sgl-project · BBuf · Jul 22, 2026 · Jun 30, 2026 · Jun 30, 2026 · Jul 1, 2026
diff --git a/benchmark/kernels/deepseek/benchmark_deepgemm_dsv3_router_gemm_blackwell.py b/benchmark/kernels/deepseek/benchmark_deepgemm_dsv3_router_gemm_blackwell.py
diff --git a/python/sglang/jit_kernel/dsv3_fused_a_gemm.py b/python/sglang/jit_kernel/dsv3_fused_a_gemm.py
@@ -1,7 +1,7 @@
 """
 JIT kernel for DeepSeek V3 fused QKV-A GEMM (min-latency).
 
-Replaces the AOT sgl_kernel.dsv3_fused_a_gemm for SM90+ (Hopper) GPUs.
+Runtime-compiled CUDA C++ kernel for SM90+ (Hopper) GPUs.
 Shapes: hd_in a multiple of 256, hd_out a multiple of 16, num_tokens 1-16, bfloat16.
 """
 

diff --git a/python/sglang/jit_kernel/dsv3_router_gemm.py b/python/sglang/jit_kernel/dsv3_router_gemm.py
@@ -1,7 +1,7 @@
 """
 JIT kernel for DeepSeek V3 router GEMM.
 
-Replaces the AOT sgl_kernel.dsv3_router_gemm for SM90+ (Hopper) GPUs.
+Runtime-compiled CUDA C++ kernel for SM90+ (Hopper) GPUs.
 Supports num_experts in {256, 384}, hidden_dim a multiple of 1024, num_tokens 1-16.
 """
 

diff --git a/python/sglang/jit_kernel/fused_a_gemm.py b/python/sglang/jit_kernel/fused_a_gemm.py
@@ -1,8 +1,7 @@
 """Unified entry point for the DeepSeek-V3 fused QKV-A GEMM.
 
-Dispatches to one of three interchangeable implementations via ``backend``:
+Dispatches to one of two interchangeable implementations via ``backend``:
 
-- ``"aot"``: prebuilt ``sgl_kernel.dsv3_fused_a_gemm`` (CUDA C++).
 - ``"jit"``: runtime-compiled CUDA C++ (``sglang.jit_kernel.dsv3_fused_a_gemm``).
 - ``"cutedsl"``: CuTe DSL (``sglang.jit_kernel.cutedsl_dsv3_fused_a_gemm``).
 - ``"auto"``: CuTe DSL on SM120+, otherwise the JIT kernel.
@@ -21,7 +20,6 @@
 
 class FusedAGemmBackend(str, Enum):
     AUTO = "auto"
-    AOT = "aot"
     JIT = "jit"
     CUTEDSL = "cutedsl"
 
@@ -70,9 +68,7 @@ def dsv3_fused_a_gemm(
     if backend == FusedAGemmBackend.AUTO:
         backend = _AUTO_BACKEND
 
-    if backend == FusedAGemmBackend.AOT:
-        from sgl_kernel import dsv3_fused_a_gemm as impl
-    elif backend == FusedAGemmBackend.JIT:
+    if backend == FusedAGemmBackend.JIT:
         from sglang.jit_kernel.dsv3_fused_a_gemm import dsv3_fused_a_gemm as impl
     else:
         from sglang.jit_kernel.cutedsl_dsv3_fused_a_gemm import (

diff --git a/sgl-kernel/CMakeLists.txt b/sgl-kernel/CMakeLists.txt
@@ -263,7 +263,6 @@ set(SOURCES
     "csrc/expert_specialization/es_sm100_mxfp8_blockscaled_group_quant.cu"
 
     "csrc/gemm/awq_kernel.cu"
-    "csrc/gemm/dsv3_fused_a_gemm.cu"
     "csrc/gemm/fp8_gemm_kernel.cu"
     "csrc/gemm/int8_gemm_kernel.cu"
     "csrc/gemm/per_token_group_quant_8bit.cu"

diff --git a/sgl-kernel/benchmark/bench_dsv3_fused_a_gemm.py b/sgl-kernel/benchmark/bench_dsv3_fused_a_gemm.py
diff --git a/sgl-kernel/csrc/common_extension.cc b/sgl-kernel/csrc/common_extension.cc
@@ -136,9 +136,6 @@ TORCH_LIBRARY_FRAGMENT(sgl_kernel, m) {
   m.def("sgl_per_token_quant_fp8(Tensor input, Tensor! output_q, Tensor! output_s) -> ()");
   m.impl("sgl_per_token_quant_fp8", torch::kCUDA, &sgl_per_token_quant_fp8);
 
-  m.def("dsv3_fused_a_gemm(Tensor! output, Tensor mat_a, Tensor mat_b) -> ()");
-  m.impl("dsv3_fused_a_gemm", torch::kCUDA, &dsv3_fused_a_gemm);
-
   /*
    * From csrc/gemm/gptq
    */

diff --git a/sgl-kernel/csrc/common_extension_musa.cc b/sgl-kernel/csrc/common_extension_musa.cc
@@ -97,9 +97,6 @@ TORCH_LIBRARY_EXPAND(sgl_kernel, m) {
   m.def("sgl_per_token_quant_fp8(Tensor input, Tensor output_q, Tensor output_s) -> ()");
   m.impl("sgl_per_token_quant_fp8", torch::kMUSA, &sgl_per_token_quant_fp8);
 
-  m.def("dsv3_fused_a_gemm(Tensor! output, Tensor mat_a, Tensor mat_b) -> ()");
-  m.impl("dsv3_fused_a_gemm", torch::kMUSA, &dsv3_fused_a_gemm);
-
   /*
    * From csrc/moe
    */