diff --git a/src/cpp/src/image_generation/flux_pipeline.hpp b/src/cpp/src/image_generation/flux_pipeline.hpp
index 547efa4415..bcff7ba141 100644
--- a/src/cpp/src/image_generation/flux_pipeline.hpp
+++ b/src/cpp/src/image_generation/flux_pipeline.hpp
@@ -351,6 +351,14 @@ class FluxPipeline : public DiffusionPipeline {
         m_custom_generation_config = m_generation_config;
         m_custom_generation_config.update_generation_config(properties);
 
+        const size_t vae_scale_factor = m_vae->get_vae_scale_factor();
+        const auto& transformer_config = m_transformer->get_config();
+
+        if (m_custom_generation_config.height == -1)
+            m_custom_generation_config.height = transformer_config.m_default_sample_size * vae_scale_factor;
+        if (m_custom_generation_config.width == -1)
+            m_custom_generation_config.width = transformer_config.m_default_sample_size * vae_scale_factor;
+
         // Use callback if defined
         std::function<bool(size_t, size_t, ov::Tensor&)> callback = nullptr;
         auto callback_iter = properties.find(ov::genai::callback.name());
@@ -358,9 +366,6 @@ class FluxPipeline : public DiffusionPipeline {
             callback = callback_iter->second.as<std::function<bool(size_t, size_t, ov::Tensor&)>>();
         }
 
-        const size_t vae_scale_factor = m_vae->get_vae_scale_factor();
-        const auto& transformer_config = m_transformer->get_config();
-
         if (m_custom_generation_config.height < 0)
             compute_dim(m_custom_generation_config.height, initial_image, 1 /* assume NHWC */);
         if (m_custom_generation_config.width < 0)
@@ -460,8 +465,6 @@ class FluxPipeline : public DiffusionPipeline {
                 m_generation_config.guidance_scale = 7.0f;
                 m_generation_config.num_inference_steps = 28;
                 m_generation_config.strength = 0.6f;
-                m_generation_config.height = 1024;
-                m_generation_config.width = 1024;
             }
             m_generation_config.max_sequence_length = 512;
         } else {
diff --git a/src/python/py_image_generation_pipelines.cpp b/src/python/py_image_generation_pipelines.cpp
index b011aee878..dcc50234ed 100644
--- a/src/python/py_image_generation_pipelines.cpp
+++ b/src/python/py_image_generation_pipelines.cpp
@@ -330,6 +330,7 @@ void init_image_generation_pipelines(py::module_& m) {
         .def_static("stable_diffusion", &ov::genai::Image2ImagePipeline::stable_diffusion, py::arg("scheduler"), py::arg("clip_text_model"), py::arg("unet"), py::arg("vae"))
         .def_static("latent_consistency_model", &ov::genai::Image2ImagePipeline::latent_consistency_model, py::arg("scheduler"), py::arg("clip_text_model"), py::arg("unet"), py::arg("vae"))
         .def_static("stable_diffusion_xl", &ov::genai::Image2ImagePipeline::stable_diffusion_xl, py::arg("scheduler"), py::arg("clip_text_model"), py::arg("clip_text_model_with_projection"), py::arg("unet"), py::arg("vae"))
+        .def_static("flux", &ov::genai::Image2ImagePipeline::flux, py::arg("scheduler"), py::arg("clip_text_model"), py::arg("t5_encoder_model"), py::arg("transformer"), py::arg("vae"))
         .def(
             "compile",
             [](ov::genai::Image2ImagePipeline& pipe,
diff --git a/tools/who_what_benchmark/tests/test_cli_image.py b/tools/who_what_benchmark/tests/test_cli_image.py
index 1ad8236058..ec36de8efa 100644
--- a/tools/who_what_benchmark/tests/test_cli_image.py
+++ b/tools/who_what_benchmark/tests/test_cli_image.py
@@ -103,8 +103,8 @@ def test_image_model_types(model_id, model_type, backend):
                             ])),
 )
 def test_image_model_genai(model_id, model_type):
-    if ("flux" in model_id or "stable-diffusion-3" in model_id) and model_type != "text-to-image":
-        pytest.skip(reason="FLUX or SD3 are supported as text to image only")
+    if ("stable-diffusion-3" in model_id) and model_type != "text-to-image":
+        pytest.skip(reason="SD3 is supported as text to image only")
 
     with tempfile.TemporaryDirectory() as temp_dir:
         GT_FILE = os.path.join(temp_dir, "gt.csv")