diff --git a/csrc/torch_bindings.cpp b/csrc/torch_bindings.cpp
index c8d70b185..b5c0b3001 100644
--- a/csrc/torch_bindings.cpp
+++ b/csrc/torch_bindings.cpp
@@ -373,6 +373,39 @@ TORCH_LIBRARY_EXPAND(TORCH_EXTENSION_NAME, ops) {
   ops.def("gptq_shuffle(Tensor! q_weight, Tensor q_perm, int bit) -> ()");
   ops.impl("gptq_shuffle", torch::kCUDA, &gptq_shuffle);
 
+  // Dequantization for GGML.
+  ops.def(
+      "ggml_dequantize(Tensor W, int type, SymInt m, SymInt n, ScalarType? "
+      "dtype) -> Tensor");
+  ops.impl("ggml_dequantize", torch::kCUDA, &ggml_dequantize);
+
+  // mmvq kernel for GGML.
+  ops.def(
+      "ggml_mul_mat_vec_a8(Tensor W, Tensor X, int type, SymInt row) -> Tensor");
+  ops.impl("ggml_mul_mat_vec_a8", torch::kCUDA, &ggml_mul_mat_vec_a8);
+
+  // mmq kernel for GGML.
+  ops.def("ggml_mul_mat_a8(Tensor W, Tensor X, int type, SymInt row) -> Tensor");
+  ops.impl("ggml_mul_mat_a8", torch::kCUDA, &ggml_mul_mat_a8);
+
+  // mmq kernel for GGML (MoE).
+  ops.def(
+      "ggml_moe_a8(Tensor X, Tensor W, "
+      "Tensor sorted_token_ids, Tensor expert_ids, "
+      "Tensor num_tokens_post_padded, int type, "
+      "SymInt row, SymInt top_k, SymInt tokens) -> Tensor");
+  ops.impl("ggml_moe_a8", torch::kCUDA, &ggml_moe_a8);
+
+  // mmvq kernel for GGML (MoE).
+  ops.def(
+      "ggml_moe_a8_vec(Tensor X, Tensor W, "
+      "Tensor topk_ids, int top_k, "
+      "int type, SymInt row, SymInt tokens) -> Tensor");
+  ops.impl("ggml_moe_a8_vec", torch::kCUDA, &ggml_moe_a8_vec);
+
+  ops.def("ggml_moe_get_block_size(int type) -> int");
+  ops.impl("ggml_moe_get_block_size", &ggml_moe_get_block_size);
+
   // ┌----------  Not supported for Metax -----------┐
   // Compute FP8 quantized tensor for given scaling factor.
   // Supports per-tensor, per-channel, per-token, and arbitrary 2D group