diff --git a/gpttype_adapter.cpp b/gpttype_adapter.cpp
index ff28fead3..6787b55d9 100644
--- a/gpttype_adapter.cpp
+++ b/gpttype_adapter.cpp
@@ -189,6 +189,10 @@ inline bool LogitsDuplicated(std::vector<float> & arr1, std::vector<float> & arr
     return true;
 }
 
+static inline void log_callback_off(ggml_log_level level, const char* text, void*) {
+    return;
+}
+
 static inline void string_trim_whitespace(std::string & s) {
     auto nul = std::find(s.begin(), s.end(), '\0'); //remove everything after the first NUL
     if (nul != s.end()) {
@@ -2559,11 +2563,17 @@ ModelLoadResult gpttype_load_model(const load_model_inputs inputs, FileFormat in
             model_params.tensor_split = tensor_split_temp;
             model_params.n_gpu_layers = -1; //must be this value to be considered default
             printf("Autofit Reserve Space: %d MB\n",taxmb);
+            //disable log spam
+            ggml_log_callback currlogger;
+            void * curruserdat;
+            llama_log_get(&currlogger, &curruserdat);
+            llama_log_set(log_callback_off, nullptr);
             fit_params_target[0] = taxmb*1024*1024;
-            llama_params_fit(kcpp_data->model_filename.c_str(), &model_params, &llama_ctx_params,
+            bool success = (llama_params_fit(kcpp_data->model_filename.c_str(), &model_params, &llama_ctx_params,
             tensor_split_temp, tenos.data(), fit_params_target.data(), kcpp_data->n_ctx,
-            GGML_LOG_LEVEL_DEBUG);
-            printf("Autofit Result: ");
+            GGML_LOG_LEVEL_NONE)==0);
+            llama_log_set(currlogger, curruserdat);
+            printf("Autofit Success: %d, Autofit Result: ",success);
             print_fitted_params(model_params,llama_ctx_params);
         }