--- title: "agentops vs aim" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/agentops-ai-agentops-vs-aimhubio-aim" tools: ["agentops-ai-agentops", "aimhubio-aim"] --- # agentops vs aim *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 aim if aim is an easy-to-use experiment tracker for Python ML projects with robust features like metadata tracking and compatibility with various frameworks. [agentops](https://agentops.ai) reports 5.8k GitHub stars, 612 forks, and 176 open issues, last pushed Jun 25, 2026. [aim](https://aimstack.io) has 6.2k stars, 401 forks, and 465 open issues, last pushed Jul 27, 2026. Figures are from public GitHub metadata via [agentops's repository](https://github.com/AgentOps-AI/agentops) and [aim's repository](https://github.com/aimhubio/aim). | | [agentops](/tools/agentops-ai-agentops.md) | [aim](/tools/aimhubio-aim.md) | | --- | --- | --- | | Tagline | Python SDK for AI agent monitoring and LLM cost tracking | An easy-to-use & supercharged open-source experiment tracker | | Stars | 5,771 | 6,210 | | Forks | 612 | 401 | | Open issues | 176 | 465 | | 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. | Aim is an easy-to-use experiment tracker for Python ML projects with robust features like metadata tracking and compatibility with various frameworks. | | Persona | - | - | | Runtime | - | - | | License | MIT | Apache-2.0 | | Categories | AI Agents, Evaluation & Observability | Evaluation & Observability, Model Training | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [agentops](/tools/agentops-ai-agentops.md) | [aim](/tools/aimhubio-aim.md) | | --- | --- | --- | | Maintenance | Steady (60%) | Very active (96%) | | Days since push | 49d | 0d | | Open issues (now) | 176 | 465 | | Full report | [trust report](/tools/agentops-ai-agentops/trust.md) | [trust report](/tools/aimhubio-aim/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: aim - **Adopt for:** Aim is an easy-to-use experiment tracker for Python ML projects with robust features like metadata tracking and compatibility with various frameworks. ## Choose when ### Choose agentops if… - License: agentops is MIT, aim 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 aim if… - License: aim is Apache-2.0, agentops is MIT. - Tags unique to aim: ai, data-science, experiment tracking, mlflow. - Also covers Model Training. - You are working on Python-based machine learning projects and need detailed experiment tracking to manage metadata effectively. ## 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 aim - You prefer comprehensive pre-built integrations with cloud services for MLOps processes that are not natively extensive in Aim. - Your project is primarily coded in languages other than Python; while language versatility might be desired, Aim specifically excels within the Python ecosystem. ## Common questions ### What is the difference between agentops and aim? agentops: Python SDK for AI agent monitoring and LLM cost tracking. aim: An easy-to-use & supercharged open-source experiment tracker. See the comparison table for live GitHub stats and shared categories. ### When should I choose agentops over aim? Choose agentops over aim when License: agentops is MIT, aim 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 aim over agentops? Choose aim over agentops when License: aim is Apache-2.0, agentops is MIT; Tags unique to aim: ai, data-science, experiment tracking, mlflow; Also covers Model Training; You are working on Python-based machine learning projects and need detailed experiment tracking to manage metadata effectively. ### 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 aim? You prefer comprehensive pre-built integrations with cloud services for MLOps processes that are not natively extensive in Aim. Your project is primarily coded in languages other than Python; while language versatility might be desired, Aim specifically excels within the Python ecosystem. ### Is agentops or aim more popular on GitHub? aim has more GitHub stars (6,210 vs 5,771). Stars measure visibility, not whether either tool fits your constraints. ### Are agentops and aim open source? Yes - both are open-source projects on GitHub (agentops: MIT, aim: Apache-2.0). ### Where can I find alternatives to agentops or aim? GraphCanon lists graph-backed alternatives at [agentops alternatives](/tools/agentops-ai-agentops/alternatives) and [aim alternatives](/tools/aimhubio-aim/alternatives) ([agentops markdown twin](/tools/agentops-ai-agentops/alternatives.md), [aim markdown twin](/tools/aimhubio-aim/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-aimhubio-aim.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, agentops or aim? agentops: Steady. aim: 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 aim? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [agentops trust report](/tools/agentops-ai-agentops/trust); [aim trust report](/tools/aimhubio-aim/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/_