diff --git a/otherarch/llama_v2.cpp b/otherarch/llama_v2.cpp
index dbe157928..06bfdee97 100644
--- a/otherarch/llama_v2.cpp
+++ b/otherarch/llama_v2.cpp
@@ -1060,33 +1060,7 @@ static void llama_v2_model_load_internal(
     ml->load_all_data(progress_callback, progress_callback_user_data, use_mlock ? &lctx.model.mlock_mmap : NULL);
 
     model.mapping = std::move(ml->mapping);
-#if defined(GGML_USE_CUBLAS)
-    {
-        const int n_gpu = std::min(n_gpu_layers, int(hparams.n_layer));
-
-        fprintf(stderr, "%s: [cublas] offloading %d layers to GPU\n", __func__, n_gpu);
-
-        size_t vram_total = 0;
-
-        for (int i = 0; i < n_gpu; ++i) {
-            const auto & layer = model.layers[i];
-
-            ggml_cuda_transform_tensor(layer.wq); vram_total += ggml_v2_nbytes(layer.wq);
-            ggml_cuda_transform_tensor(layer.wk); vram_total += ggml_v2_nbytes(layer.wk);
-            ggml_cuda_transform_tensor(layer.wv); vram_total += ggml_v2_nbytes(layer.wv);
-            ggml_cuda_transform_tensor(layer.wo); vram_total += ggml_v2_nbytes(layer.wo);
-            ggml_cuda_transform_tensor(layer.w1); vram_total += ggml_v2_nbytes(layer.w1);
-            ggml_cuda_transform_tensor(layer.w2); vram_total += ggml_v2_nbytes(layer.w2);
-            ggml_cuda_transform_tensor(layer.w3); vram_total += ggml_v2_nbytes(layer.w3);
-        }
-        if (n_gpu_layers > (int) hparams.n_layer) {
-            fprintf(stderr, "%s: [cublas] offloading output layer to GPU\n", __func__);
-            ggml_cuda_transform_tensor(model.output); vram_total += ggml_v2_nbytes(model.output);
-        }
-
-        fprintf(stderr, "%s: [cublas] total VRAM used: %zu MB\n", __func__, vram_total / 1024 / 1024);
-    }
-#elif defined(GGML_USE_CLBLAST)
+#if defined(GGML_USE_CLBLAST)
     {
         const int n_gpu = std::min(n_gpu_layers, int(hparams.n_layer));
         if(GetQuantsUnshuffled())