diff --git a/src/transformers/generation/utils.py b/src/transformers/generation/utils.py
index 4436b066107..b4f845b424e 100644
--- a/src/transformers/generation/utils.py
+++ b/src/transformers/generation/utils.py
@@ -1470,7 +1470,6 @@ class GenerationMixin:
         elif (
             model_input_name == "inputs_embeds"
             and input_ids_length != inputs_tensor.shape[1]
-            and input_ids_length != 0
             and not self.config.is_encoder_decoder
         ):
             generation_config.max_length -= inputs_tensor.shape[1]
diff --git a/tests/generation/test_utils.py b/tests/generation/test_utils.py
index a953221eb4d..6c8a5e1285f 100644
--- a/tests/generation/test_utils.py
+++ b/tests/generation/test_utils.py
@@ -1786,12 +1786,12 @@ class GenerationTesterMixin:
             model.config.use_cache = True
             model.config.is_decoder = True
             batch_size = input_ids.shape[0]
-            max_cache_len = 30
+            max_length = 30
 
             # here we force to not stop at eos and go until max-length
             model.generation_config.eos_token_id = model.config.get_text_config().eos_token_id = -1
             generation_kwargs = {
-                "max_length": max_cache_len,
+                "max_length": max_length,
                 "cache_implementation": "static",
                 "return_dict_in_generate": True,  # Required to return `past_key_values`
             }
@@ -1810,11 +1810,11 @@ class GenerationTesterMixin:
             num_hidden_layers = text_config.num_hidden_layers
 
             inputs_embeds = model.get_input_embeddings()(input_ids)
-            max_cache_len += inputs_embeds.shape[1] - 1  # the last generated token has no cache
             outputs = model.generate(inputs_embeds=inputs_embeds, **generation_kwargs, **inputs_dict)
 
-            # we should get `max_length` in shape, not `max_length - embeds_length`
-            cache_shape = (batch_size, num_key_value_heads, max_cache_len, head_dim)
+            # we should get `max_length - 1` in shape, not `max_length - embeds_length`.
+            # -1 because the last generated token isn't yet in the cache.
+            cache_shape = (batch_size, num_key_value_heads, max_length - 1, head_dim)
             self.assertTrue(isinstance(outputs.past_key_values, StaticCache))
             self.assertTrue(len(outputs.past_key_values.key_cache) == num_hidden_layers)
             self.assertTrue(outputs.past_key_values.key_cache[0].shape == cache_shape)