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The box is physically at Fountain Valley, renamed, renumbered onto 10.251/16, and serving inference again. This lands the repo half of that. Host: hostname ana-ml2 -> fv-ml1, pinned to 10.251.50.54 by a dnsmasq reservation so the address the runbook, DNS and LiteLLM all assume is the address it actually has. Its headscale node is renamed too. The sweep ran from scripts/fv-ml1-rename-sweep.sh, whose allowlist is the reason this diff touches current-state files and not the record. Dated persistent-memory entries, archival-memory and incident notes still say ana-ml2 in 31 and 62 places respectively, because that is what the box was when those things happened. Rewriting them would make the history lie. LiteLLM was the load-bearing piece and needed more than the api_base sed the runbook describes. Twenty api_base entries repointed, but a grep-and-verify pass also caught a LIVE pass_through_endpoints target for the scalar-judge reward route still on the old address -- an api_base-only substitution would have left it dead. Four prose references describing current state were repointed as well; one historical note recording where a hand-test was run is deliberately left pointing at 10.250.50.54. Two facts in the server tables were wrong and are corrected here. The site is Fountain Valley, not Anaheim. And the box has FOUR RTX PRO 6000 Blackwell Max-Q, not two -- verified by nvidia-smi -L and independently by PCI enumeration of four GB202GL devices. That is 391 GB of VRAM rather than 196, which changes what fits on it. DNS: fv-ml1, fv-ml1-bmc and fv-gw added under the fv site via the piggyback approach, scriberr re-homed, and the ana-ml2 records removed. Applied to all three resolvers. The BMC record carries a warning that its 802.1q VLAN tag must stay disabled -- it shipped tagging VLAN 250 into an untagged port, which made it invisible to every network-side diagnostic and is the reason it appeared dead through several cable changes. Verified end to end: summarizer and sec both answer through the Anaheim gateway across the mesh to FV seats on different ports.
sglang — vLLM-vs-SGLang bench on ana-ml2
Stood up to benchmark SGLang against vLLM on the same model + hardware, to see whether SGLang's throughput/latency wins justify it as a serving option (or a replacement) for the granite path on the Blackwells.
Bench-oriented, not a permanent service (yet). If SGLang wins decisively → promote to a real stack + add a gateway entry. Otherwise tear it down after.
Capability (checked 2026-06-13)
SGLang 0.5.13 (torch 2.11+cu130) supports our formats on Blackwell sm_120:
compressed-tensors (the llm-compressor NVFP4 W4A4 output), fp8,
modelopt_fp4, petit_nvfp4, mxfp4, and fp4_e2m1 KV. So the bench can be a
real NVFP4 head-to-head, not just FP8.
The one rule for a fair bench
Exclusive GPU, same everything. Both engines must run on a card with NO
co-tenants (no eval endpoints, no llama-swap hot-load), same model, same context
length, same prompt profile, same concurrency sweep, driven by the SAME load
generator (bench.py) — not each engine's self-flattering built-in benchmark.
The contention that skewed the earlier vLLM throughput probe is exactly what to
avoid here.
Run
# 1. On ana-ml2, after the eval frees a GPU: cp .env.example .env, set
# SGLANG_MODEL / SGLANG_QUANT to match the vLLM config under test, and
# SGLANG_GPU_ID to an EXCLUSIVE card.
scripts/deploy-stack.sh ana-ml2 sglang
# (or docker compose up -d on the host)
# 2. Bench SGLang:
python3 stacks/sglang/bench.py --url http://10.250.50.54:30000/v1 \
--model granite-4.1-8b-nvfp4 --concurrency 1 10 50 100 200 --in-tokens 2048 --out-tokens 256
# 3. Stop SGLang, bring up vLLM on the SAME GPU + model, bench identically:
python3 stacks/sglang/bench.py --url http://10.250.50.54:8006/v1 \
--model granite-4.1-8b-nvfp4 --concurrency 1 10 50 100 200 --in-tokens 2048 --out-tokens 256
# 4. Repeat the sweep at --in-tokens 30000 (the prefill-heavy agent-memory
# regime, where the engines can diverge sharply).
Metrics (bench.py reports)
- agg_tok/s — aggregate output throughput at concurrency N (the headline)
- ttft_p50 / p99 — time-to-first-token (prefill latency; matters most at high in-tokens)
- tpot_ms — time-per-output-token (decode latency; the per-stream UX number)
mem-fraction-static is SGLang's gpu-memory-utilization analog; set it high
(0.85–0.90) on an exclusive 96 GB card.
Bench target
Bench whichever format wins Brokkr's quality eval (the production-relevant one): 8B-NVFP4-W4A4 if that's the path, else FP8. Benching a format we won't ship is academic. Optionally run both formats to see if the engine ranking flips.