diff --git a/recipes/glm-5-3-flash-4x170hx-tp4-pp4-morrowmake-141/recipe.yaml b/recipes/glm-5-3-flash-4x170hx-tp4-pp4-morrowmake-141/recipe.yaml
index 2955e3087..f7e121534 100644
--- a/recipes/glm-5-3-flash-4x170hx-tp4-pp4-morrowmake-141/recipe.yaml
+++ b/recipes/glm-5-3-flash-4x170hx-tp4-pp4-morrowmake-141/recipe.yaml
@@ -79,7 +79,7 @@ performance:
     tok_s: 264.4
     ttft_ms: 63
     context_len: 262144
-    notes: 'T1 measured by the recipe author (release 1.4.1, 180 W/card, PCIe x16, temperature 0, median of 5): TP4 single-user 264.4 structured / 258.5 code / 189.9 prose; 8-user aggregate 763.1/684.7/512.0; cold prefill 2670 (TP4) / 6254 (PP4); TTFT 63 ms (TP4) on a 400-token prompt; KV pool 1,156,635 (TP4) / 2,320,328 (PP4). Quality: GSM8K 0.972, HumanEval 0.9634, PPL 3.2781.'
+    notes: 'T1 measured by the recipe author, release 1.8.0 (docs/results.md @ v1.8.0, measured 2026-10-16, engine 819146023f, 74 SMs/card, 180 W/card, PCIe x16, 262,144 ctx, temperature 0): 1-user decode = median of five streaming decode rates on ONE boot (1.7.x protocol was ten rates over two boots); scoring is on the answer after the reasoning (content) for both releases. TP4 1 user structured / code / prose 482.6 / 442.1 / 232.1 tok/s; 2-user aggregate 606.5 / 460.3 / 314.7; 4-user 717.7 / 618.7 / 501.4; 8-user 943.7 / 835.0 / 667.2; TP4 cold prefill 3,161 tok/s; KV pool 1,203,765 tokens at 262,144 (4.59 full-length). PP4 1 user 232.4 / 209.9 / 100.1; 2-user 343.8 / 273.4 / 195.5; 4-user 409.2 / 382.8 / 314.2; 8-user 664.1 / 608.8 / 469.2; PP4 cold prefill 7,419 tok/s; KV pool 2,088,960 tokens (7.97 full-length). Quality TP4: HumanEval 151/164, GSM8K 1,286/1,319 (1.7.2 re-scored the same way: 154/164, 1,284/1,319; neither suite significant, McNemar p=0.45 / 0.75). KL 1.8.0 vs 1.7.2: TP4 0.0158 short / 0.0083 long; PP4 0.0000 / 0.00014. The author publishes a vs-1.7.2-published column (1.7.2 published TP4 1-user 482.2 / 447.7 / 210.6; cold prefill 3,197; KV pool 1,199,570) — each column its own session, labelled published-vs-published, not a side-by-side run. Historical benchmark points on this recipe are 1.4.1/1.7.2-era measurements and keep their own attribution.'
 artifacts:
   -
     kind: model_weights