Benchmark numbers for LLM serving are usually a single average tokens-per-second figure, measured by whoever is selling something, with the denominator left undefined. These projects exist because measuring properly — per token, per regime, per request, under load — turned out to be worth the effort of building the instrument first.
VeloBenchmark is the flagship: a single-binary benchmarking and live-stats console for any OpenAI-compatible endpoint. It began as the question “what is this server actually doing per token?” and grew into chat instrumentation, repeatable test suites, a concurrent runner, session reports, comparisons, and an OTLP telemetry receiver that can sit in front of a serving engine's own OpenTelemetry stream.
veloGB10 is the engine side: a from-scratch Rust + CUDA inference engine for NVIDIA GB10 systems (DGX Spark and compatible OEM boxes), where ~255 GB/s of memory bandwidth is the scarce resource and every design decision is subordinate to spending it well. It emits the OpenTelemetry stream that VeloBenchmark's receiver was built to consume — the two projects measure and serve the same reality, and each one's docs reference the other.
VeloBenchmark is AGPL-3.0: free to use, modify, and deploy, including commercially; network deployments of modified versions share their source. That is a deliberate choice for a measurement tool — the methodology stays inspectable by the people whose decisions it informs. veloGB10 is Apache-2.0. Paid work (integration, extensions, tuning, support, and commercial licences where the AGPL does not fit) is described on the services page; none of it gates the software itself.
Both projects are developed with strong assistance from open-source LLMs, under experienced human technical direction — architecture decisions, ideas, testing and extensive debugging included — and this is stated openly because it shaped how they were built. Every performance figure is gated or measured on physical hardware; where a number is an estimate, the docs say so. The acknowledgement matters in both directions: none of this exists without the kernels, formats, and hard-won engineering knowledge of the wider open ecosystem.
Both projects are written and maintained by Stav Katsoulis (sf-stav) — kernels, scheduler, transport, gates, console, docs and releases. Bug reports and well-formed issues are always free and welcome; contracted work is quoted per request. The shortest path to a human is stav@scalarflow.co.uk.