diff --git a/src/llama-context.cpp b/src/llama-context.cpp
index f7c83e886..4341c571e 100644
--- a/src/llama-context.cpp
+++ b/src/llama-context.cpp
@@ -4673,6 +4673,7 @@ int llama_context_enc::encode(llama_batch & inp_batch) {
     ggml_backend_sched_reset(sched.get());
 
     cross->t_embd = t_embd;
+    cross->v_embd = embd;
 
     // remember the sequence ids used during the encoding - needed for cross attention later
     cross->seq_ids_enc.resize(n_tokens);
@@ -4701,12 +4702,11 @@ void llama_context_dec::input_set(const llama_ubatch & ubatch) {
     // call base functionality
     llama_context_kv_self::input_set(ubatch);
 
-    //if (inp.cross_embd && inp.cross_embd->op != GGML_OP_NONE) {
-    //    assert(inp.cross_embd->type == GGML_TYPE_F32);
-    //    assert(ggml_nelements(inp.cross_embd) == cross->n_outputs*model.hparams.n_embd);
+    if (inp.cross_embd && cross->t_embd) {
+        assert(inp.cross_embd->type == GGML_TYPE_F32);
 
-    //    ggml_backend_tensor_set(inp.cross_embd, cross->embd_enc, 0, ggml_nbytes(inp.cross_embd));
-    //}
+        ggml_backend_tensor_set(inp.cross_embd, cross->v_embd, 0, ggml_nbytes(inp.cross_embd));
+    }
 
     if (inp.cross_kq_mask) {
         const int64_t n_enc    = inp.cross_kq_mask->ne[0];
@@ -4749,16 +4749,17 @@ ggml_cgraph * llama_context_dec::graph_init() {
 ggml_tensor * llama_context_dec::build_inp_cross_embd(
         ggml_context * ctx0) {
     // if we have the output embeddings from the encoder, use them directly
-    if (cross->t_embd) {
-        inp.cross_embd = ggml_view_tensor(ctx0, cross->t_embd);
+    // TODO: needs more work to be correct, for now just use the tensor shape
+    //if (cross->t_embd) {
+    //    inp.cross_embd = ggml_view_tensor(ctx0, cross->t_embd);
 
-        return inp.cross_embd;
-    }
+    //    return inp.cross_embd;
+    //}
 
     const auto & hparams = model.hparams;
 
-    const auto n_embd = hparams.n_embd;
-    const auto n_enc  = hparams.n_ctx_train;
+    const auto n_embd = cross->t_embd ? cross->t_embd->ne[0] : hparams.n_embd;
+    const auto n_enc  = cross->t_embd ? cross->t_embd->ne[1] : hparams.n_ctx_train;
 
     inp.cross_embd = ggml_new_tensor_2d(ctx0, GGML_TYPE_F32, n_embd, n_enc);
     ggml_set_input(inp.cross_embd);
diff --git a/src/llama-context.h b/src/llama-context.h
index af35b577b..1b807ccf8 100644
--- a/src/llama-context.h
+++ b/src/llama-context.h
@@ -750,9 +750,14 @@ private:
 
 // TODO: tmp - need something better to pass the data from the encoder to the decoder
 struct llama_cross {
-    // the output embeddings from the encoder
+    // the output embeddings from the encoder as a ggml tensor
+    // TODO: this needs more work to be correct, for now copy the embeddings data to host memory
+    //       ref: https://github.com/ggml-org/llama.cpp/pull/11213#discussion_r1969892524
     ggml_tensor * t_embd = nullptr;
 
+    // embeddings data copied to host memory (tmp)
+    float * v_embd = nullptr;
+
     // needed to construct the cross-attention mask in the decoder
     std::vector<std::set<llama_seq_id>> seq_ids_enc;
 };