diff --git a/tests/benchmark.py b/tests/benchmark.py
index 647afd5..804500f 100644
--- a/tests/benchmark.py
+++ b/tests/benchmark.py
@@ -117,7 +117,6 @@ def cp_vs_python_sparse(path: str = 'benchmark_results_001_sparse.json'):
             results.append({'benchmark': 'Copapy', 'iter_size': iter_size, 'elapsed_time': elapsed_cp, 'sum_size': sum_size, 'v_size': v_size})
 
 
-
             v1 = cp.vector(float(v) for v in range(v_size))
             v2 = cp.vector(float(v) for v in [5]*v_size)
 
@@ -158,6 +157,7 @@ def plot_results(path: str):
     import matplotlib.pyplot as plt
     import numpy as np
     from collections import defaultdict
+    import matplotlib as mpl
 
     # Load the benchmark results
     with open(path, 'r') as f:
@@ -185,30 +185,97 @@ def plot_results(path: str):
     v_sizes_set = sorted(set(v for benchmark_data in medians_by_benchmark.values() for v in benchmark_data.keys()))
 
     # Create the plot
-    plt.figure(figsize=(10, 6))
+    plt.figure(figsize=(6, 4))
 
     for benchmark in benchmarks:
         if benchmark != 'Python':
             v_sizes = sorted(medians_by_benchmark[benchmark].keys())
             elapsed_times = [medians_by_benchmark[benchmark][v] for v in v_sizes]
-            plt.plot(v_sizes, elapsed_times, '.', label=benchmark)
+            plt.plot(v_sizes, elapsed_times, '.', label=benchmark, markersize=10)
 
     plt.xlabel('Vector Size (v_size)')
     plt.ylabel('Elapsed Time (seconds)')
     #plt.title('Benchmark Results: Elapsed Time vs Vector Size')
-    plt.legend()
+    plt.legend(frameon=False)
     #plt.grid(True, alpha=0.3)
     plt.ylim(bottom=0)
     plt.tight_layout()
 
     # Save to PNG
-    plt.savefig(path.replace('.json', '') + '.png', dpi=300)
+    mpl.rcParams['svg.fonttype'] = 'none'
+    save_svg_with_theme_styles(plt, path.replace('.json', '') + '.svg')
     print("Plot saved")
 
 
+def save_svg_with_theme_styles(pyplot_obj, path):
+    import io
+    import re
+    """
+    Takes a pyplot object (typically `plt`) or a figure, captures its SVG output,
+    injects theme-based CSS, and writes to disk.
+    """
+
+    # --- Step 1: Capture SVG to memory ---
+    buf = io.StringIO()
+    
+    # pyplot_obj can be a module (plt) or a Figure instance
+    if hasattr(pyplot_obj, "gcf"):
+        fig = pyplot_obj.gcf()
+    else:
+        fig = pyplot_obj
+
+    fig.savefig(buf, format="svg", dpi=150, transparent=True)
+    svg_data = buf.getvalue()
+    buf.close()
+
+    # --- Step 2: Theme CSS to inject ---
+    theme_css = """
+    <style type="text/css">
+    @media (prefers-color-scheme: dark) {
+        path {
+            stroke: #EEEEEE !important;
+        }
+        text {
+            fill: #EEEEEE !important;
+        }
+        #patch_1 path {
+            fill: #444444 !important;
+        }
+    }
+    @media (prefers-color-scheme: light) {
+        path {
+            stroke: #444444 !important;
+        }
+        text {
+            fill: #444444 !important;
+        }
+        #patch_1 path {
+            fill: #FFFFFF !important;
+        }
+    }
+    #patch_1 path {
+        stroke: none !important;
+    }
+    </style>
+    """
+
+    # --- Step 3: Inject CSS right after <svg ...> tag ---
+    # Find the first > after the <svg ...> opening tag
+    modified_svg = re.sub(
+        r"(<svg[^>]*>)",
+        r"\1\n" + theme_css,
+        svg_data,
+        count=1
+    )
+
+    # --- Step 4: Write final output to disk ---
+    with open(path, "w", encoding="utf-8") as f:
+        f.write(modified_svg)
+
+
 if __name__ == "__main__":
-    path1 = 'benchmark_results_001.json'
-    path2 = 'benchmark_results_001_sparse.json'
+    path1 = 'docs/source/media/benchmark_results_001.json'
+    path2 = 'docs/source/media/benchmark_results_001_sparse.json'
 
     if 'no_simd' in sys.argv[1:]:
         os.environ["NPY_DISABLE_CPU_FEATURES"] = CPU_SIMD_FEATURES