--- title: "agent-opt vs future-agi" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/future-agi-agent-opt-vs-future-agi-future-agi" tools: ["future-agi-agent-opt", "future-agi-future-agi"] --- # agent-opt vs future-agi *GraphCanon updated Oct 3, 2026* ## Verdict Pick agent-opt if agent-opt is tailored for teams that require automated optimization of AI workflows and support for continuous integration/continuous delivery (CI/CD), relying on Python and specific library dependencies; pick future-agi if future-AGI is an open-source platform for evaluating and observing LLM and AI agent applications, offering features like tracing, evaluations, simulations, and guardrails. It is self-hostable and supports deployment. [agent-opt](https://app.futureagi.com) reports 75 GitHub stars, 9 forks, and 0 open issues, last pushed Jun 30, 2026. [future-agi](https://futureagi.com) has 2.0k stars, 627 forks, and 961 open issues, last pushed Sep 18, 2026. Figures are from public GitHub metadata via [agent-opt's repository](https://github.com/future-agi/agent-opt) and [future-agi's repository](https://github.com/future-agi/future-agi). | | [agent-opt](/tools/future-agi-agent-opt.md) | [future-agi](/tools/future-agi-future-agi.md) | | --- | --- | --- | | Tagline | Open Source Library for Automated Optimization of AI Agent Workflows | Open-source, end-to-end platform for evaluating, observing, and improving LLM and AI agent applications | | Stars | 75 | 2,032 | | Forks | 9 | 627 | | Open issues | 0 | 961 | | Language | Python | Python | | Adopt for | Agent-opt is tailored for teams that require automated optimization of AI workflows and support for continuous integration/continuous delivery (CI/CD), relying on Python and specific library dependencies. | Future-AGI is an open-source platform for evaluating and observing LLM and AI agent applications, offering features like tracing, evaluations, simulations, and guardrails. It is self-hostable and supports deployment via, | | Persona | - | - | | Runtime | - | - | | License | Apache-2.0 | Apache License 2.0, allowing for free use, modification, and distribution of the software, with the condition that any derivative works also be licensed under the same terms. | | Categories | AI Agents, Evaluation & Observability | AI Agents, Evaluation & Observability, LLM Frameworks | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [agent-opt](/tools/future-agi-agent-opt.md) | [future-agi](/tools/future-agi-future-agi.md) | | --- | --- | --- | | Maintenance | Archived (8%) | Very active (96%) | | Days since push | 95d | 0d | | Archived on GitHub | Yes | No | | Open issues (now) | 0 | 961 | | Stars delta | +4 (30d) | +473 (30d) | | Open issues delta | 0 (30d) | +365 (30d) | | Full report | [trust report](/tools/future-agi-agent-opt/trust.md) | [trust report](/tools/future-agi-future-agi/trust.md) | ## Decision facts: agent-opt - **Adopt for:** Agent-opt is tailored for teams that require automated optimization of AI workflows and support for continuous integration/continuous delivery (CI/CD), relying on Python and specific library dependencies. ## Decision facts: future-agi - **Pricing:** freemium - The core platform is free and open-source under the Apache License 2.0. However, for managed services or additional support, contact sales for pricing. - **Requirements:** Min 4 GB RAM; Requires Docker; Future-AGI requires Docker for deployment, with support for Docker Compose and upcoming Kubernetes and Helm support.; For production environments, a setup script is provided to generate secrets and pin image tags, ensuring a secure and reproducible deployment. - **Adopt for:** Future-AGI is an open-source platform for evaluating and observing LLM and AI agent applications, offering features like tracing, evaluations, simulations, and guardrails. It is self-hostable and supports deployment via, - **License detail:** Apache License 2.0, allowing for free use, modification, and distribution of the software, with the condition that any derivative works also be licensed under the same terms. ## Choose when ### Choose agent-opt if… - Tags unique to agent-opt: agent, aioptimization, automation, cicd. - - When your project needs seamless CI/CD integration alongside automated optimization - Leaner open-issue backlog (0). ### Choose future-agi if… - Pricing: The core platform is free and open-source under the Apache License 2.0. However, for managed services or additional support, contact sales for pricing.. - Requirements: Min 4 GB RAM; Requires Docker; Future-AGI requires Docker for deployment, with support for Docker Compose and upcoming Kubernetes and Helm support.; For production environments, a setup script is provided to generate secrets and pin image tags, ensuring a secure and reproducible deployment.. - Tags unique to future-agi: ai-evals, ai-gateway, ai-optimization, ai-simulations. - Also covers LLM Frameworks. - future-agi ships Docker support for self-hosted deployment. - You need a self-hostable solution that does not phone home, ensuring full control over your data and evaluation logic. ## When NOT to use agent-opt - - If your project does not require Python or if it cannot meet the specific requirement of having Python ≥ 3.10 - - In scenarios where CI/CD integration is not a priority for your AI workflow optimization ## When NOT to use future-agi - You require immediate Kubernetes or Helm support, as these are not yet available, though they are in development. - You are seeking a managed service or a solution available through AWS Marketplace, as these options are not yet available, though they are planned for the future. - Your project is in a highly dynamic environment where frequent updates and vendor support are critical, as Future-AGI is a community-driven project with a focus on self-hosting and open-source. ## Common questions ### What is the difference between agent-opt and future-agi? agent-opt: Open Source Library for Automated Optimization of AI Agent Workflows. future-agi: Open-source, end-to-end platform for evaluating, observing, and improving LLM and AI agent applications. See the comparison table for live GitHub stats and shared categories. ### When should I choose agent-opt over future-agi? Choose agent-opt over future-agi when Tags unique to agent-opt: agent, aioptimization, automation, cicd; - When your project needs seamless CI/CD integration alongside automated optimization; Leaner open-issue backlog (0). ### When should I choose future-agi over agent-opt? Choose future-agi over agent-opt when Pricing: The core platform is free and open-source under the Apache License 2.0. However, for managed services or additional support, contact sales for pricing.; Requirements: Min 4 GB RAM; Requires Docker; Future-AGI requires Docker for deployment, with support for Docker Compose and upcoming Kubernetes and Helm support.; For production environments, a setup script is provided to generate secrets and pin image tags, ensuring a secure and reproducible deployment.; Tags unique to future-agi: ai-evals, ai-gateway, ai-optimization, ai-simulations; Also covers LLM Frameworks; future-agi ships Docker support for self-hosted deployment; You need a self-hostable solution that does not phone home, ensuring full control over your data and evaluation logic. ### When should I avoid agent-opt? - If your project does not require Python or if it cannot meet the specific requirement of having Python ≥ 3.10 - In scenarios where CI/CD integration is not a priority for your AI workflow optimization ### When should I avoid future-agi? You require immediate Kubernetes or Helm support, as these are not yet available, though they are in development. You are seeking a managed service or a solution available through AWS Marketplace, as these options are not yet available, though they are planned for the future. Your project is in a highly dynamic environment where frequent updates and vendor support are critical, as Future-AGI is a community-driven project with a focus on self-hosting and open-source. ### Is agent-opt or future-agi more popular on GitHub? future-agi has more GitHub stars (2,032 vs 75). Stars measure visibility, not whether either tool fits your constraints. ### Are agent-opt and future-agi open source? Yes - both are open-source projects on GitHub (agent-opt: Apache-2.0, future-agi: Apache-2.0). ### Where can I find alternatives to agent-opt or future-agi? GraphCanon lists graph-backed alternatives at [agent-opt alternatives](/tools/future-agi-agent-opt/alternatives) and [future-agi alternatives](/tools/future-agi-future-agi/alternatives) ([agent-opt markdown twin](/tools/future-agi-agent-opt/alternatives.md), [future-agi markdown twin](/tools/future-agi-future-agi/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/future-agi-agent-opt-vs-future-agi-future-agi.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, agent-opt or future-agi? agent-opt: Archived. future-agi: 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 agent-opt and future-agi? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [agent-opt trust report](/tools/future-agi-agent-opt/trust); [future-agi trust report](/tools/future-agi-future-agi/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=future-agi-agent-opt`](/api/graphcanon/graph?tool=future-agi-agent-opt) - 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/_