diff --git a/mlx/backend/cuda/conv.cpp b/mlx/backend/cuda/conv.cpp
index 53ef6d06c..578b520a0 100644
--- a/mlx/backend/cuda/conv.cpp
+++ b/mlx/backend/cuda/conv.cpp
@@ -150,11 +150,8 @@ cudnn_frontend::EngineConfigList get_engine_configs(
             CUDNN_NUMERICAL_NOTE_DOWN_CONVERT_INPUTS>(c)) {
       return true;
     }
-    // In PyTorch, tf32 seems to be always turned off for convolution even with
-    // "torch.backends.cudnn.allow_tf32 = True", so we are disabling tf32 too to
-    // keep results same.
-    if (dtype == float32 &&
-        cudnn_frontend::hasNumericalNote<CUDNN_NUMERICAL_NOTE_TENSOR_CORE>(c)) {
+    if (cudnn_frontend::hasNumericalNote<CUDNN_NUMERICAL_NOTE_TENSOR_CORE>(c) &&
+        dtype == float32 && !env::enable_tf32()) {
       return true;
     }
     return false;
@@ -286,8 +283,7 @@ void Convolution::eval_gpu(const std::vector<array>& inputs, array& out) {
       get_alignment(in),
       get_alignment(wt),
       get_alignment(out)};
-  auto it = conv_cache().find(cache_key);
-  if (it != conv_cache().end()) {
+  if (auto it = conv_cache().find(cache_key); it != conv_cache().end()) {
     if (!execute_plan(encoder, it->second, in, wt, out)) {
       throw std::runtime_error("Cached convolution plan failed to execute.");
     }