diff --git a/llama.cpp b/llama.cpp
index 9f12cc0d9..f478aca22 100644
--- a/llama.cpp
+++ b/llama.cpp
@@ -3271,18 +3271,19 @@ struct llama_context * llama_new_context_with_model(
         }
 
 #ifdef LLAMA_USE_ALLOCATOR
+        static const size_t tensor_alignment = 32;
         ctx->buf_compute.resize(ggml_tensor_overhead() * 3072 + ggml_graph_overhead());
 
         // measure memory requirements for worst-case graph
-        ctx->alloc = ggml_allocator_new_measure(32);
+        ctx->alloc = ggml_allocator_new_measure(tensor_alignment);
 
         // build worst-case graph
         int n_tokens = std::min((int)hparams.n_ctx, params.n_batch);
         int n_past = hparams.n_ctx - n_tokens;
-        std::vector<llama_token> tokens(n_tokens, llama_token_bos());
-        ggml_cgraph * gf = llama_build_graph(*ctx, tokens.data(), NULL, n_tokens, n_past);
+        llama_token token = llama_token_bos();
+        ggml_cgraph * gf = llama_build_graph(*ctx, &token, NULL, n_tokens, n_past);
 
-        size_t size = ggml_allocator_alloc_graph_tensors(ctx->alloc, gf);
+        size_t size = ggml_allocator_alloc_graph_tensors(ctx->alloc, gf) + tensor_alignment;
         fprintf(stderr, "%s: worst-case graph size = %7.2f MB\n", __func__, size / 1024.0 / 1024.0);
         fprintf(stderr, "%s: compute buffer total size: %7.2f MB\n", __func__, (ctx->buf_compute.size + size) / 1024.0 / 1024.0);
 
@@ -3293,7 +3294,7 @@ struct llama_context * llama_new_context_with_model(
         // recreate allocator with exact memory requirements
         ggml_allocator_free(ctx->alloc);
         ctx->buf_alloc.resize(size);
-        ctx->alloc = ggml_allocator_new(ctx->buf_alloc.addr, ctx->buf_alloc.size, 32);
+        ctx->alloc = ggml_allocator_new(ctx->buf_alloc.addr, ctx->buf_alloc.size, tensor_alignment);
 #else
         ctx->buf_compute.resize(MEM_REQ_EVAL().at(ctx->model.type) + ggml_graph_overhead());
 #endif