diff --git a/ggml/include/ggml.h b/ggml/include/ggml.h
index 1a18b3bdc..4fb929387 100644
--- a/ggml/include/ggml.h
+++ b/ggml/include/ggml.h
@@ -571,7 +571,7 @@ extern "C" {
         GGML_OP_RECIPROCAL,
         GGML_OP_TTSROUND,
         GGML_OP_MOD,
-        GGML_OP_CUMSUM,
+        GGML_OP_CUMSUM_TTS,
         GGML_OP_STFT,
         GGML_OP_AA_STFT,
         GGML_OP_ISTFT,
@@ -2658,7 +2658,7 @@ extern "C" {
             struct ggml_context * ctx,
             struct ggml_tensor  * a);
         // cumulative sums along first axis (ne0)
-    GGML_API struct ggml_tensor * ggml_cumsum(
+    GGML_API struct ggml_tensor * ggml_cumsum_tts(
             struct ggml_context * ctx,
             struct ggml_tensor  * a);
     GGML_API struct ggml_tensor * ggml_conv_1d_dw_tts(
diff --git a/ggml/src/ggml-cpu/ggml-cpu.c b/ggml/src/ggml-cpu/ggml-cpu.c
index c7843dae9..bf2b033b7 100644
--- a/ggml/src/ggml-cpu/ggml-cpu.c
+++ b/ggml/src/ggml-cpu/ggml-cpu.c
@@ -1717,7 +1717,7 @@ static void ggml_compute_forward_reciprocal(
             }
     }
 }
-static void ggml_compute_forward_cumsum_f32(
+static void ggml_compute_forward_cumsum_f32_tts(
         const struct ggml_compute_params * params,
         struct ggml_tensor * dst) {
     const struct ggml_tensor * src0 = dst->src[0];
@@ -1751,7 +1751,7 @@ static void ggml_compute_forward_cumsum_f32(
         }
     }
 }
-static void ggml_compute_forward_cumsum(
+static void ggml_compute_forward_cumsum_tts(
         const struct ggml_compute_params * params,
         struct ggml_tensor * dst) {
 
@@ -1760,7 +1760,7 @@ static void ggml_compute_forward_cumsum(
     switch (src0->type) {
         case GGML_TYPE_F32:
             {
-                ggml_compute_forward_cumsum_f32(params, dst);
+                ggml_compute_forward_cumsum_f32_tts(params, dst);
             } break;
         default:
             {
@@ -2839,9 +2839,9 @@ static void ggml_compute_forward(struct ggml_compute_params * params, struct ggm
             {
                 ggml_compute_forward_ttsround(params, tensor);
             } break;
-        case GGML_OP_CUMSUM:
+        case GGML_OP_CUMSUM_TTS:
             {
-                ggml_compute_forward_cumsum(params, tensor);
+                ggml_compute_forward_cumsum_tts(params, tensor);
             } break;
         case GGML_OP_MOD:
             {
@@ -3188,7 +3188,7 @@ static int ggml_get_n_tasks(struct ggml_tensor * node, int n_threads) {
         case GGML_OP_RECIPROCAL: //kcpp: dirtypatch tts cpp
         case GGML_OP_MOD:
         case GGML_OP_TTSROUND:
-        case GGML_OP_CUMSUM:
+        case GGML_OP_CUMSUM_TTS:
         case GGML_OP_STFT:
         case GGML_OP_AA_STFT:
         case GGML_OP_ISTFT:
diff --git a/ggml/src/ggml.c b/ggml/src/ggml.c
index cda0274ea..5db4b2d16 100644
--- a/ggml/src/ggml.c
+++ b/ggml/src/ggml.c
@@ -7489,11 +7489,11 @@ struct ggml_tensor * ggml_mod_inplace(
         float                 mod_val) {
     return ggml_mod_impl(ctx, a, mod_val, true);
 }
-struct ggml_tensor * ggml_cumsum(
+struct ggml_tensor * ggml_cumsum_tts(
         struct ggml_context * ctx,
         struct ggml_tensor  * a) {
     struct ggml_tensor * result =  ggml_dup_tensor(ctx, a);
-    result->op     = GGML_OP_CUMSUM;
+    result->op     = GGML_OP_CUMSUM_TTS;
     result->src[0] = a;
     return result;
 }
diff --git a/otherarch/ttscpp/src/kokoro_model.cpp b/otherarch/ttscpp/src/kokoro_model.cpp
index 5dde33afc..c7543ac93 100644
--- a/otherarch/ttscpp/src/kokoro_model.cpp
+++ b/otherarch/ttscpp/src/kokoro_model.cpp
@@ -173,7 +173,7 @@ static struct ggml_tensor * build_noise_block(ggml_context * ctx, kokoro_noise_r
 
 static struct ggml_tensor * build_sin_gen(ggml_context * ctx, kokoro_model * model, kokoro_context * kctx, struct ggml_tensor * x, int harmonic_num, int sequence_length, float voice_threshold, float sin_amp, float noise_std) {
 	struct ggml_tensor * cur = ggml_mul(ctx, ggml_repeat(ctx, x, ggml_new_tensor_2d(ctx, GGML_TYPE_F32, x->ne[0], harmonic_num)), model->harmonic_sampling_norm);
-	cur = ggml_mul(ctx, ggml_cumsum(ctx, ggml_mod(ctx, cur, 1.0f)), model->sampling_factor_scalar);
+	cur = ggml_mul(ctx, ggml_cumsum_tts(ctx, ggml_mod(ctx, cur, 1.0f)), model->sampling_factor_scalar);
 	cur = ggml_upscale_linear(ctx, cur, 300);
 	struct ggml_tensor * upscaled = ggml_upscale_ext(ctx, x, x->ne[0]*300, x->ne[1], x->ne[2], x->ne[3],GGML_SCALE_MODE_NEAREST);