[Cookbook] Laguna-M.1: enable FP8 on Blackwell + drop provisional AIME numbers (#28664)

docs_new/cookbook/autoregressive/Poolside/Laguna-M.1.mdx

@@ -110,7 +110,7 @@ import { Playground } from "/src/snippets/_playground.jsx";
 ## 2. Configuration Tips
 
 - **Long-context memory**: M.1 is global-attention (no sliding-window), so the 262,144-token KV cache is large. If you hit OOM at full context, lower `--mem-fraction-static` or cap `--context-length`.
-- **FP8 first launch**: FP8 triggers a multi-session DeepGEMM JIT pre-compile on first launch; pre-warm with `python3 -m sglang.compile_deep_gemm --model poolside/Laguna-M.1-FP8` to avoid paying it on every restart.
+- **FP8**: On **Blackwell** the recipe adds `--fp8-gemm-backend triton` — the compressed-tensors block-FP8 weight scales aren't UE8M0-packed, so the default DeepGEMM path emits garbage on Blackwell (sm_100); the Triton backend is correct (~19% slower). Temporary workaround pending [PR #28662](https://github.com/sgl-project/sglang/pull/28662) (which fixes the scales and restores the DeepGEMM fast path). On **Hopper (H200)** FP8 uses DeepGEMM with no extra flag — pre-warm its multi-session JIT with `python3 -m sglang.compile_deep_gemm --model poolside/Laguna-M.1-FP8` to avoid paying it on each restart.
 - **Parsers** (`poolside_v1`): for agentic / tool-using deployments enable the **Reasoning Parser** and **Tool Call Parser** in the Playground above — they emit `--reasoning-parser poolside_v1` (thinking → `reasoning_content`) and `--tool-call-parser poolside_v1` (structured `tool_calls`).
 - **Thinking default**: thinking is **off by default**; opt in per request with `extra_body={"chat_template_kwargs": {"enable_thinking": True}}`.
 - **Served model id**: the server registers the model under whatever you pass to `--model-path`, so a client's `model` field must match it — `poolside/Laguna-M.1` (BF16) or `poolside/Laguna-M.1-FP8` / `-NVFP4` for the quantized cells. The §3 examples use the BF16 id; swap in the id you launched.