diff --git a/vllm_spyre/platform.py b/vllm_spyre/platform.py
index c22ed107b..61c133c4b 100644
--- a/vllm_spyre/platform.py
+++ b/vllm_spyre/platform.py
@@ -77,7 +77,10 @@ def check_and_update_config(cls, vllm_config: VllmConfig) -> None:
             # Override --max-num-seqs to the biggest warmup batch size
             # And override --max-model-len to the biggest warmup sequence
             cls._warmup_shapes = None
-            spyre_warmup_shapes = cls.get_warmup_shapes(scheduler_config)
+            max_model_len = model_config.max_model_len \
+                if model_config is not None else sys.maxsize
+            spyre_warmup_shapes = cls.get_warmup_shapes(
+                scheduler_config, max_model_len)
             max_batch_size = 0
             max_seq_len = 0
             for shape in spyre_warmup_shapes:
@@ -168,7 +171,10 @@ def inference_mode(cls):
         return torch.no_grad()
 
     @classmethod
-    def get_warmup_shapes(cls, scheduler_config) -> tuple[dict[str, int], ...]:
+    def get_warmup_shapes(
+            cls,
+            scheduler_config,
+            max_model_len: int = sys.maxsize) -> tuple[dict[str, int], ...]:
         if cls._warmup_shapes is not None:
             return cls._warmup_shapes
         # load warmup shapes and sort by "speed"
@@ -204,6 +210,16 @@ def get_warmup_shapes(cls, scheduler_config) -> tuple[dict[str, int], ...]:
             } for pl, nt, bs in zip(wup_prompt_lens, wup_new_tokens,
                                     wup_batch_sizes)],
                    key=operator.itemgetter('batch_size', 'prompt_length')))
+
+        for shape in cls._warmup_shapes:
+            max_seq_len = shape["prompt_length"] + shape["new_tokens"]
+            if max_seq_len > max_model_len:
+                raise RuntimeError(
+                    f"Warmup shape [{shape['batch_size']},"
+                    " {shape['prompt_length']}, {shape['new_tokens']}]"
+                    " results in a maximum sequence length of "
+                    "{max_seq_len} which is longer that what the model "
+                    "supports ({max_model_len})")
         return cls._warmup_shapes
 
     @classmethod