Speed: auto flash-attention/SDPA + document perf levers

transformers .generate() is the slow path; reasoning token volume and swap_eval
(2 passes) are the multipliers. Now requests attn_implementation flash_attention_2
-> sdpa -> default automatically (free speedup, flash-attn optional). README gains
a Performance section: swap_eval off (biggest free win), flash-attn, smaller model/
fewer axes, avoid nf4 for speed, and vLLM/SGLang as the real production-speed path.

Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>

README.md

@@ -59,6 +59,22 @@ and read the model's text from the `analysis` output. Reuses the same model drop
 and auto-download as the judge, so it's a one-node abliterated VLM for captioning, tagging,
 Q&A, prompt-from-image, etc. (CLI: `agent_bridge.py --mode chat --user-prompt "..."`).
 
+## Performance / speed
+
+This node runs models through **transformers `.generate()`** — the simplest path, but the
+**slowest**: no PagedAttention / continuous batching / fused kernels like vLLM, SGLang, or
+llama.cpp. With `enable_thinking` on, the model also emits thousands of reasoning tokens
+(each token = one forward pass) — that's the cost of accurate verdicts. Levers, fastest first:
+
+- **`swap_eval = false`** — halves the work (one reasoned pass instead of two). Biggest free win.
+- **flash-attention** — the node auto-uses `flash_attention_2` if `flash-attn` is installed, else `sdpa`. `pip install flash-attn` for the speedup.
+- **smaller model / fewer axes** — Qwen3.5-9B bf16 over the 27B/35B; trim `axes` or use a focused `profile`.
+- **`enable_thinking = false`** — much faster, but reasoning models then rubber-stamp `match`; only for quick smoke tests.
+- **avoid `nf4`** for speed — bitsandbytes dequantizes every step; `bf16`/`fp8` decode faster (nf4 is for *fitting* the big models, not speed).
+
+The real fix for production speed is a different inference engine (vLLM/SGLang serve these
+models many× faster) — a heavier, separate-server setup not built into this node.
+
 **Outputs**
 
 | name | type | use |