diff --git a/src/llama.cpp b/src/llama.cpp
index 1fe2b9f7..a43312a7 100644
--- a/src/llama.cpp
+++ b/src/llama.cpp
@@ -13689,7 +13689,7 @@ static size_t llama_output_reserve(llama_context & lctx, size_t n_outputs) {
     const auto n_embd  = hparams.n_embd;
 
     // TODO: use a per-batch flag for logits presence instead
-    const bool has_logits = !cparams.embeddings;
+    const bool has_logits =  cparams.causal_attn;
     const bool has_embd   =  lctx.is_encoding || (cparams.embeddings && (cparams.pooling_type == LLAMA_POOLING_TYPE_NONE));
 
     const size_t logits_size = has_logits ? n_vocab*n_outputs_max : 0;
@@ -13959,17 +13959,25 @@ static int llama_decode_internal(
             // no output
             res  = nullptr;
             embd = nullptr;
-        } else if (cparams.embeddings) {
-            res = nullptr; // do not extract logits for embedding case
-            embd = gf->nodes[gf->n_nodes - 1];
-            if (strcmp(embd->name, "result_embd_pooled") != 0) {
-                embd = gf->nodes[gf->n_nodes - 2];
+        }
+
+        if (cparams.embeddings) {
+            for (int i = gf->n_nodes - 1; i >= 0; --i) {
+                embd = gf->nodes[i];
+                if (strcmp(embd->name, "result_embd_pooled") == 0) {
+                    break;
+                }
             }
             GGML_ASSERT(strcmp(embd->name, "result_embd_pooled") == 0 && "missing embeddings tensor");
-        } else {
+         } else {
             embd = nullptr; // do not extract embeddings when not needed
             GGML_ASSERT(strcmp(res->name, "result_output") == 0 && "missing result_output tensor");
         }
+
+        if (!cparams.causal_attn) {
+            res = nullptr; // do not extract logits when not needed
+        }
+
         // LLAMA_LOG_INFO("graph build time: %.3f ms (%d nodes, %d leafs)\n", (ggml_time_us() - t_start_us)/1000.0, gf->n_nodes, gf->n_leafs);
 
         ggml_backend_sched_alloc_graph(lctx.sched, gf);