[Minor] Use larger batch sizes for A100/B100/B200/MI300x (#17073)

Signed-off-by: Woosuk Kwon <woosuk.kwon@berkeley.edu>

vllm/engine/arg_utils.py

@@ -35,7 +35,7 @@ from vllm.reasoning import ReasoningParserManager
 from vllm.test_utils import MODEL_WEIGHTS_S3_BUCKET, MODELS_ON_S3
 from vllm.transformers_utils.utils import check_gguf_file
 from vllm.usage.usage_lib import UsageContext
-from vllm.utils import FlexibleArgumentParser, is_in_ray_actor
+from vllm.utils import FlexibleArgumentParser, GiB_bytes, is_in_ray_actor
 
 # yapf: enable
 
@@ -1625,13 +1625,13 @@ class EngineArgs:
         # values for non-H100/H200 GPUs.
         try:
             from vllm.platforms import current_platform
-            device_name = current_platform.get_device_name().lower()
+            device_memory = current_platform.get_device_total_memory()
         except Exception:
             # This is only used to set default_max_num_batched_tokens
-            device_name = "no-device"
+            device_memory = 0
 
-        if "h100" in device_name or "h200" in device_name:
-            # For H100 and H200, we use larger default values.
+        if device_memory >= 70 * GiB_bytes:
+            # For GPUs like H100 and MI300x, use larger default values.
             default_max_num_batched_tokens = {
                 UsageContext.LLM_CLASS: 16384,
                 UsageContext.OPENAI_API_SERVER: 8192,