[FlashInfer v0.6.12] Support FlashInfer 4over6 NVFP4 (#25239)

python/sglang/srt/environ.py

@@ -446,6 +446,9 @@ class Envs:
     SGLANG_FLASHINFER_WORKSPACE_SIZE = EnvInt(384 * 1024 * 1024)
     # Enable per-token NVFP4 activation scaling path for FlashInfer TRT-LLM MoE.
     SGLANG_FLASHINFER_NVFP4_PER_TOKEN_ACTIVATION = EnvBool(False)
+    # SGLang needs to know FlashInfer NVFP4 4over6 config to compute the global scale factor.
+    FLASHINFER_NVFP4_4OVER6 = EnvBool(False)
+    FLASHINFER_NVFP4_4OVER6_E4M3_USE_256 = EnvBool(False)
     # Skip-softmax threshold scale factor for TRT-LLM attention (prefill and decode separately).
     # None = standard attention. See https://arxiv.org/abs/2512.12087
     SGLANG_SKIP_SOFTMAX_PREFILL_THRESHOLD_SCALE_FACTOR = EnvFloat(None)

python/sglang/srt/layers/moe/moe_runner/flashinfer_trtllm.py

@@ -876,9 +876,16 @@ def fused_experts_none_to_flashinfer_trtllm_fp4(
     if envs.SGLANG_FLASHINFER_NVFP4_PER_TOKEN_ACTIVATION.get():
         from flashinfer import SfLayout, nvfp4_quantize
 
+        e4m3_max = 448.0
+        if (
+            envs.FLASHINFER_NVFP4_4OVER6.get()
+            and envs.FLASHINFER_NVFP4_4OVER6_E4M3_USE_256.get()
+        ):
+            e4m3_max = 256.0
+
         hs_fp4_bytes, hs_sf_bytes, per_token_scale = nvfp4_quantize(
             hidden_states,
-            1.0 / (448.0 * 6.0),
+            1.0 / (e4m3_max * 6.0),
             sfLayout=SfLayout.layout_linear,
             per_token_activation=True,
         )