diff --git a/server-rs/crates/api-server/src/editor_screen_background_decision.rs b/server-rs/crates/api-server/src/editor_screen_background_decision.rs
index 1762e3e92..48c47c27f 100644
--- a/server-rs/crates/api-server/src/editor_screen_background_decision.rs
+++ b/server-rs/crates/api-server/src/editor_screen_background_decision.rs
@@ -152,9 +152,9 @@ pub(crate) async fn resolve_editor_screen_background_color(
             None => LlmMessage::user(user_prompt.as_str()),
         };
         // 预算要够推理模型（如 gpt-5-mini）先花几百 token 推理、再吐 JSON 答案；
-        // 实测 low 档推理约 320~384 token，取 768 留足余量。非推理模型遇 stop 提前结束，不会多花。
+        // 实测 low 档推理约 320~384 token，取 1024 留足余量。非推理模型遇 stop 提前结束，不会多花。
         let mut request = LlmTextRequest::new(vec![LlmMessage::system(system_prompt), user_message])
-            .with_max_tokens(768)
+            .with_max_tokens(1024)
             .with_request_timeout_ms(EDITOR_SCREEN_BACKGROUND_DECISION_TIMEOUT_MS);
         if let Some(vision_model) = vision_model {
             // 视觉模型 gpt-5-mini 是推理模型：走 Responses 协议并压到 low 推理档，