--- title: "olmo-eval vs future-agi" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/allenai-olmo-eval-vs-future-agi-future-agi" tools: ["allenai-olmo-eval", "future-agi-future-agi"] --- # olmo-eval vs future-agi *GraphCanon updated Oct 12, 2026* ## Verdict Pick olmo-eval if olmo-eval is an evaluation framework for large language models, using uv for reproducible builds. It focuses on modular task implementations and integrates with various datasets via defined tasks; 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. [olmo-eval](https://github.com/allenai/olmo-eval) reports 72 GitHub stars, 23 forks, and 81 open issues, last pushed Oct 11, 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 [olmo-eval's repository](https://github.com/allenai/olmo-eval) and [future-agi's repository](https://github.com/future-agi/future-agi). | | [olmo-eval](/tools/allenai-olmo-eval.md) | [future-agi](/tools/future-agi-future-agi.md) | | --- | --- | --- | | Tagline | Olmo Evaluation Framework for LLM Tasks | Open-source, end-to-end platform for evaluating, observing, and improving LLM and AI agent applications | | Stars | 72 | 2,032 | | Forks | 23 | 627 | | Open issues | 81 | 961 | | Language | Python | Python | | Adopt for | Olmo-eval is an evaluation framework for large language models, using uv for reproducible builds. It focuses on modular task implementations and integrates with various datasets via defined tasks. | 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 | Evaluation & Observability | AI Agents, Evaluation & Observability, LLM Frameworks | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [olmo-eval](/tools/allenai-olmo-eval.md) | [future-agi](/tools/future-agi-future-agi.md) | | --- | --- | --- | | Open issues (now) | 81 | 961 | | Stars delta | +3 (30d) | +473 (30d) | | Open issues delta | +25 (30d) | +365 (30d) | | Full report | [trust report](/tools/allenai-olmo-eval/trust.md) | [trust report](/tools/future-agi-future-agi/trust.md) | ## Decision facts: olmo-eval - **Adopt for:** Olmo-eval is an evaluation framework for large language models, using uv for reproducible builds. It focuses on modular task implementations and integrates with various datasets via defined tasks. ## 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 olmo-eval if… - Tags unique to olmo-eval: datasets, evaluation, llm, python. - When you need a flexible evaluation setup that works with a variety of LLMs and datasets. - More recently updated (last pushed Oct 11, 2026). ### 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-agents, ai-evals, ai-gateway, ai-optimization. - Also covers AI Agents, LLM Frameworks. - You need a self-hostable solution that does not phone home, ensuring full control over your data and evaluation logic. ## When NOT to use olmo-eval - When you require a simpler setup that doesn't need the reproducibility constraints of uv builds. - If your project already has an established evaluation toolchain and does not benefit from introducing a new framework for manageability reasons. ## 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 olmo-eval and future-agi? olmo-eval: Olmo Evaluation Framework for LLM Tasks. 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 olmo-eval over future-agi? Choose olmo-eval over future-agi when Tags unique to olmo-eval: datasets, evaluation, llm, python; When you need a flexible evaluation setup that works with a variety of LLMs and datasets; More recently updated (last pushed Oct 11, 2026). ### When should I choose future-agi over olmo-eval? Choose future-agi over olmo-eval 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-agents, ai-evals, ai-gateway, ai-optimization; Also covers AI Agents, LLM Frameworks; You need a self-hostable solution that does not phone home, ensuring full control over your data and evaluation logic. ### When should I avoid olmo-eval? When you require a simpler setup that doesn't need the reproducibility constraints of uv builds. If your project already has an established evaluation toolchain and does not benefit from introducing a new framework for manageability reasons. ### 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 olmo-eval or future-agi more popular on GitHub? future-agi has more GitHub stars (2,032 vs 72). Stars measure visibility, not whether either tool fits your constraints. ### Are olmo-eval and future-agi open source? Yes - both are open-source projects on GitHub (olmo-eval: Apache-2.0, future-agi: Apache-2.0). ### Where can I find alternatives to olmo-eval or future-agi? GraphCanon lists graph-backed alternatives at [olmo-eval alternatives](/tools/allenai-olmo-eval/alternatives) and [future-agi alternatives](/tools/future-agi-future-agi/alternatives) ([olmo-eval markdown twin](/tools/allenai-olmo-eval/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/allenai-olmo-eval-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, olmo-eval or future-agi? olmo-eval: Very active. 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 olmo-eval and future-agi? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [olmo-eval trust report](/tools/allenai-olmo-eval/trust); [future-agi trust report](/tools/future-agi-future-agi/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=allenai-olmo-eval`](/api/graphcanon/graph?tool=allenai-olmo-eval) - 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/_