diff --git a/examples/images/cifar10/compute_fid.py b/examples/images/cifar10/compute_fid.py
index 52ffbb4..2f79554 100644
--- a/examples/images/cifar10/compute_fid.py
+++ b/examples/images/cifar10/compute_fid.py
@@ -27,6 +27,8 @@
 flags.DEFINE_integer("step", 400000, help="training steps")
 flags.DEFINE_integer("num_gen", 50000, help="number of samples to generate")
 flags.DEFINE_float("tol", 1e-5, help="Integrator tolerance (absolute and relative)")
+flags.DEFINE_float("batch_size_fid", 1024, help="Batch size to compute FID")
+
 FLAGS(sys.argv)
 
 
@@ -70,7 +72,7 @@
 
 def gen_1_img(unused_latent):
     with torch.no_grad():
-        x = torch.randn(500, 3, 32, 32, device=device)
+        x = torch.randn(FLAGS.batch_size_fid, 3, 32, 32, device=device)
         if FLAGS.integration_method == "euler":
             print("Use method: ", FLAGS.integration_method)
             t_span = torch.linspace(0, 1, FLAGS.integration_steps + 1, device=device)
@@ -90,7 +92,7 @@ def gen_1_img(unused_latent):
 score = fid.compute_fid(
     gen=gen_1_img,
     dataset_name="cifar10",
-    batch_size=500,
+    batch_size=FLAGS.batch_size_fid,
     dataset_res=32,
     num_gen=FLAGS.num_gen,
     dataset_split="train",