diff --git a/studio/backend/core/training/trainer.py b/studio/backend/core/training/trainer.py
index 0aa6d0922e..bc252d1fa5 100644
--- a/studio/backend/core/training/trainer.py
+++ b/studio/backend/core/training/trainer.py
@@ -466,6 +466,7 @@ class UnslothTrainer:
         is_dataset_image: bool = False,
         is_dataset_audio: bool = False,
         trust_remote_code: bool = False,
+        full_finetuning: bool = False,
     ) -> bool:
         """Load model for training (supports both text and vision models)"""
         self.load_in_4bit = load_in_4bit  # Store for training_meta.json
@@ -612,6 +613,7 @@ class UnslothTrainer:
                     dtype = None,
                     auto_model = CsmForConditionalGeneration,
                     load_in_4bit = False,
+                    full_finetuning = full_finetuning,
                     token = hf_token,
                     trust_remote_code = trust_remote_code,
                 )
@@ -626,6 +628,7 @@ class UnslothTrainer:
                     model_name = model_name,
                     dtype = None,
                     load_in_4bit = False,
+                    full_finetuning = full_finetuning,
                     auto_model = WhisperForConditionalGeneration,
                     whisper_language = "English",
                     whisper_task = "transcribe",
@@ -646,6 +649,7 @@ class UnslothTrainer:
                     max_seq_length = max_seq_length,
                     dtype = None,
                     load_in_4bit = load_in_4bit,
+                    full_finetuning = full_finetuning,
                     token = hf_token,
                     trust_remote_code = trust_remote_code,
                 )
@@ -684,6 +688,7 @@ class UnslothTrainer:
                     max_seq_length = max_seq_length,
                     dtype = torch.float32,  # Spark-TTS requires float32
                     load_in_4bit = False,
+                    full_finetuning = full_finetuning,
                     token = hf_token,
                     trust_remote_code = trust_remote_code,
                 )
@@ -697,6 +702,7 @@ class UnslothTrainer:
                     model_name,
                     max_seq_length = max_seq_length,
                     load_in_4bit = False,
+                    full_finetuning = full_finetuning,
                     token = hf_token,
                     trust_remote_code = trust_remote_code,
                 )
@@ -712,6 +718,7 @@ class UnslothTrainer:
                     max_seq_length = max_seq_length,
                     dtype = None,
                     load_in_4bit = load_in_4bit,
+                    full_finetuning = full_finetuning,
                     token = hf_token,
                     trust_remote_code = trust_remote_code,
                 )
@@ -724,6 +731,7 @@ class UnslothTrainer:
                     max_seq_length = max_seq_length,
                     dtype = None,  # Auto-detect
                     load_in_4bit = load_in_4bit,
+                    full_finetuning = full_finetuning,
                     token = hf_token,
                     trust_remote_code = trust_remote_code,
                 )
@@ -755,6 +763,7 @@ class UnslothTrainer:
                     max_seq_length = max_seq_length,
                     dtype = None,  # Auto-detect
                     load_in_4bit = load_in_4bit,
+                    full_finetuning = full_finetuning,
                     token = hf_token,
                     trust_remote_code = trust_remote_code,
                 )
@@ -779,13 +788,14 @@ class UnslothTrainer:
                 self._source_code_retried = True
                 logger.info(f"\n'could not get source code' — retrying once...\n")
                 return self.load_model(
-                    model_name,
-                    max_seq_length,
-                    load_in_4bit,
-                    hf_token,
-                    is_dataset_image,
-                    is_dataset_audio,
-                    trust_remote_code,
+                    model_name = model_name,
+                    max_seq_length = max_seq_length,
+                    load_in_4bit = load_in_4bit,
+                    hf_token = hf_token,
+                    is_dataset_image = is_dataset_image,
+                    is_dataset_audio = is_dataset_audio,
+                    trust_remote_code = trust_remote_code,
+                    full_finetuning = full_finetuning,
                 )
             error_msg = str(e)
             error_lower = error_msg.lower()
diff --git a/studio/backend/core/training/worker.py b/studio/backend/core/training/worker.py
index 57559ded54..284fcf228d 100644
--- a/studio/backend/core/training/worker.py
+++ b/studio/backend/core/training/worker.py
@@ -444,12 +444,16 @@ def run_training_process(
         _tqdm_thread = _th.Thread(target = _monitor_tqdm, daemon = True)
         _tqdm_thread.start()
 
+        training_type = config.get("training_type", "LoRA/QLoRA")
+        use_lora = training_type == "LoRA/QLoRA"
+
         # ── 4c. Load training model (uses VRAM — dataset already formatted) ──
         _send_status(event_queue, "Loading model...")
         success = trainer.load_model(
             model_name = model_name,
             max_seq_length = config["max_seq_length"],
             load_in_4bit = config["load_in_4bit"],
+            full_finetuning = not use_lora,
             hf_token = hf_token,
             is_dataset_image = config.get("is_dataset_image", False),
             is_dataset_audio = config.get("is_dataset_audio", False),
@@ -473,8 +477,6 @@ def run_training_process(
             return
 
         # ── 4d. Prepare model (LoRA or full finetuning) ──
-        training_type = config.get("training_type", "LoRA/QLoRA")
-        use_lora = training_type == "LoRA/QLoRA"
         if use_lora:
             _send_status(event_queue, "Configuring LoRA adapters...")
             success = trainer.prepare_model_for_training(