RelayPlane vs Traceloop (OpenLLMetry)
Traceloop ships OpenLLMetry, an Apache 2.0 open-source SDK that instruments LLM calls with OpenTelemetry spans and exports to any OTLP backend. RelayPlane is an MIT-licensed npm proxy that intercepts LLM requests at the network level for real-time cost control, smart routing, and zero-code observability.
TL;DR
Traceloop observes. RelayPlane observes AND routes AND reduces costs.
Choose RelayPlane when you want:
- npm install and running in 30 seconds with zero code changes
- Real-time cost control and smart model routing in the request path
- Local SQLite cost tracking with no data leaving your machine
- Drop-in proxy for any OpenAI-compatible client with one baseURL swap
- Cost tracking for Claude Code and Cursor without SDK instrumentation
Traceloop may work for you if you need:
- Standard OTel spans for LLM calls that plug into your existing observability stack
- LLM traces correlated with distributed traces across your broader application
- Structured session and workflow tracing with @tracer decorator support
- Apache 2.0 licensed open-source SDK with broad language support
Feature Comparison
| Feature | RelayPlane | Traceloop |
|---|---|---|
| Product type RelayPlane sits in the critical path of every LLM request: it intercepts, routes, and logs each call transparently as an HTTP proxy. Traceloop ships the OpenLLMetry SDK, which instruments LLM calls by wrapping them with OpenTelemetry spans inside your application code. Traceloop does not proxy or route requests. | npm-native LLM proxy and gateway (local-first) | Open-source OpenTelemetry SDK for LLM observability (OpenLLMetry instrumentation library) |
| Setup complexity RelayPlane is a single npm binary. Run npm install -g @relayplane/proxy, then relayplane start, and you are proxying in under 30 seconds. Traceloop requires installing the SDK, calling Traceloop.init() in your application entry point, and decorating every workflow or LLM call with @workflow or @task decorators for structured tracing to appear. | One npm install, one command to start | Install SDK, initialize Traceloop, add @tracer decorators to every LLM call |
| Zero code changes RelayPlane intercepts requests at the network level via a baseURL swap. Your existing code does not change. Traceloop requires SDK initialization and decorator-based instrumentation throughout your codebase. Every function that makes LLM calls must be wrapped before traces are collected. | ||
| Drop-in proxy (no SDK wrapping) RelayPlane is a network proxy. Set OPENAI_BASE_URL=http://localhost:4100 and every LLM call from any client is intercepted automatically. Traceloop instruments at the application code layer using decorators and SDK patches. It is not a network endpoint and cannot intercept traffic without code instrumentation. | ||
| Cost tracking RelayPlane calculates and stores exact dollar costs in local SQLite for every request, with no data leaving your machine. Traceloop captures token usage as OpenTelemetry span attributes which you can use to derive costs in your chosen OTel backend. The cost calculation and storage depend on your backend configuration. | Token counts via OTel spans (cost calculation in backend) | |
| Smart routing (complexity mode) RelayPlane analyzes each incoming request and routes simple queries to cheaper, faster models automatically. This complexity-based routing can reduce costs significantly without changing application behavior. Traceloop is an observability SDK and has no routing capability. It cannot redirect requests or switch providers. | ||
| LLM tracing and observability Traceloop is purpose-built for LLM tracing. It generates structured OpenTelemetry spans with model name, prompt, completion, token counts, and latency as standardized attributes. These traces flow into any OTel-compatible backend. RelayPlane logs per-request metadata but does not produce OTel-compatible distributed trace trees. | Basic request logging | |
| OpenTelemetry support Traceloop is built on OpenTelemetry and emits OTLP-compatible spans and metrics that plug into Jaeger, Zipkin, Grafana Tempo, Honeycomb, Datadog, and any other OTel backend. If your team already has an OTel stack, Traceloop slots LLM traces into it. RelayPlane does not emit OTel spans. | ||
| Local dashboard RelayPlane includes a local web dashboard at localhost:4100 showing costs, request history, and model usage with no signup. Traceloop exports traces to external backends. It does not include a bundled local dashboard. You view trace data in whatever OTel backend you configure. | ||
| Cloud dashboard Traceloop provides a cloud dashboard at app.traceloop.com for viewing traces, sessions, and LLM metrics. RelayPlane is local-first by default. A cloud dashboard is available at relayplane.com for teams who want cross-machine visibility, but the local dashboard works with no account. | Optional (relayplane.com) | |
| Self-hosted option Both products support self-hosted deployments. RelayPlane runs entirely on localhost by default with no infrastructure required. Traceloop is open source (Apache 2.0) and can export traces to any self-hosted OTel backend. The Traceloop cloud dashboard can also be bypassed in favor of your own OTel infrastructure. | ||
| SDK wrapping required RelayPlane requires zero SDK integration. Point any HTTP client at localhost:4100 and it works. Traceloop requires importing and initializing its SDK in your application and decorating LLM-calling functions. Services that do not have this instrumentation will not appear in traces. | ||
| Cost reduction via routing RelayPlane actively reduces costs by routing requests to lower-cost models based on complexity analysis. Simple queries go to cheaper models; complex ones go to capable models. This is a real-time action in the request path. Traceloop observes and records costs but cannot act on them. | ||
| Works with any OpenAI-compatible client RelayPlane is compatible with any client that supports the OpenAI API format: set one base URL and it works. Traceloop instruments supported LLM SDK libraries (OpenAI, Anthropic, Cohere, etc.) by patching them at the library level. Clients or tools that make raw HTTP requests without a supported SDK library will not be instrumented. | ||
| Works with Claude Code and Cursor RelayPlane proxies traffic from any tool that makes HTTP requests to an LLM provider, including Claude Code, Cursor, Windsurf, and Aider. Traceloop instruments application code. It cannot intercept traffic from AI coding assistants running at the CLI or IDE level that you do not control the source code of. | Not applicable (SDK instrumentation, not a proxy) | |
| Open source Both products are fully open source. Traceloop publishes OpenLLMetry on GitHub under Apache 2.0 with over 1,000 stars. RelayPlane is MIT licensed. Neither product has a proprietary core library. | MIT | Apache 2.0 (OpenLLMetry on GitHub) |
| Pricing The Traceloop SDK (OpenLLMetry) is free and open source. The traceloop.com cloud dashboard offers a free tier for small workloads with paid plans for higher volume and team features. RelayPlane is MIT licensed with a free local dashboard. The relayplane.com cloud dashboard is optional. | Free (MIT), optional cloud at relayplane.com | Open source SDK free; traceloop.com cloud dashboard has a free tier |
Why Teams Choose RelayPlane When They Need Cost Control, Not Just Observability
A network proxy intercepts any client. An SDK only instruments the code you control.
Traceloop instruments LLM calls through its SDK by patching supported library clients in your application process. This works well for application code you own and can modify. But it cannot intercept traffic from Claude Code, Cursor, or other AI coding tools you do not control. RelayPlane is an HTTP proxy. Set one environment variable and every LLM request from any application, library, or tool running on your machine is captured, tracked, and governed without a single line of code changed.
npm install in 30 seconds vs SDK installation plus decorator instrumentation across your codebase
npm install -g @relayplane/proxy and relayplane start gets you proxying LLM requests in under 30 seconds with no code changes and no account. Traceloop requires installing the OpenLLMetry SDK, calling Traceloop.init() in your application entry point, and adding @workflow and @task decorators to every function that calls an LLM. For teams with multiple services or existing codebases, that instrumentation work multiplies across every service.
Cost control in the request path, not just cost observation after the fact
Traceloop captures token usage as OpenTelemetry span attributes and surfaces cost data in its cloud dashboard. This is valuable for understanding which workflows are expensive. But it cannot stop spending. RelayPlane tracks cost and enforces it: budget limits, automatic routing to cheaper models when thresholds are hit, fallback on provider failures. For agentic workloads that can run for minutes and burn unexpected tokens, having a proxy that acts in real time is meaningfully different from a dashboard that reports what happened.
Complexity mode routes simple queries to cheaper models automatically
RelayPlane analyzes each incoming request for complexity and routes straightforward queries to cost-effective models like GPT-4o mini or Haiku while sending complex reasoning tasks to more capable models. This happens transparently with no application code changes. Traceloop has no routing capability. It observes which model was used but cannot change it.
Traceloop Solves Observability Problems. RelayPlane Solves Cost Control Problems.
Traceloop's OpenLLMetry is a well-designed open-source SDK for teams who are already invested in the OpenTelemetry ecosystem and want LLM calls to appear as first-class spans alongside application traces. Its multi-language support, @tracer decorator pattern, and zero-vendor-lock-in architecture make it a strong choice for platform teams who own an observability stack and want to extend it to cover LLM workloads.
But Traceloop requires SDK instrumentation in every service that makes LLM calls. It cannot intercept traffic from tools you do not control, cannot route requests, and cannot enforce budget limits. If you want to track and reduce LLM costs in Claude Code or Cursor today without touching your codebase, without adding SDK dependencies, and without sending logs to a third-party platform, RelayPlane installs in one command and runs on localhost.
What is Traceloop (OpenLLMetry)
| Property | Detail |
|---|---|
| Created by | Traceloop (GitHub: traceloop/openllmetry) |
| License | Apache 2.0 (fully open source, 1K+ GitHub stars) |
| Languages | Python, JavaScript/TypeScript, Go, Ruby, Java |
| What it does | Instruments LLM calls with OpenTelemetry spans via @tracer decorators and exports to any OTLP-compatible backend |
| Requires code changes | Yes: SDK initialization and @workflow/@task decorator instrumentation in your application |
| Cloud dashboard | Available at app.traceloop.com with a free tier for low-volume workloads |
| Does not do | Proxy requests, route traffic, enforce budgets, or intercept tools you do not control |
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