[FlashInfer v0.6.16] Support FlashInfer CuTe DSL NVFP4 MoE quantization (#28354)

python/sglang/srt/server_args.py

@@ -6670,9 +6670,9 @@ class ServerArgs:
         if view.moe_runner_backend == "flashinfer_cutedsl":
             # modelopt_mixed with non-NVFP4 MoE layers is rejected at load time.
             assert (
-                view.quantization in ["modelopt_fp4", "modelopt_mixed"]
+                view.quantization in ["modelopt_fp4", "modelopt_mixed", "nvfp4_online"]
                 or self.get_model_config().nvfp4_moe_meta is not None
-            ), f"Invalid quantization '{view.quantization}'. \nFlashInfer CuteDSL MOE currently supports only: 'modelopt_fp4', 'modelopt_mixed' (with NVFP4 MoE layers), or hybrid NVFP4 models."
+            ), f"Invalid quantization '{view.quantization}'. \nFlashInfer CuteDSL MOE currently supports only: 'modelopt_fp4', 'modelopt_mixed' (with NVFP4 MoE layers), 'nvfp4_online', or hybrid NVFP4 models."
             assert view.ep_size in [
                 1,
                 self.tp_size,
@@ -6685,6 +6685,14 @@ class ServerArgs:
                 f"flashinfer_cutedsl supports moe_a2a_backend='none', 'deepep', or 'flashinfer', "
                 f"got '{view.moe_a2a_backend}'."
             )
+            if view.moe_a2a_backend == "deepep" and (
+                view.quantization == "nvfp4_online"
+                or envs.SGLANG_FLASHINFER_NVFP4_PER_TOKEN_ACTIVATION.get()
+            ):
+                raise ValueError(
+                    "flashinfer_cutedsl per-token NVFP4 activation requires "
+                    "moe_a2a_backend='none' or 'flashinfer'."
+                )
 
         if view.moe_runner_backend in ["flashinfer_trtllm", "experimental_sgl_trtllm"]:
             assert view.quantization in [
@@ -7983,6 +7991,8 @@ class ServerArgs:
             "1" if self.enable_deterministic_inference else "0"
         )
         self._handle_custom_all_reduce_v2_multinode()
+        if self.enable_deterministic_inference:
+            envs.SGLANG_FLASHINFER_MOE_FUSED_FINALIZE.set("0")
         if self.debug_cuda_graph:
             if not (is_cuda() or is_hip()):
                 logger.warning(