diff --git a/examples/offline_inference/long_context.py b/examples/offline_inference/long_context.py
index 019d9a200..e52c56221 100644
--- a/examples/offline_inference/long_context.py
+++ b/examples/offline_inference/long_context.py
@@ -56,7 +56,7 @@
 trunc = args.trunc_print_len
 
 max_num_seqs = args.max_num_seqs  # defines the max batch size
-assert args.max_prompt_len < args.max_model_len
+assert args.max_prompt_len <= args.max_model_len
 
 if platform.machine() == "arm64":
     print("Detected arm64 running environment. "
@@ -122,7 +122,7 @@ def round_up(t):
 
 
 tokens_to_generate = [
-    args.max_model_len - round_up(plen) for plen in prompt_lens
+    args.max_model_len + 1 - round_up(prompt_len) for prompt_len in prompt_lens
 ]
 
 sampling_params = [
diff --git a/vllm_spyre/platform.py b/vllm_spyre/platform.py
index 20007d501..f8e22d1fa 100644
--- a/vllm_spyre/platform.py
+++ b/vllm_spyre/platform.py
@@ -284,7 +284,8 @@ def validate_request(
             # ceil division to pad to next block boundary
             prompt_padding_len = math.ceil(
                 prompt_len / cls._block_size) * cls._block_size
-            if (prompt_padding_len + max_tokens
+            # we have to account for the token generated during prefill (-1)
+            if (prompt_padding_len + max_tokens - 1
                     > cls._config.scheduler_config.max_model_len):
                 raise ValueError(
                     "Could not add request: prompt length is "