diff --git a/llm/ext_server/server.cpp b/llm/ext_server/server.cpp
index 7b281977..318b581a 100644
--- a/llm/ext_server/server.cpp
+++ b/llm/ext_server/server.cpp
@@ -1032,18 +1032,6 @@ struct llama_server_context
 
     bool process_images(server_slot &slot) const
     {
-        // Set cross attention state for mllama models
-        // TODO (jmorganca): this should be provided via the API
-        // TODO (jmorganca): generalize this beyond mllama models
-        char arch_str[256];
-        llama_model_meta_val_str(model, "general.architecture", arch_str, 256);
-        if (strcmp(arch_str, "mllama") == 0) {
-            // TODO (jmorganca): this should be passed in via the llama_decode api
-            // or similar, maybe using the llama_batch struct
-            // llama_reset_cross_attn_state(ctx);
-            // llama_set_cross_attn_state(ctx, (float*)cross_attn_state);
-        }
-
         for (slot_image &img : slot.images)
         {
             if (!img.request_encode_image)
@@ -1258,6 +1246,17 @@ struct llama_server_context
         task.type = TASK_TYPE_COMPLETION;
         task.multitask_id = multitask_id;
 
+        // Set cross attention state for mllama models
+        // TODO (jmorganca): this should be provided via the API
+        // TODO (jmorganca): generalize this beyond mllama models
+        char arch_str[256];
+        llama_model_meta_val_str(model, "general.architecture", arch_str, 256);
+        if (strcmp(arch_str, "mllama") == 0) {
+            // TODO (jmorganca): this should be passed in via the llama_decode api
+            // or similar, maybe using the llama_batch struct
+            // llama_set_cross_attn_state(ctx, (float*)cross_attn_state);
+        }
+
         // when a completion task's prompt array is not a singleton, we split it into multiple requests
         // otherwise, it's a single-prompt task, we actually queue it
         // if there's numbers in the prompt array it will be treated as an array of tokens