diff --git a/examples/mnist/mnist-common.cpp b/examples/mnist/mnist-common.cpp
index 1bc5b4c81..ea90dd97c 100644
--- a/examples/mnist/mnist-common.cpp
+++ b/examples/mnist/mnist-common.cpp
@@ -556,15 +556,6 @@ void mnist_model_train(mnist_model & model, const float * images, const float *
                 ggml_backend_graph_compute(model.backend, gb_opt);
                 ggml_graph_reset(gb_grad); // Set gradients to zero, do not reset optimizer.
             }
-            for (int j = 0; j < gb_grad->n_nodes; ++j) {
-                struct ggml_tensor * node = gb_grad->nodes[j];
-
-                if (node->op != GGML_OP_OPT_STEP_ADAM) {
-                    continue;
-                }
-
-                node->op_params[0]++;
-            }
 
             ggml_backend_tensor_get(model.loss,   &loss,         0, ggml_nbytes(model.loss));
             ggml_backend_tensor_get(model.logits, logits.data(), 0, ggml_nbytes(model.logits));
diff --git a/src/ggml-cuda/opt-step-adam.cu b/src/ggml-cuda/opt-step-adam.cu
index 580f08167..4f2689bf6 100644
--- a/src/ggml-cuda/opt-step-adam.cu
+++ b/src/ggml-cuda/opt-step-adam.cu
@@ -63,15 +63,18 @@ void ggml_cuda_opt_step_adam(ggml_backend_cuda_context & ctx, ggml_tensor * dst)
 
     const int64_t ne = ggml_nelements(src0);
 
-    int32_t iter;  memcpy(&iter,  &dst->op_params[0], sizeof(float));
-    float   alpha; memcpy(&alpha, &dst->op_params[1], sizeof(float));
-    float   beta1; memcpy(&beta1, &dst->op_params[2], sizeof(float));
-    float   beta2; memcpy(&beta2, &dst->op_params[3], sizeof(float));
-    float   eps;   memcpy(&eps,   &dst->op_params[4], sizeof(float));
-    float   l1;    memcpy(&l1,    &dst->op_params[5], sizeof(float));
+    int64_t iter;  memcpy(&iter,  &dst->op_params[0], sizeof(int64_t));
+    float   alpha; memcpy(&alpha, &dst->op_params[2], sizeof(float));
+    float   beta1; memcpy(&beta1, &dst->op_params[3], sizeof(float));
+    float   beta2; memcpy(&beta2, &dst->op_params[4], sizeof(float));
+    float   eps;   memcpy(&eps,   &dst->op_params[5], sizeof(float));
+    float   l1;    memcpy(&l1,    &dst->op_params[6], sizeof(float));
 
     const float beta1h  = alpha/(1.0f - powf(beta1, iter));
     const float beta2h  =  1.0f/(1.0f - powf(beta2, iter));
 
     opt_step_adam_f32_cuda(src0_d, src0_grad_d, src0_grad_m_d, src0_grad_v_d, ne, alpha, beta1, beta2, eps, l1, beta1h, beta2h, stream);
+
+    iter++;
+    memcpy(&dst->op_params[0], &iter, sizeof(int64_t));
 }
diff --git a/src/ggml.c b/src/ggml.c
index 0994309af..ffcc9defe 100644
--- a/src/ggml.c
+++ b/src/ggml.c
@@ -8132,12 +8132,13 @@ struct ggml_tensor * ggml_opt_step_adam(
     result->src[2] = ggml_dup_tensor(ctx, a->grad);
     result->src[3] = ggml_dup_tensor(ctx, a->grad);
 
-    ggml_set_op_params_i32(result, 0, 1);     // iteration
-    ggml_set_op_params_f32(result, 1, alpha);
-    ggml_set_op_params_f32(result, 2, beta1);
-    ggml_set_op_params_f32(result, 3, beta2);
-    ggml_set_op_params_f32(result, 4, eps);
-    ggml_set_op_params_f32(result, 5, l1);
+    const int64_t iter = 1;
+    memcpy(&result->op_params[0], &iter, sizeof(int64_t));
+    ggml_set_op_params_f32(result, 2, alpha);
+    ggml_set_op_params_f32(result, 3, beta1);
+    ggml_set_op_params_f32(result, 4, beta2);
+    ggml_set_op_params_f32(result, 5, eps);
+    ggml_set_op_params_f32(result, 6, l1);
 
     return result;
 }
@@ -17162,12 +17163,12 @@ static void ggml_compute_forward_opt_step_adam_f32(
     const int ir1 = MIN(ir0 + dr, nr);
 
     /* const float   gnorm = 1.0f; */
-    const int32_t iter  = ggml_get_op_params_i32(dst, 0);
-    const float   alpha = ggml_get_op_params_f32(dst, 1);
-    const float   beta1 = ggml_get_op_params_f32(dst, 2);
-    const float   beta2 = ggml_get_op_params_f32(dst, 3);
-    const float   eps   = ggml_get_op_params_f32(dst, 4);
-    const float   l1    = ggml_get_op_params_f32(dst, 5);
+    int64_t       iter;   memcpy(&iter, &dst->op_params[0], sizeof(int64_t));
+    const float   alpha = ggml_get_op_params_f32(dst, 2);
+    const float   beta1 = ggml_get_op_params_f32(dst, 3);
+    const float   beta2 = ggml_get_op_params_f32(dst, 4);
+    const float   eps   = ggml_get_op_params_f32(dst, 5);
+    const float   l1    = ggml_get_op_params_f32(dst, 6);
 
     const float beta1h  = alpha/(1.0f - powf(beta1, iter));
     const float beta2h  =  1.0f/(1.0f - powf(beta2, iter));
@@ -17194,6 +17195,14 @@ static void ggml_compute_forward_opt_step_adam_f32(
             w[i00] = w[i00]*(1.0f - alpha*l1) - mh/vh;
         }
     }
+
+    ggml_barrier(params->shared);
+    if (ith != 0) {
+        return;
+    }
+
+    iter++;
+    memcpy(&dst->op_params[0], &iter, sizeof(int64_t));
 }
 
 static void ggml_compute_forward_opt_step_adam(