OpenLLMetry vs Helicone
Both are alternatives to LangSmith. Here's how they stack up — verified facts, no spin.
Also searched as Helicone vs OpenLLMetry — same comparison, one verdict.
OpenLLMetry and Helicone are closely matched on ownership (92 vs 88) — this one comes down to pricing and to which trade-offs below you can live with.
OpenLLMetry
Apache-2.0 OpenTelemetry instrumentation — send traces anywhere you already send them.
OpenLLMetry takes the opposite approach to a platform: it is a set of Apache-2.0 OpenTelemetry extensions that emit LLM traces in a standard format, so they flow into whatever you already run — Grafana, Datadog, Honeycomb, Jaeger or Traceloop's own hosted backend. If you already have observability infrastructure, this adds LLM visibility to it rather than asking you to adopt a second, parallel system. It is also the strongest hedge against lock-in: standard telemetry moves between backends by configuration.
Helicone
Gateway and observability in one — one integration instead of two.
Helicone is an Apache-2.0 AI gateway with logging, cost tracking and caching built into the routing layer, which makes it a genuine two-birds option: point your client at Helicone and you get both the gateway and the observability without instrumenting your application code. That proxy-based approach is the practical distinction — nothing to add to your codebase, at the cost of only seeing what passes through the proxy. Helicone joined Mintlify in March 2026 and is now in maintenance: fixes continue, new development does not.
Side by side
6 points of comparison, every one read from a verified field. Green marks the side that wins a row outright. A dash means we do not hold that fact — never that it is zero.
| OpenLLMetry | Helicone | |
|---|---|---|
| Sovereignty ScoreOur transparent 0–100 composite for data ownership and exit cost. | 92 | 88 |
| Open source | Yes | Yes |
| Self-hostable | Yes | Yes |
| Local-first data | Yes | Yes |
| License | Apache-2.0 | Apache-2.0 |
| Pricing | Free — Apache-2.0 instrumentation libraries. You pay only whatever backend you already send telemetry to; a hosted Traceloop backend is available separately. | Free and self-hostable under Apache-2.0. Hosted service has a free tier of roughly 10,000 requests per month, with paid plans starting around $79/month. |
OpenLLMetry edges it on the Sovereignty Score, but the right pick depends on the trade-offs below.
Weighing both against staying on LangSmith? Is LangSmith free? What it actually costs →
OpenLLMetry
Strengths
- +Apache-2.0 throughout — no enterprise-directory carve-out
- +Standard OpenTelemetry: traces go to a backend you already operate
- +The best protection against lock-in — switching backends is configuration
- +Reuses your existing observability stack instead of adding a parallel one
Trade-offs
- −Instrumentation, not a platform — no evaluation or prompt-management UI
- −You need a trace backend already, or you are choosing one anyway
- −Generic backends render LLM traces less legibly than a purpose-built UI
- −Smaller project (about 7k stars) than Langfuse
Helicone
Strengths
- +Apache-2.0, fully self-hostable
- +Proxy-based — no code instrumentation needed to start
- +Gateway and observability in one component
- +Real free tier on the hosted version for evaluating it
Trade-offs
- −Maintenance mode since the Mintlify acquisition (March 2026) — no new development
- −Only sees traffic through the proxy — no visibility into internal agent steps
- −Weaker evaluation tooling than Langfuse or LangSmith
- −Adds a proxy hop to every model call
Which one fits you
The trade-offs above, turned into a decision. Find the line that describes your team.
Choose OpenLLMetry
if a lower exit cost matters more to you than any single feature, and apache-2.0 throughout — no enterprise-directory carve-out.
Choose Helicone
if apache-2.0, fully self-hostable.
Neither, yet
if both carry a real cost you should weigh first — instrumentation, not a platform — no evaluation or prompt-management UI, and maintenance mode since the Mintlify acquisition (March 2026) — no new development. If either of those is a dealbreaker for your team, the shortlist is wrong rather than the choice.
OpenLLMetry vs Helicone — common questions
Is OpenLLMetry a better fit than Helicone for llm observability & evaluation?
It depends on what you are optimising for, and the honest split is this: OpenLLMetry scores 92 to Helicone's 88 on data ownership and exit cost, so it is the safer choice if you care about being able to leave. Helicone earns its place on a different axis — apache-2.0, fully self-hostable. Neither is a wrong answer for every team; the table above is the actual comparison.
What happens if we want to switch later?
OpenLLMetry keeps its data local or in open formats, so leaving is an export rather than a negotiation. Helicone is still self-hostable, so the files stay on your server either way — but it is not local-first by design, so check what its export produces before you rely on it.
Can I self-host OpenLLMetry or Helicone?
Both can be self-hosted. The difference is what it costs you in time rather than whether it is possible — see the setup and maintenance rows above.
Are OpenLLMetry and Helicone both alternatives to LangSmith?
Yes — both appear in our LangSmith comparison, which is why they are worth putting side by side. People usually arrive here already having decided to move off LangSmith and now choosing between the two replacements, which is a narrower and much easier question.
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Facts verified 2026-07-30. Licenses and pricing change — spotted something out of date? That's a correction we want.