diff --git a/onnxruntime/contrib_ops/webgpu/bert/attention.cc b/onnxruntime/contrib_ops/webgpu/bert/attention.cc
index 0bc834e1af93d..ea5ab3d091461 100644
--- a/onnxruntime/contrib_ops/webgpu/bert/attention.cc
+++ b/onnxruntime/contrib_ops/webgpu/bert/attention.cc
@@ -125,7 +125,7 @@ Status AttentionProbsProgram::GenerateShaderCode(ShaderHelper& shader) const {
                               << "let kv_head_idx = head_idx / uniforms.n_reps;\n"
                               << "let kv_num_heads = uniforms.num_heads / uniforms.n_reps;\n"
                               << "let abs_kv_head_idx = batch_idx * kv_num_heads + kv_head_idx;\n"
-                              << "let kOffset = abs_kv_head_idx * uniforms.kv_sequence_length * uniforms.K;\n";;
+                              << "let kOffset = abs_kv_head_idx * uniforms.kv_sequence_length * uniforms.K;\n";
     if (feed_past_key_ && has_present_key_) {
       shader.MainFunctionBody() << "let pastKeyOffset = abs_kv_head_idx * uniforms.past_sequence_length * uniforms.K;\n";
     }
@@ -201,7 +201,7 @@ Status ComputeAttentionProbs(onnxruntime::webgpu::ComputeContext& context, int o
   const bool feed_past_key = present_key != nullptr && past_key != nullptr && past_key->SizeInBytes() > 0;
   const bool has_present_key = output_count > 1 && past_key;
   const bool has_attention_bias = attention_bias != nullptr;
-  const int tile_size = 12;
+  constexpr int tile_size = 12;
   const int components = parameters.head_size_ % 4 == 0 ? 4 : (parameters.head_size_ % 2 == 0 ? 2 : 1);
 
   AttentionProbsProgram program{"AttentionProbs", feed_past_key, has_present_key, has_attention_bias, tile_size,
@@ -257,13 +257,13 @@ Status InPlaceSoftmaxProgram::GenerateShaderCode(ShaderHelper& shader) const {
   shader.MainFunctionBody() << "let batch_idx = workgroup_id.z / uniforms.num_heads;\n"
                             << "let head_idx = workgroup_id.z % uniforms.num_heads;\n"
                             << "let sequence_length = uniforms.sequence_length;\n"
-                            << "var total_sequence_length = uniforms.total_sequence_length;\n";
+                            << "var total_sequence_length = uniforms.total_sequence_length_comp * " << components_ << ";\n";
   std::ostringstream oss;
   InitVarStub(seqlen_k_, total_seqlen_tensor_, true, oss);
   shader.MainFunctionBody() << oss.str()
                             << "let local_offset = local_idx * uniforms.elements_per_thread;\n"
-                            << "let offset = (global_idx / " << work_group_size_ << ") * uniforms.total_sequence_length + local_offset;\n"
-                            << "let seq_causal_length = " << (seqlen_k_ ? "past_sequence_length + workgroup_id.y + 1" : "total_sequence_length") << ";\n"
+                            << "let offset = (global_idx / " << work_group_size_ << ") * uniforms.total_sequence_length_comp + local_offset;\n"
+                            << "let seq_causal_length = " << (seqlen_k_ ? "past_sequence_length + workgroup_id.y + 1" : "uniforms.total_sequence_length_comp") << ";\n"
                             << "var thread_max_vector = f32_val_t(-3.402823e+38f);\n"
                             << "for (var i: u32 = 0; i < uniforms.elements_per_thread && i + local_offset < seq_causal_length; i++) {\n"
                             << "  thread_max_vector = max(f32_val_t(x[offset + i]), thread_max_vector);\n"
@@ -295,7 +295,7 @@ Status InPlaceSoftmaxProgram::GenerateShaderCode(ShaderHelper& shader) const {
                             << "  }\n"
                             << "}\n";
   if (seqlen_k_) {
-    shader.MainFunctionBody() << "for (var total_seq_id: u32 = seq_causal_length; total_seq_id + local_offset < uniforms.total_sequence_length; total_seq_id++) {\n"
+    shader.MainFunctionBody() << "for (var total_seq_id: u32 = seq_causal_length; total_seq_id + local_offset < total_sequence_length; total_seq_id++) {\n"
                               << "   x[offset + total_seq_id] = x_value_t(x_element_t(0));\n"
                               << "}\n";
   }
@@ -319,7 +319,7 @@ Status ComputeInPlaceSoftmax(onnxruntime::webgpu::ComputeContext& context, Tenso
                        {total_seqlen_tensor, ProgramTensorMetadataDependency::TypeAndRank}});
   }
   program.AddOutputs({{probs, ProgramTensorMetadataDependency::TypeAndRank, components}})
-      .SetDispatchGroupSize(batch_size * num_heads * sequence_length)
+      .SetDispatchGroupSize(1, sequence_length, batch_size * num_heads)
       .SetWorkgroupSize(work_group_size)
       .AddUniformVariables({{static_cast<uint32_t>(batch_size)},
                             {static_cast<uint32_t>(num_heads)},
diff --git a/onnxruntime/contrib_ops/webgpu/bert/attention.h b/onnxruntime/contrib_ops/webgpu/bert/attention.h
index 17f7b9e9c5fcd..ea0ad7e03fc54 100644
--- a/onnxruntime/contrib_ops/webgpu/bert/attention.h
+++ b/onnxruntime/contrib_ops/webgpu/bert/attention.h
@@ -75,7 +75,7 @@ class InPlaceSoftmaxProgram final : public Program<InPlaceSoftmaxProgram> {
                                           {"num_heads", ProgramUniformVariableDataType::Uint32},
                                           {"past_sequence_length", ProgramUniformVariableDataType::Uint32},
                                           {"sequence_length", ProgramUniformVariableDataType::Uint32},
-                                          {"total_sequence_length", ProgramUniformVariableDataType::Uint32},
+                                          {"total_sequence_length_comp", ProgramUniformVariableDataType::Uint32},
                                           {"elements_per_thread", ProgramUniformVariableDataType::Uint32});
 
  private: