diff --git a/llama.cpp b/llama.cpp
index 28e2645e1..0c8e85f6d 100644
--- a/llama.cpp
+++ b/llama.cpp
@@ -6788,7 +6788,7 @@ static struct ggml_tensor * llm_build_kqv(
 
         cur = ggml_flash_attn_ext(ctx, q, k, v, kq_mask, kq_scale, hparams.f_max_alibi_bias);
 
-        if (model.arch == LLM_ARCH_PHI2 || model.arch == LLM_ARCH_PHI3) {
+        if (model.arch == LLM_ARCH_PHI2 || model.arch == LLM_ARCH_PHI3 || model.arch == LLM_ARCH_GPTNEOX) {
             ggml_flash_attn_ext_set_prec(cur, GGML_PREC_F32);
         }
 
@@ -6797,7 +6797,7 @@ static struct ggml_tensor * llm_build_kqv(
         struct ggml_tensor * kq = ggml_mul_mat(ctx, k, q);
         cb(kq, "kq", il);
 
-        if (model.arch == LLM_ARCH_PHI2 || model.arch == LLM_ARCH_PHI3) {
+        if (model.arch == LLM_ARCH_PHI2 || model.arch == LLM_ARCH_PHI3 || model.arch == LLM_ARCH_GPTNEOX) {
             // for this arch, we need to perform the KQ multiplication with F32 precision, otherwise we get NaNs
             // ref: https://github.com/ggerganov/llama.cpp/pull/4490#issuecomment-1859055847
             ggml_mul_mat_set_prec(kq, GGML_PREC_F32);
@@ -17724,6 +17724,14 @@ void llama_set_n_threads(struct llama_context * ctx, uint32_t n_threads, uint32_
     ctx->cparams.n_threads_batch = n_threads_batch;
 }
 
+uint32_t llama_n_threads(struct llama_context * ctx) {
+    return ctx->cparams.n_threads;
+}
+
+uint32_t llama_n_threads_batch(struct llama_context * ctx) {
+    return ctx->cparams.n_threads_batch;
+}
+
 void llama_set_abort_callback(struct llama_context * ctx, bool (*abort_callback)(void * data), void * abort_callback_data) {
     ctx->abort_callback      = abort_callback;
     ctx->abort_callback_data = abort_callback_data;
diff --git a/llama.h b/llama.h
index abb1145a8..f59505d9f 100644
--- a/llama.h
+++ b/llama.h
@@ -761,6 +761,12 @@ extern "C" {
     // n_threads_batch is the number of threads used for prompt and batch processing (multiple tokens)
     LLAMA_API void llama_set_n_threads(struct llama_context * ctx, uint32_t n_threads, uint32_t n_threads_batch);
 
+    // Get the number of threads used for generation of a single token.
+    LLAMA_API uint32_t llama_n_threads(struct llama_context * ctx);
+
+    // Get the number of threads used for prompt and batch processing (multiple token).
+    LLAMA_API uint32_t llama_n_threads_batch(struct llama_context * ctx);
+
     // Set whether to use causal attention or not
     // If set to true, the model will only attend to the past tokens
     LLAMA_API void llama_set_causal_attn(struct llama_context * ctx, bool causal_attn);