Revert "[Fix] DeepSeek EP accuracy issue on B200 GPUs (#9946)" (#9955)

python/sglang/srt/layers/quantization/deep_gemm_wrapper/compile_utils.py

@@ -44,13 +44,6 @@ def update_deep_gemm_config(gpu_id: int, server_args: ServerArgs):
     global _DO_COMPILE_ALL
     global _IS_FIRST_RANK_ON_NODE
 
-    # Update UE8M0 scaling configuration based on server args
-    from sglang.srt.layers.quantization.deep_gemm_wrapper.configurer import (
-        update_deepgemm_scale_ue8m0,
-    )
-
-    update_deepgemm_scale_ue8m0(server_args.disable_deepgemm_ue8m0)
-
     # Generate m_max
     m_max = 1024 * 16
     if server_args.chunked_prefill_size < 1:

python/sglang/srt/layers/quantization/deep_gemm_wrapper/configurer.py

@@ -29,21 +29,4 @@ def _is_blackwell_arch() -> bool:
 ENABLE_JIT_DEEPGEMM = _compute_enable_deep_gemm()
 
 DEEPGEMM_BLACKWELL = ENABLE_JIT_DEEPGEMM and _is_blackwell_arch()
-# Allow disabling UE8M0 scaling for accuracy-critical workloads
-# This can help with DeepSeek EP accuracy issues on B200 GPUs
-# Will be updated by server args in update_deepgemm_scale_ue8m0()
-DEEPGEMM_SCALE_UE8M0 = DEEPGEMM_BLACKWELL and get_bool_env_var(
-    "SGL_ENABLE_DEEPGEMM_UE8M0", default="true"
-)
-
-
-def update_deepgemm_scale_ue8m0(disable_ue8m0: bool):
-    """Update DEEPGEMM_SCALE_UE8M0 based on server arguments."""
-    global DEEPGEMM_SCALE_UE8M0
-    if disable_ue8m0:
-        DEEPGEMM_SCALE_UE8M0 = False
-        logger.info("DeepGEMM UE8M0 scaling disabled via server argument")
-    else:
-        DEEPGEMM_SCALE_UE8M0 = DEEPGEMM_BLACKWELL and get_bool_env_var(
-            "SGL_ENABLE_DEEPGEMM_UE8M0", default="true"
-        )
+DEEPGEMM_SCALE_UE8M0 = DEEPGEMM_BLACKWELL

python/sglang/srt/server_args.py

@@ -268,7 +268,6 @@ class ServerArgs:
     flashinfer_mxfp4_moe_precision: Literal["default", "bf16"] = "default"
     enable_flashinfer_allreduce_fusion: bool = False
     deepep_mode: Literal["auto", "normal", "low_latency"] = "auto"
-    disable_deepgemm_ue8m0: bool = False
     ep_num_redundant_experts: int = 0
     ep_dispatch_algorithm: Optional[Literal["static", "dynamic", "fake"]] = None
     init_expert_location: str = "trivial"
@@ -1563,11 +1562,6 @@ class ServerArgs:
             default="auto",
             help="Select the mode when enable DeepEP MoE, could be `normal`, `low_latency` or `auto`. Default is `auto`, which means `low_latency` for decode batch and `normal` for prefill batch.",
         )
-        parser.add_argument(
-            "--disable-deepgemm-ue8m0",
-            action="store_true",
-            help="Disable DeepGEMM UE8M0 scaling optimizations. This can help with accuracy issues on Blackwell GPUs (B200) for certain models like DeepSeek.",
-        )
         parser.add_argument(
             "--ep-num-redundant-experts",
             type=int,