Comparison
Helicone vs LLMJury
Helicone sits in front of your model calls and records them. LLMJury sits around them and compares two versions of what you send.
Helicone is open-source LLM observability via a proxy gateway — logging, caching, and cost tracking. Below is what it does well, where LLMJury does something different, and why the two are usually complements rather than a choice.
What Helicone is good at
- One-line integration. Change a base URL and every request is logged, with no SDK to adopt and no code path to instrument.
- Gateway features you get for free at that position: response caching, rate limiting, retries, and per-key spend controls that actually stop a runaway job.
- Cost and usage analytics across models and providers, which is the fastest answer to "why is the bill like that".
- Open source and self-hostable, and a prompt store with versioning alongside the logs.
Where LLMJury does something else
A proxy sees every request and no comparison. It can tell you what your app sent, what came back, what it cost, and how long it took — and it cannot tell you whether the version you shipped last Tuesday is better than the one before it, because that requires deciding in advance who sees which version and then testing the difference.
LLMJury is that decision and that test. Deterministic local assignment splits your users, an LLM-as-judge grades a sample of the outputs against your rubric, and the result is reported only after an SRM check confirms the split held and FDR correction accounts for every metric you asked about.
There is also a positional difference worth knowing: LLMJury does not sit on your request path. Assignment is a local hash and grading happens afterwards on sampled outputs, so nothing about your users’ latency depends on us being up.
Side by side
| Dimension | LLMJury | Helicone |
|---|---|---|
| Built for | LLM products: prompt and model variants, judged on live traffic | Observability and control at the gateway: logging, caching, cost tracking |
| Core unit | The online experiment — a variant split running on real users | The logged request, through the proxy |
| Quality measurement | Built-in LLM-as-judge (quality, safety, relevance) plus your own rubric metrics | Scoring and feedback on logged requests |
| Live-traffic comparison | The product — variant assignment, exposure tracking, a verdict per metric | Requests are recorded, not split and compared |
| Statistical treatment | Chi-squared SRM hard gate (analysis halts, no result shown), per-metric test routing, Benjamini–Hochberg FDR correction across every comparison, raw and corrected p-values both reported | Usage and cost aggregates |
| Request path | Zero added latency; judging runs after the fact on sampled outputs | In the path — the proxy is where the value comes from |
| Prompt management | Prompts live outside your repo with version history, audit trail, diff, and one-click rollback — and the version you edit is the variant that gets tested | Prompt store with versioning |
Written from each product’s own published positioning, and last checked against it on 3 August 2026. Both products move — if something here is out of date or unfair, tell us at [email protected] and we will correct it.
Should you run both?
They occupy different positions on purpose. Helicone at the gateway gives you the log, the cache, and the bill; LLMJury around the call gives you the comparison. If you already proxy through Helicone, nothing about adding LLMJury conflicts — the SDK wraps your client, which is still pointed at the proxy.