Lumbridge Compute: telemetry and four-lane operations

2026-08-31 16:09:08 -07:00
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+apiVersion: lumbridge/v1
+kind: Scene
+metadata:
+  name: qwen38-dspark
+  version: 1
+  description: "qwen38-mia tuning with the DSpark speculative stack (code/tool-call optimised)."
+  author: karti
+  tags: [brain, vision, voice, sglang, dspark, benchmark]
+
+# Same model set and same MiaAI-Lab tuning as `qwen38-mia`; only the
+# speculative stack differs (EAGLE/MTP -> DSpark) plus torch.compile and
+# continuous-decode-steps 2.
+#
+# Benchmark with MiaAI-Lab's own net-decode harness, NOT the prose `performance`
+# suite: python3 /tmp/ndec_ours.py
+#   qwen38-mia (EAGLE) baseline: code 31.60 / prose 23.97 tok/s
+#   MiaAI-Lab reports for DSpark: code 51.5 / prose 18.3
+#
+# DSpark is faster on code/math/tool-calls and SLOWER on free-form prose, so
+# check both probes before adopting — the squawk/news path is prose.
+#
+# Same swap discipline as every other scene: kill stale `scene activate`,
+# deactivate, wait for free -g >= 110 GB, activate, then activate again to
+# persist desired.
+models:
+  - brain-qwen38-dspark
+  - ears
+  - voice-vox
+  - voice
+
+budget_gb: 100
+activation:
+  order: listed
+  wait_healthy: true