--- title: "helicone vs openllmetry" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/helicone-helicone-vs-traceloop-openllmetry" tools: ["helicone-helicone", "traceloop-openllmetry"] --- # helicone vs openllmetry Neutral, constraint-first comparison with live GitHub stats. | | [helicone](/tools/helicone-helicone.md) | [openllmetry](/tools/traceloop-openllmetry.md) | | --- | --- | --- | | Tagline | Ice-cold observability for LLMs. | Open-source observability for your LLM application | | Stars | 5,920 | 7,281 | | Forks | 622 | 1,016 | | Open issues | 124 | 591 | | Language | TypeScript | Python | | Adopt for | Helicone is an open-source LLM observability platform that supports monitoring, evaluation, and experimentation of Large Language Models using a simple integration. It provides advanced tracing, intelligent routing, cost | OpenLLMetry is an open-source observability tool based on OpenTelemetry for monitoring and metrics in GenAI and LLM applications. | | Persona | - | - | | Runtime | - | - | | License | Apache-2.0 | Apache-2.0 license grants permission to use, study, modify, and distribute the tool freely. | | Categories | Evaluation & Observability, Inference & Serving | Evaluation & Observability | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [helicone](/tools/helicone-helicone.md) | [openllmetry](/tools/traceloop-openllmetry.md) | | --- | --- | --- | | Days since push | 3d | 0d | | Open issues (now) | 124 | 591 | | Full report | [trust report](/tools/helicone-helicone/trust.md) | [trust report](/tools/traceloop-openllmetry/trust.md) | **Typed relationship:** helicone _(related)_ openllmetry ## Decision facts: helicone - **Pricing:** freemium - Helicone offers a free tier (generous monthly 10k requests/month). Pricing details for additional usage tiers are available on their official pricing page. - **Requirements:** Ensure TypeScript is supported in your project environment since Helicone's API is compatible with TypeScript.; Before integrating Helicone, verify that intelligent routing and fallback mechanisms align with the requirements of your LLM deployment scenario. - **Adopt for:** Helicone is an open-source LLM observability platform that supports monitoring, evaluation, and experimentation of Large Language Models using a simple integration. It provides advanced tracing, intelligent routing, cost ## Decision facts: openllmetry - **Requirements:** Built on top of OpenTelemetry; compatible with various observability solutions like Datadog and Honeycomb - **Adopt for:** OpenLLMetry is an open-source observability tool based on OpenTelemetry for monitoring and metrics in GenAI and LLM applications. - **License detail:** Apache-2.0 license grants permission to use, study, modify, and distribute the tool freely. ## Choose when ### Choose helicone if… - helicone is primarily TypeScript; openllmetry is Python. - Pricing: Helicone offers a free tier (generous monthly 10k requests/month). Pricing details for additional usage tiers are available on their official pricing page.. - Requirements: Ensure TypeScript is supported in your project environment since Helicone's API is compatible with TypeScript.; Before integrating Helicone, verify that intelligent routing and fallback mechanisms align with the requirements of your LLM deployment scenario.. - Graph edge: helicone is a typed related of openllmetry - see the relationship row above. - Tags unique to helicone: agent-monitoring, evaluation, cost-tracking, observability. - Also covers Inference & Serving. - helicone ships Docker support for self-hosted deployment. - When you need to integrate multiple AI models with one API key through the OpenAI API, including automatic fallbacks. ### Choose openllmetry if… - openllmetry is primarily Python; helicone is TypeScript. - Requirements: Built on top of OpenTelemetry; compatible with various observability solutions like Datadog and Honeycomb. - Graph edge: openllmetry is a typed related of helicone - see the relationship row above. - Tags unique to openllmetry: llmops, ml, artifical-intelligence, llm. - - Use it if you are working with Large Language Model (LLM) or Generative AI applications that require detailed observations, including model oversight and performance metrics. ## When NOT to use helicone - When the requirement demands strict adherence to proprietary systems, as Helicone encourages open-source development. - For projects that do not necessitate monitoring metrics such as cost and latency tracking via an external platform. - If your application does not need intelligent routing across multiple AI models or fallback mechanisms. ## When NOT to use openllmetry - - Avoid using it for applications where existing comprehensive proprietary observability solutions already meet all requirements without the need for integration flexibility offered by OpenTelemetry. - - Not recommended if your team has limited experience with OpenTelemetry, which could complicate adoption and integration with other tools unless there is a dedicated effort to adapt. ## Common questions ### What is the difference between helicone and openllmetry? helicone: Ice-cold observability for LLMs.. openllmetry: Open-source observability for your LLM application. See the comparison table for live GitHub stats and shared categories. ### When should I choose helicone over openllmetry? Choose helicone over openllmetry when helicone is primarily TypeScript; openllmetry is Python; Pricing: Helicone offers a free tier (generous monthly 10k requests/month). Pricing details for additional usage tiers are available on their official pricing page.; Requirements: Ensure TypeScript is supported in your project environment since Helicone's API is compatible with TypeScript.; Before integrating Helicone, verify that intelligent routing and fallback mechanisms align with the requirements of your LLM deployment scenario.; Graph edge: helicone is a typed related of openllmetry - see the relationship row above; Tags unique to helicone: agent-monitoring, evaluation, cost-tracking, observability; Also covers Inference & Serving; helicone ships Docker support for self-hosted deployment; When you need to integrate multiple AI models with one API key through the OpenAI API, including automatic fallbacks. ### When should I choose openllmetry over helicone? Choose openllmetry over helicone when openllmetry is primarily Python; helicone is TypeScript; Requirements: Built on top of OpenTelemetry; compatible with various observability solutions like Datadog and Honeycomb; Graph edge: openllmetry is a typed related of helicone - see the relationship row above; Tags unique to openllmetry: llmops, ml, artifical-intelligence, llm; - Use it if you are working with Large Language Model (LLM) or Generative AI applications that require detailed observations, including model oversight and performance metrics. ### When should I avoid helicone? When the requirement demands strict adherence to proprietary systems, as Helicone encourages open-source development. For projects that do not necessitate monitoring metrics such as cost and latency tracking via an external platform. If your application does not need intelligent routing across multiple AI models or fallback mechanisms. ### When should I avoid openllmetry? - Avoid using it for applications where existing comprehensive proprietary observability solutions already meet all requirements without the need for integration flexibility offered by OpenTelemetry. - Not recommended if your team has limited experience with OpenTelemetry, which could complicate adoption and integration with other tools unless there is a dedicated effort to adapt. ### Is helicone or openllmetry more popular on GitHub? openllmetry has more GitHub stars (7,281 vs 5,920). Stars measure visibility, not whether either tool fits your constraints. ### Are helicone and openllmetry open source? Yes - both are open-source projects on GitHub (helicone: Apache-2.0, openllmetry: Apache-2.0). ### Where can I find alternatives to helicone or openllmetry? GraphCanon lists graph-backed alternatives at /tools/helicone-helicone/alternatives and /tools/traceloop-openllmetry/alternatives (/tools/helicone-helicone/alternatives.md, /tools/traceloop-openllmetry/alternatives.md), ranked by typed relationship edges rather than popularity votes. ### Is there a machine-readable version of this comparison? Yes. The markdown twin at /compare/helicone-helicone-vs-traceloop-openllmetry.md mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, helicone or openllmetry? helicone: Very active. openllmetry: Very active. Compare maintenance labels, days since push, and release cadence in the trust section below - stars alone do not measure maintenance. ### Where are the full trust reports for helicone and openllmetry? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: helicone: /tools/helicone-helicone/trust; openllmetry: /tools/traceloop-openllmetry/trust. --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=helicone-helicone`](/api/graphcanon/graph?tool=helicone-helicone) - LLM index: [/llms.txt](/llms.txt) - Full corpus: [/llms-full.txt](/llms-full.txt) _GraphCanon - The knowledge graph for AI development. https://www.graphcanon.com/_