diff --git a/docs/guides/grpo-deepscaler.md b/docs/guides/grpo-deepscaler.md
index 4404b4294..bc177f2fd 100644
--- a/docs/guides/grpo-deepscaler.md
+++ b/docs/guides/grpo-deepscaler.md
@@ -19,7 +19,7 @@ At the end of each stage, you need to specify the Hugging Face checkpoint to con
 uv run examples/converters/convert_dcp_to_hf.py --config=results/grpo-deepscaler-1.5b-8K/step_240/config.yaml --dcp-ckpt-path=results/grpo-deepscaler-1.5b-8K/step_240/policy/weights --hf-ckpt-path=results/grpo-deepscaler-1.5b-8K/step_240/hf
 ```
 
-When running the next command, we use the Hugging Face checkpoint as the initial checkpoint. We train with an 8K context window for 240 steps, a 16K context window for 290 steps, and a 24K context window for 50 steps. We run all experiments on a single 8XH100 80GB node or on a single 8XA100 80GB node.
+When running the next command, we use the Hugging Face checkpoint as the initial checkpoint. We train with an 8K context window for 240 steps, a 16K context window for 290 steps, and a 24K context window for 50 steps. We run all experiments on a single 8XH100 80GB node. If you're running on 8XA100 80GB, you will need at least 1 node for 8K training and 2 nodes for 16-24k training.
 
 ## Training Curve
 When using the above commands, we get the following training curve: