diff --git a/src/plugins/intel_gpu/src/kernel_selector/kernels/convolution/convolution_kernel_ref.cpp b/src/plugins/intel_gpu/src/kernel_selector/kernels/convolution/convolution_kernel_ref.cpp
index 7ddc42b6c152b0..776ef796ab92b5 100644
--- a/src/plugins/intel_gpu/src/kernel_selector/kernels/convolution/convolution_kernel_ref.cpp
+++ b/src/plugins/intel_gpu/src/kernel_selector/kernels/convolution/convolution_kernel_ref.cpp
@@ -123,7 +123,8 @@ bool ConvolutionKernel_Ref::Validate(const Params& params) const {
 
     // int8/uint8 inputs (quantization case) require additional checks
     // require some additional checks.
-    if (input_type == output_type && input_type != Datatype::UINT8 && input_type != Datatype::INT8)
+    if (input_type != Datatype::UINT8 && input_type != Datatype::INT8 &&
+        output_type != Datatype::UINT8 && output_type != Datatype::INT8)
         return true;
 
     // (u)int8 input + fp weights
diff --git a/src/plugins/intel_gpu/tests/unit/test_cases/convolution_gpu_test.cpp b/src/plugins/intel_gpu/tests/unit/test_cases/convolution_gpu_test.cpp
index ce07bffe3666f3..5939e8066b9537 100644
--- a/src/plugins/intel_gpu/tests/unit/test_cases/convolution_gpu_test.cpp
+++ b/src/plugins/intel_gpu/tests/unit/test_cases/convolution_gpu_test.cpp
@@ -12,6 +12,7 @@
 #include <intel_gpu/primitives/crop.hpp>
 #include <intel_gpu/primitives/reorder.hpp>
 #include <intel_gpu/primitives/reshape.hpp>
+#include <intel_gpu/primitives/permute.hpp>
 
 #include <algorithm>
 #include <array>
@@ -1639,6 +1640,47 @@ TEST(convolution_f32_fw_gpu, basic_convolution) {
     }
 }
 
+TEST(convolution_f32_fw_gpu, input_f32_output_f16_dynamic_ref_kernel) {
+    auto& engine = get_test_engine();
+
+    auto in_layout = layout{ov::PartialShape::dynamic(4), data_types::f32, format::bfyx};
+    auto input = engine.allocate_memory({ data_types::f32, format::bfyx, { 1, 1, 5, 4 } });
+    auto weights = engine.allocate_memory({ data_types::i8, format::bfyx, { 1, 1, 3, 2 } });
+    auto biases = engine.allocate_memory({ data_types::f32, format::bfyx, { 1, 1, 1, 1 } });
+    auto eltwise_data = engine.allocate_memory({ data_types::f32, format::bfyx, { 1, 1, 1, 1 } });
+
+    set_values(input, {
+        1.0f, 2.0f, 3.0f, 4.0f,
+        5.0f, 2.0f, 2.0f, 3.0f,
+        4.0f, 6.0f, 3.0f, 3.0f,
+        3.0f, 5.0f, 1.0f, 1.0f,
+        1.0f, 1.0f, 1.0f, 1.0f }
+    );
+
+    topology topology(
+        input_layout("input", in_layout),
+        data("weights", weights),
+        data("biases", biases),
+        data("eltwise_data", eltwise_data),
+        convolution( "conv", input_info("input"), "weights", "biases", 1, {2, 1}, {1, 1}, {0, 0}, {0, 0}, false),
+        eltwise("eltwise", { input_info("conv"), input_info("eltwise_data") }, eltwise_mode::prod, data_types::f16),
+        permute("permute", input_info("eltwise"), {0, 1, 2, 3}));
+
+    ExecutionConfig config = get_test_default_config(engine);
+    ov::intel_gpu::ImplementationDesc conv_impl_ref = { format::bfyx, "convolution_gpu_ref", impl_types::ocl };
+    config.set_property(ov::intel_gpu::force_implementations(ov::intel_gpu::ImplForcingMap{ { "conv", conv_impl_ref } }));
+    config.set_property(ov::intel_gpu::allow_new_shape_infer(true));
+
+    network network(engine, topology, config);
+    network.set_input_data("input", input);
+
+    auto outputs = network.execute();
+
+    ASSERT_EQ(outputs.size(), size_t(1));
+    ASSERT_FALSE(has_node(*network.get_program(), "eltwise"));
+    ASSERT_EQ(outputs.at("permute").get_layout().data_type, data_types::f16);
+}
+
 TEST(convolution_f32_fw_gpu, convolution_big_size_weights) {
     auto& engine = get_test_engine();