diff --git a/src/backends/cpu/CPURoPE.cpp b/src/backends/cpu/CPURoPE.cpp
index e47c740e..2b9e2932 100644
--- a/src/backends/cpu/CPURoPE.cpp
+++ b/src/backends/cpu/CPURoPE.cpp
@@ -140,7 +140,52 @@ void CPURoPE::rope_llama(shared_ptr<Tensor> input, shared_ptr<Tensor> output){
 void CPURoPE::rope_hf(shared_ptr<Tensor> input, shared_ptr<Tensor> output){
     auto out_dtype = output->dtype();
     int partial_dimension = (input->dimension()) * partial_rotary_factor_;
+    int half = (int)(partial_dimension / 2);
     assert(partial_dimension%2==0);
+    if(output->ctype() == BSHD){        
+        if (out_dtype == MLLM_TYPE_F32){
+#pragma omp parallel for collapse(4) num_threads(thread_count)
+            for (int n = 0; n < input->batch(); ++n) {
+                for (int h = 0; h < input->head(); ++h) {
+                    for (int s = 0; s < input->sequence(); ++s) { // sequance
+                        for (int d = 0; d < partial_dimension/2; ++d) {
+                            auto v = input->ptrAt<float>(n, h, s, d);
+                            auto o = output->ptrAt<float>(n, h, s, d);
+                            float in_value = v[0];
+                            float in_value_2 = v[half];
+                            float sin_value = sin_[s + h_cnt_][d];
+                            float cos_value = cos_[s + h_cnt_][d];
+                            auto value = in_value * cos_value - in_value_2 * sin_value;
+                            auto value2 = in_value * sin_value + in_value_2 * cos_value;
+                            o[0] = value;
+                            o[half] = value2;
+                        }
+                    }
+                }
+            }
+        }else if(out_dtype == MLLM_TYPE_F16){
+#pragma omp parallel for collapse(4) num_threads(thread_count)
+            for (int n = 0; n < input->batch(); ++n) {
+                for (int h = 0; h < input->head(); ++h) {
+                    for (int s = 0; s < input->sequence(); ++s) { // sequance
+                        for (int d = 0; d < partial_dimension/2; ++d) {
+                            auto v = input->ptrAt<float>(n, h, s, d);
+                            auto o = output->ptrAt<mllm_fp16_t>(n, h, s, d);
+                            float in_value = v[0];
+                            float in_value_2 = v[half];
+                            float sin_value = sin_[s + h_cnt_][d];
+                            float cos_value = cos_[s + h_cnt_][d];
+                            auto value = in_value * cos_value - in_value_2 * sin_value;
+                            auto value2 = in_value * sin_value + in_value_2 * cos_value;
+                            o[0] = MLLM_FP32_TO_FP16(value);
+                            o[half] = MLLM_FP32_TO_FP16(value2);
+                        }
+                    }
+                }
+            }
+        }
+        return;
+    }
 #pragma omp parallel for collapse(4) num_threads(thread_count)
     for (int n = 0; n < input->batch(); ++n) {
         for (int h = 0; h < input->head(); ++h) {
@@ -152,10 +197,10 @@ void CPURoPE::rope_hf(shared_ptr<Tensor> input, shared_ptr<Tensor> output){
                     float cos_value = cos_[s + h_cnt_][d];
                     auto value = in_value * cos_value - in_value_2 * sin_value;
                     auto value2 = in_value * sin_value + in_value_2 * cos_value;
-                    if (output->dtypeAt(n, h, s, d) == MLLM_TYPE_F32) {
+                    if (out_dtype == MLLM_TYPE_F32) {
                         output->setDataAt<float>(n, h, s, d, value);
                         output->setDataAt<float>(n, h, s, d+ partial_dimension / 2, value2);
-                    } else if (output->dtypeAt(n, h, s, d) == MLLM_TYPE_F16) {
+                    } else if (out_dtype == MLLM_TYPE_F16) {
                         output->setDataAt<mllm_fp16_t>(n, h, s, d, MLLM_FP32_TO_FP16(value));
                         output->setDataAt<mllm_fp16_t>(n, h, s, d+ partial_dimension / 2, MLLM_FP32_TO_FP16(value2));
                     }