diff --git a/docs/configuration/optimization.md b/docs/configuration/optimization.md
index 2eeb8ad25de5f..c7f50497d6ffa 100644
--- a/docs/configuration/optimization.md
+++ b/docs/configuration/optimization.md
@@ -48,7 +48,7 @@ You can tune the performance by adjusting `max_num_batched_tokens`:
 
 - Smaller values (e.g., 2048) achieve better inter-token latency (ITL) because there are fewer prefills slowing down decodes.
 - Higher values achieve better time to first token (TTFT) as you can process more prefill tokens in a batch.
-- For optimal throughput, we recommend setting `max_num_batched_tokens > 8096` especially for smaller models on large GPUs.
+- For optimal throughput, we recommend setting `max_num_batched_tokens > 8192` especially for smaller models on large GPUs.
 - If `max_num_batched_tokens` is the same as `max_model_len`, that's almost the equivalent to the V0 default scheduling policy (except that it still prioritizes decodes).
 
 ```python