Files
serverAppConfigs/serverAppConfigs-docs/LLM/ubatch-benchmark-large.md
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Frank 55f87fcdce llm: retire the trio service names — fleet services renamed to frank-archon/frank-dragoon/frank-zealot
The 2026-10-09 wire aliases become the service names everywhere:
systemd units, serve scripts, env files and FRANK_* variables,
deploy-plan/deploy-remote service keys, container names, Prometheus
job names + alert rules, Grafana dashboard queries, bats seams,
runbook filenames, homepage/AGENTS lore, and historical prose.
Rollback tags renamed in lockstep. Residue in the tree: zero.
Retired frank-medium/small/npu names are history and stay.

Known casualty: scripts/patches/*.patch context lines were rewritten;
those retired-era vLLM-fork patches no longer apply byte-exact.
2026-10-10 17:03:14 -07:00

1.6 KiB

type, title, description, tags, timestamp
type title description tags timestamp
benchmark plan frank-dragoon ubatch sweep Standardized ubatch sweep for the active kingjones Qwen3.8 ROCmFPX deployment.
llama.cpp
rocm
benchmark
ubatch
2026-09-01

frank-dragoon ubatch sweep

This benchmark uses the active frank-dragoon model on Dankclaw with llama-bench. It does not use llama-server, HTTP requests, or server-log scraping. Stop the production service before running it and start the service again afterward.

The old custom harnesses are retained in .AGENTTRASH/bench-scripts-20260901/ for auditability only. Their results are invalid and must not be used.

Sweep

The requested points are 256, 512, 768, 1024, 1280, 1536, 1792, 2048, 3072, 4096 at 8K context, with batch equal to ubatch at every point. Each point runs three 128-token repetitions by default.

Run on Dankclaw from the repository checkout:

sudo systemctl stop frank-dragoon
./scripts/bench-ubatch.sh
sudo systemctl start frank-dragoon

The script uses the active Q6 AGENT model, an 8K prompt workload, equal batch and ubatch values, and llama-bench JSONL output. The sweep is:

256, 512, 768, 1024, 1280, 1536, 1792, 2048, 3072, 4096

The GPU is shared with live workloads; do not run with the production service up.

Results

No valid results are recorded here. All results from the retired custom harnesses are explicitly discarded. Record the raw llama-bench JSONL output from the new harness here after a clean run.

See also