fix(azure_ai): price FLUX.2-flex pixels per 1024x1024 megapixel

The Flex row stored 0.05 / 1,000,000 per pixel, so a 1024x1024 image billed
0.0524288 instead of 0.05. Azure and Black Forest Labs define one megapixel as
1,048,576 pixels, so the rate is 0.05 / 1048576, exact in float64. Tests that
pinned the old literal now derive the rate from the catalog and assert the
invariant our code owns: one 1024x1024 image prices at exactly one megapixel

litellm/model_prices_and_context_window_backup.json

@@ -10963,7 +10963,7 @@
         ]
     },
     "azure_ai/FLUX.2-flex": {
-        "input_cost_per_pixel": 5e-08,
+        "input_cost_per_pixel": 4.76837158203125e-08,
         "litellm_provider": "azure_ai",
         "max_input_tokens": 32000,
         "max_tokens": 32000,

model_prices_and_context_window.json

@@ -10963,7 +10963,7 @@
         ]
     },
     "azure_ai/FLUX.2-flex": {
-        "input_cost_per_pixel": 5e-08,
+        "input_cost_per_pixel": 4.76837158203125e-08,
         "litellm_provider": "azure_ai",
         "max_input_tokens": 32000,
         "max_tokens": 32000,

tests/test_litellm/llms/azure_ai/image_generation/test_azure_ai_flux2_image_generation.py

@@ -28,6 +28,10 @@ def use_local_model_cost_map(monkeypatch):
     _invalidate_model_cost_lowercase_map()
 
 
+def _flex_pixel_rate() -> float:
+    return litellm.model_cost["azure_ai/FLUX.2-flex"]["input_cost_per_pixel"]
+
+
 @pytest.mark.parametrize(
     ("model", "provider_path"),
     [
@@ -127,7 +131,7 @@ def test_flux2_flex_model_info():
     assert model_info["max_input_tokens"] == 32000
     assert model_info["max_tokens"] == 32000
     assert model_info["supported_endpoints"] == ["/v1/images/generations", "/v1/images/edits"]
-    assert catalog_info["input_cost_per_pixel"] == 5e-08
+    assert catalog_info["input_cost_per_pixel"] * 1024 * 1024 == pytest.approx(0.05)
     assert catalog_info["supported_modalities"] == ["text", "image"]
     assert catalog_info["supported_output_modalities"] == ["image"]
 
@@ -148,7 +152,7 @@ def test_flux2_flex_cost_uses_generated_megapixels():
         call_type="image_generation",
     )
 
-    assert cost == pytest.approx(5e-08 * 2048 * 1024 * 2)
+    assert cost == pytest.approx(_flex_pixel_rate() * 2048 * 1024 * 2)
 
 
 @pytest.mark.parametrize("model", ("FLUX-1.1-pro", "FLUX.1-Kontext-pro"))
@@ -189,7 +193,7 @@ def test_flux2_cost_uses_mapped_dimensions_after_response_transformation(dimensi
         completion_response=response,
         optional_params=params,
         call_type="image_generation",
-    ) == pytest.approx(5e-08 * 2048 * 1024 * 2)
+    ) == pytest.approx(_flex_pixel_rate() * 2048 * 1024 * 2)
 
 
 def test_flux2_flex_cost_accepts_lowercase_model_spelling():
@@ -202,7 +206,7 @@ def test_flux2_flex_cost_accepts_lowercase_model_spelling():
         call_type="image_generation",
     )
 
-    assert cost == pytest.approx(5e-08 * 1536 * 1024 * 2)
+    assert cost == pytest.approx(_flex_pixel_rate() * 1536 * 1024 * 2)
 
 
 def test_flux2_flex_cost_prefers_deployment_input_cost_per_pixel() -> None:

tests/unit/llms/azure_ai/image_edit/test_azure_ai_image_edit_transformation.py

@@ -144,7 +144,9 @@ def test_flux2_image_edit_rejects_too_many_references(model: str, reference_imag
         )
 
 
-@pytest.mark.parametrize("dimensions", ({"size": "2048x1024"}, {"width": 2048, "height": 1024}, {"width": "2048", "height": "1024"}))
+@pytest.mark.parametrize(
+    "dimensions", ({"size": "2048x1024"}, {"width": 2048, "height": 1024}, {"width": "2048", "height": "1024"})
+)
 @pytest.mark.usefixtures("local_model_cost_map")
 def test_flux2_image_edit_preserves_controls_and_pixel_cost(dimensions: Mapping[str, int | str]):
     def respond(request: httpx.Request) -> httpx.Response:
@@ -175,7 +177,9 @@ def test_flux2_image_edit_preserves_controls_and_pixel_cost(dimensions: Mapping[
         **dimensions,
     )
 
-    assert response._hidden_params["response_cost"] == pytest.approx(5e-08 * 2048 * 1024 * 2)
+    assert response._hidden_params["response_cost"] == pytest.approx(
+        litellm.model_cost["azure_ai/FLUX.2-flex"]["input_cost_per_pixel"] * 2048 * 1024 * 2
+    )
 
 
 def test_flux2_image_edit_accepts_and_drops_openai_only_parameters():