diff --git a/benchmark_chart.py b/benchmark_chart.py
new file mode 100644
index 0000000..cf2843e
--- /dev/null
+++ b/benchmark_chart.py
@@ -0,0 +1,289 @@
+#!/usr/bin/env python3
+"""
+AI 模型基准测试对比图生成器
+
+用法：
+    python benchmark_chart.py -c data.py -o output.png
+    python benchmark_chart.py -c data.py -o output.png --dpi 150
+    python benchmark_chart.py -c data.yaml -o result.png --width 28 --height 18
+
+数据文件格式（支持 .py / .json / .yaml）：
+
+    TITLE = "总标题"
+    COLORS = {"qwen36": "#5B2D8E", ...}
+    BENCHMARKS = [
+        {
+            "title": "Benchmark Name",
+            "subtitle": "简短描述",
+            "models": [
+                {"name": "全名", "short_label": "短标", "group": "moe|dense", "score": 85.0, "color_key": "qwen36"},
+                ...
+            ],
+        },
+        ...
+    ]
+"""
+
+import argparse
+import json
+import sys
+from pathlib import Path
+from typing import Any
+
+import matplotlib
+import matplotlib.pyplot as plt
+import matplotlib.ticker as mticker
+import numpy as np
+
+matplotlib.use("Agg")
+
+# ────────────────────── 默认值 ──────────────────────
+DEFAULT_COLORS = {
+    "qwen36": "#5B2D8E",
+    "qwen35": "#8B5CF6",
+    "gemma26": "#06B6D4",
+    "qwen27": "#B0B5BD",
+    "gemma31": "#34D399",
+}
+DEFAULT_BG = "#E8F5E9"
+DEFAULT_BAR_WIDTH = 0.55
+DEFAULT_DPI = 200
+DEFAULT_FIGSIZE = (24, 16)
+GROUP_GAP = 1.2  # MoE 和 Dense 组间距
+
+
+def load_data(source: str) -> dict:
+    p = Path(source)
+    if p.suffix == ".py":
+        sys.path.insert(0, str(p.parent))
+        ns: dict[str, Any] = {}
+        exec(p.read_text(encoding="utf-8"), ns)
+        return ns
+    elif p.suffix == ".json":
+        return json.loads(p.read_text(encoding="utf-8"))
+    elif p.suffix in (".yaml", ".yml"):
+        try:
+            import yaml
+        except ImportError:
+            raise ImportError("需要 PyYAML: pip install pyyaml")
+        return yaml.safe_load(p.read_text(encoding="utf-8"))
+    else:
+        raise ValueError(f"不支持的文件格式: {p.suffix}")
+
+
+def draw_chart(ax: plt.Axes, benchmark: dict, colors: dict, bar_width: float):
+    """在单个 Axes 上绘制一个基准测试的柱状图"""
+    title = benchmark.get("title", "")
+    subtitle = benchmark.get("subtitle", "")
+    models = benchmark.get("models", [])
+
+    moe_models = [m for m in models if m.get("group", "").lower() == "moe"]
+    dense_models = [m for m in models if m.get("group", "").lower() == "dense"]
+    n_moe = len(moe_models)
+    n_dense = len(dense_models)
+
+    # ── X 坐标 ──
+    moe_x = np.arange(n_moe) - (n_moe - 1) / 2 if n_moe else np.array([])
+    dense_start = (n_moe - 1) / 2 + GROUP_GAP + bar_width / 2 if n_moe else 0
+    dense_x = (np.arange(n_dense) + dense_start) if n_dense else np.array([])
+    sep_x = (moe_x[-1] + dense_x[0]) / 2 if n_moe > 0 and n_dense > 0 else None
+
+    # ── 画柱子 ──
+    all_scores: list[float] = []
+    for i, m in enumerate(moe_models):
+        score = float(m.get("score", 0))
+        all_scores.append(score)
+        ck = m.get("color_key", "")
+        color = colors.get(ck, "#999")
+        ax.bar(moe_x[i], score, bar_width, color=color,
+               edgecolor="white", linewidth=0.5, zorder=3)
+    for i, m in enumerate(dense_models):
+        score = float(m.get("score", 0))
+        all_scores.append(score)
+        ck = m.get("color_key", "")
+        color = colors.get(ck, "#999")
+        ax.bar(dense_x[i], score, bar_width, color=color,
+               edgecolor="white", linewidth=0.5, zorder=3)
+
+    if not all_scores:
+        return
+
+    y_max = max(all_scores)
+    y_pad = y_max * 0.32  # 上方留白给分数标注 + 分组标签
+    label_reserve = y_max * 0.22  # 底部留给 x 轴标签的空间
+
+    # ═══ X 轴标签：模型短名 ═══
+    label_fs = 7.5 if n_moe + n_dense > 4 else 8.5
+    name_y = -label_reserve * 0.4
+
+    for i, m in enumerate(moe_models):
+        lbl = m.get("short_label", m.get("name", ""))
+        ax.text(moe_x[i], name_y, lbl, ha="center", va="top",
+                fontsize=label_fs, color="#555", linespacing=1.0)
+    for i, m in enumerate(dense_models):
+        lbl = m.get("short_label", m.get("name", ""))
+        ax.text(dense_x[i], name_y, lbl, ha="center", va="top",
+                fontsize=label_fs, color="#555", linespacing=1.0)
+
+    # ═══ MoE / Dense 分组标签：放在柱子组上方 ═══
+    if n_moe > 0:
+        ax.text(moe_x.mean(), y_max + y_pad * 0.55, "MoE",
+                ha="center", va="center",
+                fontsize=8.5, fontweight="bold", color="#888",
+                bbox=dict(boxstyle="round,pad=0.3", fc="white", ec="#ddd", alpha=0.85))
+    if n_dense > 0:
+        ax.text(dense_x.mean(), y_max + y_pad * 0.55, "Dense",
+                ha="center", va="center",
+                fontsize=8.5, fontweight="bold", color="#888",
+                bbox=dict(boxstyle="round,pad=0.3", fc="white", ec="#ddd", alpha=0.85))
+
+    # ── 虚线分隔 ──
+    if sep_x is not None:
+        ax.axvline(x=sep_x, ymin=0.04, ymax=0.92, color="#ccc",
+                   linestyle=":", linewidth=1.2, zorder=2)
+
+    # ── 最高分标注 ──
+    top_score = max(all_scores)
+    for i, m in enumerate(moe_models):
+        if m.get("score", 0) == top_score:
+            ax.annotate(
+                f"{top_score}",
+                xy=(moe_x[i], top_score),
+                xytext=(0, 5), textcoords="offset points",
+                ha="center", va="bottom",
+                fontsize=11, fontweight="bold", color="#222",
+            )
+            break
+    else:
+        for i, m in enumerate(dense_models):
+            if m.get("score", 0) == top_score:
+                ax.annotate(
+                    f"{top_score}",
+                    xy=(dense_x[i], top_score),
+                    xytext=(0, 5), textcoords="offset points",
+                    ha="center", va="bottom",
+                    fontsize=11, fontweight="bold", color="#222",
+                )
+                break
+
+    # ═══ 标题 + 副标题（放在上方，无重叠） ═══
+    # 标题：左上角，加粗
+    ax.text(0.0, 1.02, title, transform=ax.transAxes,
+            fontsize=12, fontweight="bold", color="#222",
+            ha="left", va="bottom")
+    if subtitle:
+        # 副标题：标题下方
+        ax.text(0.0, 0.94, subtitle, transform=ax.transAxes,
+                fontsize=7.5, color="#aaa", ha="left", va="top",
+                fontstyle="italic")
+
+    # ── 美化 ──
+    ax.set_facecolor("white")
+    for spine in ("top", "right", "left"):
+        ax.spines[spine].set_visible(False)
+    ax.spines["bottom"].set_color("#ddd")
+    ax.tick_params(axis="x", bottom=False, labelbottom=False)
+    ax.tick_params(axis="y", labelsize=6.5, colors="#aaa", length=0)
+    ax.yaxis.set_major_locator(mticker.MaxNLocator(4, integer=True))
+    ax.grid(axis="y", color="#f0f0f0", linewidth=0.5, zorder=0)
+
+    # ── 坐标范围 ──
+    all_x = list(moe_x) + list(dense_x)
+    x_pad = bar_width * 1.8
+    ax.set_xlim(min(all_x) - x_pad, max(all_x) + x_pad)
+    ax.set_ylim(-label_reserve, y_max + y_pad)
+
+
+def make_chart(
+    data_source: str,
+    output_path: str,
+    dpi: int = DEFAULT_DPI,
+    figsize: tuple = DEFAULT_FIGSIZE,
+):
+    data = load_data(data_source)
+    benchmarks = data.get("benchmarks", data.get("BENCHMARKS", []))
+    colors = data.get("colors", data.get("COLORS", DEFAULT_COLORS))
+    bg_color = data.get("bg_color", data.get("BG_COLOR", DEFAULT_BG))
+    bar_width = data.get("bar_width", data.get("BAR_WIDTH", DEFAULT_BAR_WIDTH))
+    title = data.get("title", data.get("TITLE", ""))
+    ncols = data.get("ncols", data.get("NCOLS", 4))
+
+    n = len(benchmarks)
+    if n == 0:
+        print("❌ 没有找到 benchmarks 数据")
+        sys.exit(1)
+
+    nrows = (n + ncols - 1) // ncols
+
+    fig, axes = plt.subplots(
+        nrows, ncols, figsize=figsize,
+        facecolor=bg_color,
+    )
+    fig.subplots_adjust(
+        hspace=0.55, wspace=0.35,
+        top=0.93, bottom=0.09, left=0.04, right=0.96,
+    )
+
+    # 统一 axes 数组
+    axes_flat = np.array(axes).flatten()
+
+    if title:
+        fig.suptitle(title, fontsize=16, fontweight="bold", color="#222", y=0.97)
+
+    for i, bench in enumerate(benchmarks):
+        draw_chart(axes_flat[i], bench, colors, bar_width)
+
+    for j in range(i + 1, len(axes_flat)):
+        axes_flat[j].set_visible(False)
+
+    # ── 底部图例 ──
+    seen: dict[str, dict] = {}
+    for bench in benchmarks:
+        for m in bench.get("models", []):
+            name = m.get("name", "")
+            if name not in seen:
+                seen[name] = m
+
+    if seen:
+        handles = []
+        labels = []
+        for name, m in seen.items():
+            ck = m.get("color_key", "")
+            color = colors.get(ck, "#999")
+            handles.append(plt.Rectangle((0, 0), 1, 1, fc=color, ec="white", lw=0.5))
+            labels.append(name)
+        fig.legend(
+            handles, labels, loc="lower center",
+            ncol=min(len(seen), 5), frameon=False,
+            fontsize=8,
+            bbox_to_anchor=(0.5, 0.005),
+        )
+
+    fig.savefig(output_path, dpi=dpi, bbox_inches="tight", facecolor=bg_color)
+    print(f"✅ 图表已保存到 {output_path}")
+    return output_path
+
+
+def main():
+    parser = argparse.ArgumentParser(description="AI Benchmark 对比图生成器")
+    parser.add_argument("-c", "--config", required=True,
+                        help="数据配置文件 (.py / .json / .yaml)")
+    parser.add_argument("-o", "--output", default="benchmark_chart.png",
+                        help="输出图片路径")
+    parser.add_argument("--dpi", type=int, default=DEFAULT_DPI,
+                        help=f"分辨率 (默认: {DEFAULT_DPI})")
+    parser.add_argument("--width", type=float, default=DEFAULT_FIGSIZE[0],
+                        help="图宽 (英寸)")
+    parser.add_argument("--height", type=float, default=DEFAULT_FIGSIZE[1],
+                        help="图高 (英寸)")
+    args = parser.parse_args()
+    make_chart(
+        data_source=args.config,
+        output_path=args.output,
+        dpi=args.dpi,
+        figsize=(args.width, args.height),
+    )
+
+
+if __name__ == "__main__":
+    main()