ "$KV_OFFLOADING" = "dram" ]; then
+    require_agentic_kv_offload_backend mooncake
+    TOTAL_CPU_DRAM_GIB=$((TOTAL_CPU_DRAM_GB * 1000000000 / 1073741824))
+    PER_RANK_GB=$(((TOTAL_CPU_DRAM_GIB - MODEL_CHECKPOINT_PAGE_CACHE_GIB) / TP - MOONCAKE_LOCAL_BUFFER_GIB))
+    if (( PER_RANK_GB <= 0 )); then
+        echo "Error: CPU DRAM budget is too small for checkpoint cache and KV offload" >&2
+        exit 1
+    fi
+    MOONCAKE_VERSION=0.3.11.post1
+    agentic_pip_install --quiet --no-cache-dir --no-deps \
+        --force-reinstall "mooncake-transfer-engine-cuda13==$MOONCAKE_VERSION"
+    python3 -c "from mooncake.store import MooncakeDistributedStore" >/dev/null
+    MOONCAKE_MASTER_PORT=$((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": "4GB",
+  "protocol": "rdma",
+  "device_name": "",
+  "enable_offload": false
+}
+EOF
+    export MOONCAKE_CONFIG_PATH PYTHONHASHSEED=0 MC_SLICE_SIZE=1048576 MC_WORKERS_PER_CTX=4
+    export MC_ENABLE_DEST_DEVICE_AFFINITY=1
+    mooncake_master --port "$MOONCAKE_MASTER_PORT" \
+        --eviction_high_watermark_ratio=0.80 \
+        --eviction_ratio=0.10 > "$MOONCAKE_MASTER_LOG" 2>&1 &
+    MOONCAKE_MASTER_PID=$!
+    sleep 2
+    kill -0 "$MOONCAKE_MASTER_PID"
+    OFFLOAD_ARGS=(
+        --kv-transfer-config
+        '{"kv_connector":"MooncakeStoreConnector","kv_role":"kv_both","kv_connector_extra_config":{"load_async":true}}'
+    )
+else
+    echo "Error: unsupported KV_OFFLOADING='$KV_OFFLOADING'" >&2
+    exit 1
+fi
+
+export AIPERF_SERVER_METRICS_URLS="http://localhost:${PORT}/metrics"
+export AIPERF_REQUIRED_SERVER_METRIC_PREFIX="vllm:"
+
+NUM_SPEC_TOKENS=3
+TOKENS_PER_SEQ=$((1 + NUM_SPEC_TOKENS))
+
+# Golden AL is minimaxm3_eagle3_gqa.yaml thinking_on[3]; eval uses real verification.
+SYNTHETIC_ACCEPT_LEN=2.78
+if [ "$EVAL_ONLY" = "true" ]; then
+    SPEC_CONFIG="{\"method\": \"eagle3\", \"model\": \"$DRAFT_MODEL\", \"num_speculative_tokens\": $NUM_SPEC_TOKENS, \"attention_backend\": \"FLASH_ATTN\"}"
+else
+    SPEC_CONFIG="{\"method\": \"eagle3\", \"model\": \"$DRAFT_MODEL\", \"num_speculative_tokens\": $NUM_SPEC_TOKENS, \"attention_backend\": \"FLASH_ATTN\", \"rejection_sample_method\": \"synthetic\", \"synthetic_acceptance_length\": $SYNTHETIC_ACCEPT_LEN}"
+fi
+
+MAX_NUM_SEQS=$((2 * CONC))
+# MTP verifies four tokens per sequence, so CUDA graph capture is token-sized.
+MAX_CUDAGRAPH_CAPTURE_SIZE=$((MAX_NUM_SEQS * TOKENS_PER_SEQ))
+
+VLLM_CMD=(
+    vllm serve "$MODEL_PATH"
+    --served-model-name "$MODEL"
+    --host 0.0.0.0
+    --port "$PORT"
+    --tensor-parallel-size "$TP"
+    --data-parallel-size 1
+    --gpu-memory-utilization 0.90
+    --kv-cache-dtype fp8
+    --attention-backend TRITON_ATTN
+    --block-size 128
+    --language-model-only
+    --enable-prefix-caching
+    --enable-prompt-tokens-details
+    --default-chat-template-kwargs '{"thinking_mode":"enabled"}'
+    --max-num-seqs "$MAX_NUM_SEQS"
+    --max-cudagraph-capture-size "$MAX_CUDAGRAPH_CAPTURE_SIZE"
+    --speculative-config "$SPEC_CONFIG"
+    --tool-call-parser minimax_m3
+    --reasoning-parser minimax_m3
+    --enable-auto-tool-choice
+    --trust-remote-code
+    "${OFFLOAD_ARGS[@]}"
+)
+write_command "$RESULT_DIR/vllm_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"
+    run_agentic_replay_and_write_outputs "$RESULT_DIR"
+fi
diff --git a/configs/nvidia-master.yaml b/configs/nvidia-master.yaml
index 92e8f1646..757a15c0e 100644
--- a/configs/nvidia-master.yaml
+++ b/configs/nvidia-master.yaml
@@ -7177,6 +7177,25 @@ minimaxm3-fp8-h200-vllm-agentic:
       - { tp: 8, ep: 8, kv-offloading: none, conc-list: [2, 4, 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-h200-vllm-agentic-mtp:
+  image: vllm/vllm-openai:v0.27.1
+  model: MiniMaxAI/MiniMax-M3-MXFP8
+  model-prefix: minimaxm3
+  runner: cluster:h200-dgxc
+  precision: fp8
+  framework: vllm
+  multinode: false
+  scenarios:
+    agentic-coding:
+    # Fast runs 31540120459 and 31558981228 locate the resident knee at c10
+    # and show Mooncake retaining throughput at c12-c14. TEP is dominated,
+    # DEP cannot allocate the 1M-token KV cache, and vLLM-simple falls after
+    # c10, so the strict sweep keeps only the measured Pareto candidates.
+    - dram-utilization: 0.80
+      search-space:
+      - { tp: 8, spec-decoding: mtp, kv-offloading: none, conc-list: [1, 2, 4, 6, 8, 10] }
+      - { tp: 8, spec-decoding: mtp, kv-offloading: dram, kv-offload-backend: { name: mooncake, version: "0.3.11.post1" }, conc-list: [12, 14] }
+
 qwen3.5-fp4-b200-sglang-agentic-mtp:
   image: lmsysorg/sglang:v0.5.16-cu130
   model: nvidia/Qwen3.5-397B-A17B-NVFP4
diff --git a/perf-changelog.yaml b/perf-changelog.yaml
index 461e296aa..b13720a31 100644
--- a/perf-changelog.yaml
+++ b/perf-changelog.yaml
@@ -5866,3 +5866,11 @@
     - "Use lmsysorg/sglang:v0.5.16-rocm720-mi30x, FP8 KV cache, AITER attention, and required SGLang Prometheus metrics"
     - "Select a 32-point official TP2/EP2, TP4, TEP4, TP8, and TEP8 matrix from the complete 62-point fast discovery sweep"
   pr-link: https://github.com/SemiAnalysisAI/InferenceX/pull/2566
+
+- config-keys:
+    - minimaxm3-fp8-h200-vllm-agentic-mtp
+  scenario-type:
+    - agentic-coding
+  description:
+    - "Add MiniMax-M3 MXFP8 AgentX on H200 with vLLM v0.27.1, EAGLE3 golden AL 2.78, resident TP8 c1/c2/c4/c6/c8/c10, and Mooncake DRAM offload c12/c14."
+  pr-link: https://github.com/SemiAnalysisAI/InferenceX/pull/2565