docs: add qwen235b prefill 7-day compare

docs/qwen235b-thinking-prefill/7day-compare.md

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+# qwen235b-thinking-prefill-7day-compare
+
+qwen3-235b-a22b `thinking` trace, prefill-only replay with `output_length=1`, comparing 3 configs across 7 daily `10:00-10:10` windows by `request_rate_per_gpu`.
+
+## Setup
+
+- Hardware: `dash1`, `8x H20`
+- Model: `/home/admin/resource/model/464482ce.qwen3-235b-a22b/256k-0717`
+- Engine: internal vLLM, baseline aligned to `~/run_qwen235b.sh`
+- Trace set: `thinking_w20260321_1000` to `thinking_w20260327_1000`
+- Window duration: `600s` each
+- Request mode: `chat`
+- Replay override: `min_tokens=max_tokens=1`
+- SLO:
+  - pass target: `95%`
+  - `TTFT <= 2000ms` for `<=8191` input tokens
+  - `TTFT <= 4000ms` for `<=32767` input tokens
+  - `TTFT <= 6000ms` for `>32767` input tokens
+- Search:
+  - each candidate independently binary-searches its own `sampling_u`
+  - `sampling_u in [0, 0.125]`
+  - `max_probes = 6`
+
+## Candidates
+
+- `baseline`
+  - `TP=4, DP=1, EP=off`
+  - baseline `run_qwen235b.sh` shape
+- `tuned_0323`
+  - tuned on `thinking_w20260323_1000`
+  - `TP=4, DP=1, EP=off`
+  - `max-num-batched-tokens=3072`
+  - `max-num-seqs=32`
+- `tuned_0327`
+  - tuned on `thinking_w20260327_1000`
+  - `TP=8, DP=1, EP=off`
+  - `max-num-batched-tokens=6144`
+  - `max-num-seqs=48`
+  - `block-size=32`
+
+## Run assets
+
+- Compare root: `/home/admin/cpfs/wjh/aituner/aituner/.aituner-compare/dash1-qwen235b-prefill-thinking-7day-baseline-vs-0323-vs-0327`
+- Summary: `/home/admin/cpfs/wjh/aituner/aituner/.aituner-compare/dash1-qwen235b-prefill-thinking-7day-baseline-vs-0323-vs-0327/summary.json`
+- Report: `/home/admin/cpfs/wjh/aituner/aituner/.aituner-compare/dash1-qwen235b-prefill-thinking-7day-baseline-vs-0323-vs-0327/report.md`
+- Compare spec: `/home/admin/cpfs/wjh/aituner/aituner/configs/examples/dash1_qwen235b_prefill_thinking_7day_compare.json`
+
+## Aggregate result
+
+- Wins by `request_rate_per_gpu`:
+  - `tuned_0327`: `5 / 7`
+  - `baseline`: `2 / 7`
+  - `tuned_0323`: `0 / 7`
+- Mean `request_rate_per_gpu`:
+  - `baseline`: `0.13845`
+  - `tuned_0323`: `0.12756`
+  - `tuned_0327`: `0.17232`
+- Relative to baseline:
+  - `tuned_0323`: `0.92x` mean per-GPU throughput
+  - `tuned_0327`: `1.24x` mean per-GPU throughput
+
+## Per-day result
+
+| Date | baseline req/s/gpu | tuned_0323 req/s/gpu | tuned_0327 req/s/gpu | Winner |
+| --- | ---: | ---: | ---: | --- |
+| `2026-03-21` | `0.08500` | `0.03917` | `0.14375` | `tuned_0327` |
+| `2026-03-22` | `0.10125` | `0.12083` | `0.15313` | `tuned_0327` |
+| `2026-03-23` | `0.12792` | `0.12792` | `0.19167` | `tuned_0327` |
+| `2026-03-24` | `0.09000` | `0.09583` | `0.11250` | `tuned_0327` |
+| `2026-03-25` | `0.13792` | `0.13208` | `0.13146` | `baseline` |
+| `2026-03-26` | `0.32000` | `0.25917` | `0.23375` | `baseline` |
+| `2026-03-27` | `0.10708` | `0.11792` | `0.24000` | `tuned_0327` |
+
+## Key takeaways
+
+- `tuned_0327` is the only candidate with clear cross-day value. It wins `5/7` windows and improves mean per-GPU throughput by about `24%`.
+- `tuned_0323` does not generalize. It is slightly more conservative and keeps high pass rate, but mean per-GPU throughput is below baseline.
+- The `0327` winner is not universal. On `2026-03-25` and especially `2026-03-26`, the 4-GPU baseline is more efficient per GPU than the `TP8` tuned shape.
+- The practical reading is that prefill-only tuning has workload-regime sensitivity. `TP8 + 6144 + 48 + block-size=32` is a strong default candidate, but not a global static optimum across all days.