diff --git a/py/routes/handlers/recipe_handlers.py b/py/routes/handlers/recipe_handlers.py
index b36ade5d..cee3ad0c 100644
--- a/py/routes/handlers/recipe_handlers.py
+++ b/py/routes/handlers/recipe_handlers.py
@@ -22,6 +22,7 @@ from ...services.recipes import (
     RecipeSharingService,
     RecipeValidationError,
 )
+from ...services.metadata_service import get_default_metadata_provider
 
 Logger = logging.Logger
 EnsureDependenciesCallable = Callable[[], Awaitable[None]]
@@ -451,7 +452,6 @@ class RecipeManagementHandler:
                 raise RuntimeError("Recipe scanner unavailable")
 
             params = request.rel_url.query
-            print(params)
             image_url = params.get("image_url")
             name = params.get("name")
             resources_raw = params.get("resources")
@@ -478,6 +478,9 @@ class RecipeManagementHandler:
                 gen_params_ref = metadata.setdefault("gen_params", {})
                 if "checkpoint" not in gen_params_ref:
                     gen_params_ref["checkpoint"] = checkpoint_entry
+                base_model_from_metadata = await self._resolve_base_model_from_checkpoint(checkpoint_entry)
+                if base_model_from_metadata:
+                    metadata["base_model"] = base_model_from_metadata
 
             tags = self._parse_tags(params.get("tags"))
             image_bytes = await self._download_image_bytes(image_url)
@@ -769,6 +772,29 @@ class RecipeManagementHandler:
         except (TypeError, ValueError):
             return 0
 
+    async def _resolve_base_model_from_checkpoint(self, checkpoint_entry: Dict[str, Any]) -> str:
+        version_id = self._safe_int(checkpoint_entry.get("modelVersionId"))
+
+        if not version_id:
+            return ""
+
+        try:
+            provider = await get_default_metadata_provider()
+            if not provider:
+                return ""
+
+            version_info = await provider.get_model_version_info(version_id)
+            if isinstance(version_info, tuple):
+                version_info = version_info[0]
+
+            if isinstance(version_info, dict):
+                base_model = version_info.get("baseModel") or ""
+                return str(base_model) if base_model is not None else ""
+        except Exception as exc:  # pragma: no cover - defensive logging
+            self._logger.warning("Failed to resolve base model from checkpoint metadata: %s", exc)
+
+        return ""
+
 
 class RecipeAnalysisHandler:
     """Analyze images to extract recipe metadata."""
diff --git a/tests/routes/test_recipe_routes.py b/tests/routes/test_recipe_routes.py
index 93e3578d..93d66300 100644
--- a/tests/routes/test_recipe_routes.py
+++ b/tests/routes/test_recipe_routes.py
@@ -13,6 +13,7 @@ from aiohttp.test_utils import TestClient, TestServer
 
 from py.config import config
 from py.routes import base_recipe_routes
+from py.routes.handlers import recipe_handlers
 from py.routes.recipe_routes import RecipeRoutes
 from py.services.recipes import RecipeValidationError
 from py.services.service_registry import ServiceRegistry
@@ -296,6 +297,18 @@ async def test_save_and_delete_recipe_round_trip(monkeypatch, tmp_path: Path) ->
 
 
 async def test_import_remote_recipe(monkeypatch, tmp_path: Path) -> None:
+    provider_calls: list[int] = []
+
+    class Provider:
+        async def get_model_version_info(self, model_version_id):
+            provider_calls.append(model_version_id)
+            return {"baseModel": "Flux Provider"}, None
+
+    async def fake_get_default_metadata_provider():
+        return Provider()
+
+    monkeypatch.setattr(recipe_handlers, "get_default_metadata_provider", fake_get_default_metadata_provider)
+
     async with recipe_harness(monkeypatch, tmp_path) as harness:
         resources = [
             {
@@ -335,7 +348,8 @@ async def test_import_remote_recipe(monkeypatch, tmp_path: Path) -> None:
         assert call["name"] == "Remote Recipe"
         assert call["tags"] == ["foo", "bar"]
         metadata = call["metadata"]
-        assert metadata["base_model"] == "Flux"
+        assert metadata["base_model"] == "Flux Provider"
+        assert provider_calls == [33]
         assert metadata["checkpoint"]["modelVersionId"] == 33
         assert metadata["loras"][0]["weight"] == 0.25
         assert metadata["gen_params"]["prompt"] == "hello world"
@@ -343,6 +357,49 @@ async def test_import_remote_recipe(monkeypatch, tmp_path: Path) -> None:
         assert harness.downloader.urls == ["https://example.com/images/1"]
 
 
+async def test_import_remote_recipe_falls_back_to_request_base_model(monkeypatch, tmp_path: Path) -> None:
+    provider_calls: list[int] = []
+
+    class Provider:
+        async def get_model_version_info(self, model_version_id):
+            provider_calls.append(model_version_id)
+            return {}, None
+
+    async def fake_get_default_metadata_provider():
+        return Provider()
+
+    monkeypatch.setattr(recipe_handlers, "get_default_metadata_provider", fake_get_default_metadata_provider)
+
+    async with recipe_harness(monkeypatch, tmp_path) as harness:
+        resources = [
+            {
+                "type": "checkpoint",
+                "modelId": 11,
+                "modelVersionId": 77,
+                "modelName": "Flux",
+                "modelVersionName": "Dev",
+            },
+        ]
+        response = await harness.client.get(
+            "/api/lm/recipes/import-remote",
+            params={
+                "image_url": "https://example.com/images/1",
+                "name": "Remote Recipe",
+                "resources": json.dumps(resources),
+                "tags": "foo,bar",
+                "base_model": "Flux",
+            },
+        )
+
+        payload = await response.json()
+        assert response.status == 200
+        assert payload["success"] is True
+
+        metadata = harness.persistence.save_calls[-1]["metadata"]
+        assert metadata["base_model"] == "Flux"
+        assert provider_calls == [77]
+
+
 async def test_analyze_uploaded_image_error_path(monkeypatch, tmp_path: Path) -> None:
     async with recipe_harness(monkeypatch, tmp_path) as harness:
         harness.analysis.raise_for_uploaded = RecipeValidationError("No image data provided")