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4 posts tagged with "LLM latency"

Measured latency of LLMOps platforms and the overhead a gateway adds to a model call.

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Laminar alternative: SQL over traces vs a prompt gateway

· 22 min read
LLM-ops platform

Laminar (lmnr) is a Y Combinator S24 project that calls itself observability purpose-built for AI agents — a Rust ingest server, ClickHouse for spans, Quickwit for search, and an OpenTelemetry SDK that instruments fifteen-plus agent frameworks from one line of code — Vercel AI SDK, Claude Agent SDK, OpenAI Agents SDK, LangChain DeepAgents, Mastra, Pydantic AI, Browser Use, Stagehand, Playwright, LiteLLM, OpenCode and OpenHands among them. It is the most differently shaped tool we have compared AcruxCore against. Its project sidebar has dashboards, traces, evaluations, datasets, labeling, a SQL editor, playgrounds, a debugger and settings — and no prompt registry anywhere. That is not an oversight; it is the product being about agent runs rather than about the calls inside them. Both projects are Apache 2.0, so this is a comparison of shape, not of who is open.

Full-cycle latency across six LLM-ops platforms, measured against real OpenAI

· 16 min read
LLM-ops platform

Every latency number we'd published before this measured one thing: the completion call. But a real request to any of these platforms is usually two round trips — fetch or resolve a stored prompt, then complete it — and most of them were benchmarked against OpenRouter, not the provider whose name is on the model.

So this one measures the full cycle, on real OpenAI billing, across all six platforms plus both of AcruxCore's calling modes — eight paths in one interleaved run. We also ran it four independent times, because a single 100-round run against a live third-party API turned out to not be enough to trust a single number, and that's worth showing rather than hiding.

Exact-match gateway caching: latency and cost saved

· 5 min read
LLM-ops platform

A gateway virtual key can be given a cache window: set cacheTtlSeconds and an exact-match repeat of a call — same model, same messages, same temperature/max_tokens/top_p/stop — is served from Postgres instead of the provider. We ran the same fixed set of prompts through it repeatedly to see what a hit is actually worth, in milliseconds and in dollars.

How much overhead does an LLM gateway add?

· 8 min read
LLM-ops platform

Putting a gateway in front of your model providers buys you a lot: one endpoint for every provider, cost accounting, caching, virtual keys, and budgets. But it raises an obvious worry — am I paying for that with latency? Every request now takes an extra hop, and for a user-facing app, milliseconds matter.

So we measured five ways to reach the same model — through our gateway, around it with your own key, and raw — to see exactly where the milliseconds go.