diff --git a/src/llama-quant.cpp b/src/llama-quant.cpp
index 1e24303c52..b0b3be76ca 100644
--- a/src/llama-quant.cpp
+++ b/src/llama-quant.cpp
@@ -1314,6 +1314,12 @@ static void llama_model_quantize_impl(const std::string & fname_inp, const std::
         }
     }
 
+    std::unordered_map<std::string, ggml_type> bpw_overrides = {};
+    if (params->target_bpw != -1.0f) {
+        LLAMA_LOG_INFO("%s: computing tensor quantization mix to achieve %.3f bpw at lowest ppl - this opearation may take some time\n", __func__, params->target_bpw);
+        bpw_overrides = target_bpw_type(ml, read_data, model, tensors, mapped, values_data, activations_data, params->target_bpw, nthread);
+    }
+
     int cur_split = -1;
     std::ofstream fout;
     auto close_ofstream = [&]() {
@@ -1430,6 +1436,9 @@ static void llama_model_quantize_impl(const std::string & fname_inp, const std::
             if (!params->pure && ggml_is_quantized(default_type)) {
                 int fallback = qs.n_fallback;
                 new_type = llama_tensor_get_type(qs, new_type, tensor, ftype);
+                // get bpw override
+                const auto override = bpw_overrides.find(name);
+                if (override != bpw_overrides.end()) { new_type = override->second; }
                 // unless the user specifies a type, and the tensor geometry will not require fallback quantisation
                 if (params->tensor_types && qs.n_fallback - fallback == 0) {
                     const std::vector<tensor_quantization> & tensor_types = *static_cast<const std::vector<tensor_quantization> *>(params->tensor_types);