--- title: "agentops vs athina-evals" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/agentops-ai-agentops-vs-athina-ai-athina-evals" tools: ["agentops-ai-agentops", "athina-ai-athina-evals"] --- # agentops vs athina-evals *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 athina-evals if athina-evals is a Python SDK developed for facilitating the evaluation of outputs from large language models through predefined metrics and frameworks. [agentops](https://agentops.ai) reports 5.8k GitHub stars, 612 forks, and 176 open issues, last pushed Jun 25, 2026. [athina-evals](https://docs.athina.ai) has 301 stars, 22 forks, and 3 open issues, last pushed Jun 6, 2025. Figures are from public GitHub metadata via [agentops's repository](https://github.com/AgentOps-AI/agentops) and [athina-evals's repository](https://github.com/athina-ai/athina-evals). | | [agentops](/tools/agentops-ai-agentops.md) | [athina-evals](/tools/athina-ai-athina-evals.md) | | --- | --- | --- | | Tagline | Python SDK for AI agent monitoring and LLM cost tracking | Python SDK for evaluating LLM generated responses | | Stars | 5,771 | 301 | | Forks | 612 | 22 | | Open issues | 176 | 3 | | Language | Python | Python | | Adopt for | AgentOps is an open-source Python toolkit for monitoring AI agents and tracking costs associated with Large Language Model usage. | athina-evals is a Python SDK developed for facilitating the evaluation of outputs from large language models through predefined metrics and frameworks. | | Persona | - | - | | Runtime | - | - | | License | MIT | - | | Categories | AI Agents, Evaluation & Observability | Evaluation & Observability | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [agentops](/tools/agentops-ai-agentops.md) | [athina-evals](/tools/athina-ai-athina-evals.md) | | --- | --- | --- | | Maintenance | Steady (60%) | Dormant (18%) | | Days since push | 49d | 417d | | Open issues (now) | 176 | 3 | | Full report | [trust report](/tools/agentops-ai-agentops/trust.md) | [trust report](/tools/athina-ai-athina-evals/trust.md) | ## 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: athina-evals - **Adopt for:** athina-evals is a Python SDK developed for facilitating the evaluation of outputs from large language models through predefined metrics and frameworks. ## Choose when ### Choose agentops if… - 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 athina-evals if… - Tags unique to athina-evals: evaluation, evaluation-framework, evaluation-metrics, llm-eval. - When comprehensive evaluation of LLM responses is required, leveraging athina's specific tools and metrics - Leaner open-issue backlog (3). ## 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 athina-evals - If open-source alternatives with transparent customization options are preferred over athina-evals' approach - In scenarios where API access requirements limit the ability to perform evaluations offline or in private environments ## Common questions ### What is the difference between agentops and athina-evals? agentops: Python SDK for AI agent monitoring and LLM cost tracking. athina-evals: Python SDK for evaluating LLM generated responses. See the comparison table for live GitHub stats and shared categories. ### When should I choose agentops over athina-evals? Choose agentops over athina-evals when 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 athina-evals over agentops? Choose athina-evals over agentops when Tags unique to athina-evals: evaluation, evaluation-framework, evaluation-metrics, llm-eval; When comprehensive evaluation of LLM responses is required, leveraging athina's specific tools and metrics; Leaner open-issue backlog (3). ### 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 athina-evals? If open-source alternatives with transparent customization options are preferred over athina-evals' approach In scenarios where API access requirements limit the ability to perform evaluations offline or in private environments ### Is agentops or athina-evals more popular on GitHub? agentops has more GitHub stars (5,771 vs 301). Stars measure visibility, not whether either tool fits your constraints. ### Are agentops and athina-evals open source? Yes - both are open-source projects on GitHub. ### Where can I find alternatives to agentops or athina-evals? GraphCanon lists graph-backed alternatives at [agentops alternatives](/tools/agentops-ai-agentops/alternatives) and [athina-evals alternatives](/tools/athina-ai-athina-evals/alternatives) ([agentops markdown twin](/tools/agentops-ai-agentops/alternatives.md), [athina-evals markdown twin](/tools/athina-ai-athina-evals/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-athina-ai-athina-evals.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, agentops or athina-evals? agentops: Steady. athina-evals: Dormant. 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 athina-evals? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [agentops trust report](/tools/agentops-ai-agentops/trust); [athina-evals trust report](/tools/athina-ai-athina-evals/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/_