diff --git a/README.md b/README.md
index 4a7a715..20f80e8 100644
--- a/README.md
+++ b/README.md
@@ -1,5 +1,9 @@
 # sskj — 多平台大模型推理性能基准测试项目
 
+> **更新（2026-07-31 00:11:25 CST）**
+>
+> 完成 DeepSeek-V4-Pro 双机 Pro6000D SGLang TP16 的长 Decode 补测，Run `dsv4pro-phase1-long-decode-20260730-234236` 结果 2/2 成功。`1K → 4K, C=16` 生成 65,536 个目标输出 token，Output TPS 为 310.02，TPOT P95 为 50.33 ms；相比 `1K → 1K, C=16`，Output TPS 增加 4.99%，TPOT P95 仅增加 0.62%。`128K → 1K, C=1` 生成完整 1,024 token，TTFT P95 为 49.326 s，TPOT P95 为 32.24 ms；其 TTFT 与 `128K → 1` 纯 Prefill 仅差 2.03%，TPOT P95 相比 1K Context 仅增加 2.47%。Phase 1 至此共完成 11 个固定点和 3 个混合结果，14/14 成功；两节点容器和 16 张 GPU 已清理。
+>
 > **更新（2026-07-30 23:38:42 CST）**
 >
 > 为 DeepSeek-V4-Pro 双机 Pro6000D SGLang TP16 Phase 1 增加两个最小长 Decode 补充场景：`1K → 4K, C=16` 用于观察持续长输出、KV 增长与稳态 Decode，`128K → 1K, C=1` 用于观察长上下文上的 Decode Attention。继续复用唯一 `run_quick_map.sh` 入口和 `CASE_IDS` 过滤，不新增启动脚本；场景验证单测由 9 点更新为 11 点，Shell、3 个 Python 单测和两点 Dry-run 已通过。
diff --git a/experiments/pro6000/dsv4pro_pro6000d_2node_sglang_tp16_quick_map/README.md b/experiments/pro6000/dsv4pro_pro6000d_2node_sglang_tp16_quick_map/README.md
index 9e9adf8..1c8d716 100644
--- a/experiments/pro6000/dsv4pro_pro6000d_2node_sglang_tp16_quick_map/README.md
+++ b/experiments/pro6000/dsv4pro_pro6000d_2node_sglang_tp16_quick_map/README.md
@@ -38,6 +38,38 @@ The same main entry also runs a mixed-interference A/B:
 This aggregate mixed test is sufficient for the first performance-map pass. Per-request time-series
 attribution belongs to the later scheduler/interference phase.
 
+## Verified Phase 1 results
+
+The no-profiler baseline completed in two runs over the same TP16 service
+configuration and the same dual-rail `NET/IB + GDRDMA` gate:
+
+| Run | Result | Scope |
+|---|---:|---|
+| `dsv4pro-phase1-full-20260730-220916` | 12/12 | 9 fixed points and 3 mixed A/B outputs |
+| `dsv4pro-phase1-long-decode-20260730-234236` | 2/2 | Long-output and long-context Decode |
+
+The long-Decode supplement produced every configured output token:
+
+| Case | Output tokens | Output TPS | TTFT P95 | TPOT P95 | E2E P95 |
+|---|---:|---:|---:|---:|---:|
+| `1K -> 4K, C=16` | 65,536 | 310.02 | 6.241 s | 50.33 ms | 211.364 s |
+| `128K -> 1K, C=1` | 1,024 | 12.43 | 49.326 s | 32.24 ms | 82.312 s |
+
+Compared with `1K -> 1K, C=16`, the long-output case improved aggregate
+Output TPS by 4.99% while TPOT P95 changed by only +0.62%. The longer measured
+Decode interval amortized fixed startup and Prefill costs; no sustained-Decode
+throughput collapse was observed.
+
+For `128K -> 1K, C=1`, TTFT was only 2.03% above the `128K -> 1` Prefill-only
+case, while TPOT P95 was only 2.47% above `1K -> 1K, C=1`. In this run, the
+large added latency came mainly from Prefill. Its 12.43 Output TPS includes the
+49-second Prefill in benchmark duration and is not a pure Decode-rate metric.
+
+Phase 1 therefore closes at 11/11 fixed points plus 3/3 mixed results. The next
+diagnostic stage should collect aligned GPU, CPU, SGLang scheduler and dual-rail
+RDMA time series for Prefill, ordinary Decode, sustained Decode, long-context
+Decode and the mixed A/B.
+
 ## Files
 
 | File | Purpose |
@@ -139,8 +171,9 @@ inside ignored result directories and are not committed.
 - Quick default: one repetition and one measured request wave
   (`num_prompts=C`, including one request when `C=1`).
 - Milestone: three repetitions.
-- Short Prefill and Decode cases use one warm-up request. Expensive 32K/128K
-  Prefill cases do not add a same-shape warm-up.
+- Short Prefill, ordinary Decode and `1K -> 4K` long-output Decode use one
+  warm-up request. Expensive 32K/128K Prefill and `128K -> 1K` long-context
+  Decode do not add a same-shape warm-up.
 - Every isolated point calls SGLang benchmark with `--flush-cache`; the benchmark
   performs its warm-up first and then clears the server Prefix Cache before
   measured requests.