chore(sweep): re-run MiniMax-M2.5 vLLM sweeps to capture power telemetry

Re-runs the MiniMax-M2.5 single-node vLLM configs (H100/H200 FP8,
B200/B300/MI355X FP4) with no recipe change, so the new rows carry the
per-GPU power telemetry (avg_power_w) added in #1558. The power/energy
canvas currently models power because its source rows predate the
2026-05-27 capture merge; this re-run lets it use measured power.

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

Author: arygupt

perf-changelog.yaml

@@ -3474,3 +3474,14 @@
     - "Use scheduler-recv-interval values 2/60/30/1200/600/1920 for conc 1-4/8/16/32/64/128-256"
     - "Set max-running-requests=256, chunked-prefill-size=16384, mem-fraction-static=0.8, cuda-graph-max-bs=CONC, and enable symm-mem"
   pr-link: https://github.com/SemiAnalysisAI/InferenceX/pull/1544
+
+- config-keys:
+    - minimaxm2.5-fp8-h100-vllm
+    - minimaxm2.5-fp8-h200-vllm
+    - minimaxm2.5-fp4-b200-vllm
+    - minimaxm2.5-fp4-b300-vllm
+    - minimaxm2.5-fp4-mi355x-vllm
+  description:
+    - "Re-run MiniMax-M2.5 single-node vLLM sweeps (H100/H200 FP8, B200/B300/MI355X FP4) with no recipe change, to capture per-GPU power telemetry (avg_power_w) added in #1558 for the power/energy canvas"
+    - "Source rows for the canvas predate the 2026-05-27 power-capture merge, so they carry throughput/latency but no measured power; this re-run replaces the modeled power layer with measured power"
+  pr-link: https://github.com/SemiAnalysisAI/InferenceX/pull/XXX