Comparison
agentops vs oss-llmops-stack
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 oss-llmops-stack if the OSS LLMOps Stack is designed for managing and unifying LLM APIs with LiteLLM, and providing detailed observability through Langfuse.
Markdown twin · agentops alternatives · oss-llmops-stack alternatives
GraphCanon updated 1w
vs
Trust & integrity
| Signal | agentops | oss-llmops-stack |
|---|---|---|
| Maintenance | Steady (49d since push) As of 1w · github_public_v1 | Very active (0d since push) As of 4w · github_public_v1 |
| Provenance | Not a fork · Organization account As of 1w · github_public_v1 | Not a fork · Organization account As of 4w · github_public_v1 |
| OSV dependency advisories | No lockfile (source not queried) As of 1mo · osv@v1 | No lockfile (source not queried) As of 1mo · osv@v1 |
| deps.dev advisories | Not queried deps.dev@v1 | Not queried deps.dev@v1 |
| OpenSSF Scorecard | Not queried openssf-scorecard@v1 | Not queried openssf-scorecard@v1 |
Tagline
- agentops
- Python SDK for AI agent monitoring and LLM cost tracking
- oss-llmops-stack
- Modular open source LLMOps stack for LLM API unification, observability and prompt management
Stars
- agentops
- 5.8k
- oss-llmops-stack
- 142
Forks
- agentops
- 612
- oss-llmops-stack
- 7
Open issues
- agentops
- 176
- oss-llmops-stack
- 1
Language
- agentops
- Python
- oss-llmops-stack
- -
Adopt for
- agentops
- AgentOps is an open-source Python toolkit for monitoring AI agents and tracking costs associated with Large Language Model usage.
- oss-llmops-stack
- The OSS LLMOps Stack is designed for managing and unifying LLM APIs with LiteLLM, and providing detailed observability through Langfuse.
Persona
- agentops
- -
- oss-llmops-stack
- -
Runtime
- agentops
- -
- oss-llmops-stack
- -
License
- agentops
- MIT
- oss-llmops-stack
- MIT
Last pushed
- agentops
- Jun 25, 2026
- oss-llmops-stack
- Jul 28, 2026
Categories
- agentops
- AI Agents, Evaluation & Observability
- oss-llmops-stack
- Evaluation & Observability, Inference & Serving
Trust and health
Maintenance
- agentops
- Steady (60%)
- oss-llmops-stack
- Very active (96%)
Days since push
- agentops
- 49d
- oss-llmops-stack
- 0d
Open issues (now)
- agentops
- 176
- oss-llmops-stack
- 1
Full report
- agentops
- Trust report
- oss-llmops-stack
- Trust report
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
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
Choose oss-llmops-stack if…
- Requirements: Ensure your environment supports both LiteLLM and Langfuse functionalities for seamless operation of the OSS LLMOps Stack.; Consider server capacity to handle the additional load introduced by using this stack for API unification and observability services..
- Tags unique to oss-llmops-stack: ai-gateway, llm-evaluation, open-source, prompt management.
- Also covers Inference & Serving.
- When you need to unify Multiple Large Language Model (LLM) APIs using LiteLLM's API mediation capabilities for efficient routing, cost control, and high-availability support.
When NOT to use oss-llmops-stack
- If your operational requirements are simple and you do not need comprehensive observability metrics or advanced LLM API unification capabilities provided by the stack.
- In scenarios where you prefer a proprietary software solution over an open-source tool for security, support, or compliance reasons.
Explore
Sources
Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.
- GitHub stars (AgentOps-AI/agentops) · observed Aug 14, 2026
- GitHub forks (AgentOps-AI/agentops) · observed Aug 14, 2026
- Last push (AgentOps-AI/agentops) · observed Jun 25, 2026
- License file (MIT) · observed Aug 14, 2026
- Decision facts (enrichment) · observed Jul 17, 2026
- Trust scan (lockfile / OSV) · observed Jul 15, 2026
- GitHub stars (langfuse/oss-llmops-stack) · observed Jul 29, 2026
- GitHub forks (langfuse/oss-llmops-stack) · observed Jul 29, 2026
- Last push (langfuse/oss-llmops-stack) · observed Jul 28, 2026
- License file (MIT) · observed Jul 29, 2026
- Decision facts (enrichment) · observed Jul 16, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
GitHub stars on cards: agentops 5.8k · oss-llmops-stack 142 (synced Aug 14, 2026).
Common questions
- What is the difference between agentops and oss-llmops-stack?
- agentops: Python SDK for AI agent monitoring and LLM cost tracking. oss-llmops-stack: Modular open source LLMOps stack for LLM API unification, observability and prompt management. See the comparison table for live GitHub stats and shared categories.
- When should I choose agentops over oss-llmops-stack?
- Choose agentops over oss-llmops-stack 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 oss-llmops-stack over agentops?
- Choose oss-llmops-stack over agentops when Requirements: Ensure your environment supports both LiteLLM and Langfuse functionalities for seamless operation of the OSS LLMOps Stack.; Consider server capacity to handle the additional load introduced by using this stack for API unification and observability services.; Tags unique to oss-llmops-stack: ai-gateway, llm-evaluation, open-source, prompt management; Also covers Inference & Serving; When you need to unify Multiple Large Language Model (LLM) APIs using LiteLLM's API mediation capabilities for efficient routing, cost control, and high-availability support.
- 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 oss-llmops-stack?
- If your operational requirements are simple and you do not need comprehensive observability metrics or advanced LLM API unification capabilities provided by the stack. In scenarios where you prefer a proprietary software solution over an open-source tool for security, support, or compliance reasons.
- Is agentops or oss-llmops-stack more popular on GitHub?
- agentops has more GitHub stars (5,771 vs 142). Stars measure visibility, not whether either tool fits your constraints.
- Are agentops and oss-llmops-stack open source?
- Yes - both are open-source projects on GitHub (agentops: MIT, oss-llmops-stack: MIT).
- Where can I find alternatives to agentops or oss-llmops-stack?
- GraphCanon lists graph-backed alternatives at agentops alternatives and oss-llmops-stack alternatives (agentops markdown twin, oss-llmops-stack markdown twin), 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 mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers.
- Which is better maintained, agentops or oss-llmops-stack?
- agentops: Steady. oss-llmops-stack: 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 oss-llmops-stack?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: agentops trust report; oss-llmops-stack trust report.