--- title: "agentops vs openlit" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/agentops-ai-agentops-vs-openlit-openlit" tools: ["agentops-ai-agentops", "openlit-openlit"] --- # agentops vs openlit *GraphCanon updated Aug 14, 2026* ## Verdict Pick agentops if agentOps is an open-source Python toolkit for monitoring AI agents and tracking costs associated with Large Language Model usage; pick openlit if decision-critical facts for OpenLIT are centered around its unique features in LLM observability, GPU monitoring, and extensive integration capabilities. [agentops](https://agentops.ai) reports 5.8k GitHub stars, 612 forks, and 176 open issues, last pushed Jun 25, 2026. [openlit](https://docs.openlit.io) has 2.7k stars, 342 forks, and 48 open issues, last pushed Jul 31, 2026. Figures are from public GitHub metadata via [agentops's repository](https://github.com/AgentOps-AI/agentops) and [openlit's repository](https://github.com/openlit/openlit). | | [agentops](/tools/agentops-ai-agentops.md) | [openlit](/tools/openlit-openlit.md) | | --- | --- | --- | | Tagline | Python SDK for AI agent monitoring and LLM cost tracking | A comprehensive open-source platform for AI Engineering with LLM Observability, Monitoring, and Management | | Stars | 5,771 | 2,664 | | Forks | 612 | 342 | | Open issues | 176 | 48 | | Language | Python | TypeScript | | Adopt for | AgentOps is an open-source Python toolkit for monitoring AI agents and tracking costs associated with Large Language Model usage. | Decision-critical facts for OpenLIT are centered around its unique features in LLM observability, GPU monitoring, and extensive integration capabilities. | | Persona | - | - | | Runtime | - | - | | License | MIT | Apache-2.0 | | Categories | AI Agents, Evaluation & Observability | Evaluation & Observability, Inference & Serving | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [agentops](/tools/agentops-ai-agentops.md) | [openlit](/tools/openlit-openlit.md) | | --- | --- | --- | | Maintenance | Steady (60%) | Very active (96%) | | Days since push | 49d | 0d | | Open issues (now) | 176 | 48 | | Full report | [trust report](/tools/agentops-ai-agentops/trust.md) | [trust report](/tools/openlit-openlit/trust.md) | ## Shared compatibility - **Python**: [agentops](/tools/agentops-ai-agentops.md) - Python runtime; [openlit](/tools/openlit-openlit.md) - Python runtime ## Decision facts: agentops - **Adopt for:** AgentOps is an open-source Python toolkit for monitoring AI agents and tracking costs associated with Large Language Model usage. ## Decision facts: openlit - **Pricing:** freemium - **Adopt for:** Decision-critical facts for OpenLIT are centered around its unique features in LLM observability, GPU monitoring, and extensive integration capabilities. - **License detail:** Apache-2.0 ## Choose when ### Choose agentops if… - agentops is primarily Python; openlit is TypeScript. - License: agentops is MIT, openlit is Apache-2.0. - Tags unique to agentops: ai-agents, benchmarking, cost-tracking. - Also covers AI Agents. - Integrations are needed specifically with Langchain, CrewAI, or OpenAI Agents SDK ### Choose openlit if… - openlit is primarily TypeScript; agentops is Python. - License: openlit is Apache-2.0, agentops is MIT. - Tags unique to openlit: ai-observability, gpu-monitoring, langchain, llmops. - Also covers Inference & Serving. - openlit ships Docker support for self-hosted deployment. - When you need comprehensive observability features native to OpenTelemetry, allowing seamless trace and metric management with an out-of-the-box solution. ## When NOT to use agentops - If specific integration support is needed for frameworks not listed including Autogen AG2 CamelAI - In case self-hosting of components is impractical due to resource constraints ## When NOT to use openlit - If your project strictly requires a proprietary tool or if you have specific requirements that are not covered by OpenLIT's integrations, such as unique vector databases not yet supported. - When the team lacks the expertise in TypeScript or Python SDK to efficiently manage and implement observability into their current workflows with OpenLIT. ## Common questions ### What is the difference between agentops and openlit? agentops: Python SDK for AI agent monitoring and LLM cost tracking. openlit: A comprehensive open-source platform for AI Engineering with LLM Observability, Monitoring, and Management. See the comparison table for live GitHub stats and shared categories. ### When should I choose agentops over openlit? Choose agentops over openlit when agentops is primarily Python; openlit is TypeScript; License: agentops is MIT, openlit is Apache-2.0; Tags unique to agentops: ai-agents, benchmarking, cost-tracking; Also covers AI Agents; Integrations are needed specifically with Langchain, CrewAI, or OpenAI Agents SDK. ### When should I choose openlit over agentops? Choose openlit over agentops when openlit is primarily TypeScript; agentops is Python; License: openlit is Apache-2.0, agentops is MIT; Tags unique to openlit: ai-observability, gpu-monitoring, langchain, llmops; Also covers Inference & Serving; openlit ships Docker support for self-hosted deployment; When you need comprehensive observability features native to OpenTelemetry, allowing seamless trace and metric management with an out-of-the-box solution. ### When should I avoid agentops? If specific integration support is needed for frameworks not listed including Autogen AG2 CamelAI In case self-hosting of components is impractical due to resource constraints ### When should I avoid openlit? If your project strictly requires a proprietary tool or if you have specific requirements that are not covered by OpenLIT's integrations, such as unique vector databases not yet supported. When the team lacks the expertise in TypeScript or Python SDK to efficiently manage and implement observability into their current workflows with OpenLIT. ### Is agentops or openlit more popular on GitHub? agentops has more GitHub stars (5,771 vs 2,664). Stars measure visibility, not whether either tool fits your constraints. ### Are agentops and openlit open source? Yes - both are open-source projects on GitHub (agentops: MIT, openlit: Apache-2.0). ### Where can I find alternatives to agentops or openlit? GraphCanon lists graph-backed alternatives at [agentops alternatives](/tools/agentops-ai-agentops/alternatives) and [openlit alternatives](/tools/openlit-openlit/alternatives) ([agentops markdown twin](/tools/agentops-ai-agentops/alternatives.md), [openlit markdown twin](/tools/openlit-openlit/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 [this comparison](/compare/agentops-ai-agentops-vs-openlit-openlit.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, agentops or openlit? agentops: Steady. openlit: 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 agentops and openlit? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [agentops trust report](/tools/agentops-ai-agentops/trust); [openlit trust report](/tools/openlit-openlit/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=agentops-ai-agentops`](/api/graphcanon/graph?tool=agentops-ai-agentops) - 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/_