--- title: "lm-evaluation-harness vs futureagi-sdk" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/eleutherai-lm-evaluation-harness-vs-future-agi-futureagi-sdk" tools: ["eleutherai-lm-evaluation-harness", "future-agi-futureagi-sdk"] --- # lm-evaluation-harness vs futureagi-sdk *GraphCanon updated Aug 7, 2026* ## Verdict Pick lm-evaluation-harness if lm-evaluation-harness is a Python framework for evaluating language models in various parallelism modes using different checkpoint formats, compatible with the Megatron-LM backend; pick futureagi-sdk if future AGI SDK is an innovative toolkit designed for production-grade AI evaluation, prompt management, and observability. It supports Python and TypeScript languages and is licensed under Apache-2.0. [lm-evaluation-harness](https://www.eleuther.ai) reports 14k GitHub stars, 3.5k forks, and 938 open issues, last pushed Jul 13, 2026. [futureagi-sdk](https://app.futureagi.com) has 48 stars, 5 forks, and 3 open issues, last pushed Jul 8, 2026. Figures are from public GitHub metadata via [lm-evaluation-harness's repository](https://github.com/EleutherAI/lm-evaluation-harness) and [futureagi-sdk's repository](https://github.com/future-agi/futureagi-sdk). | | [lm-evaluation-harness](/tools/eleutherai-lm-evaluation-harness.md) | [futureagi-sdk](/tools/future-agi-futureagi-sdk.md) | | --- | --- | --- | | Tagline | A framework for few-shot evaluation of language models. | Production-grade AI evaluation, prompt management & observability SDK | | Stars | 13,560 | 48 | | Forks | 3,467 | 5 | | Open issues | 938 | 3 | | Language | Python | Python | | Adopt for | lm-evaluation-harness is a Python framework for evaluating language models in various parallelism modes using different checkpoint formats, compatible with the Megatron-LM backend. | Future AGI SDK is an innovative toolkit designed for production-grade AI evaluation, prompt management, and observability. It supports Python and TypeScript languages and is licensed under Apache-2.0. | | Persona | - | - | | Runtime | - | - | | License | MIT | The Future AGI SDK uses the Apache License, Version 2.0 (Apache-2.0). It allows users to freely use, modify, and distribute the software while maintaining copyright notices. | | Categories | Evaluation & Observability | Evaluation & Observability | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [lm-evaluation-harness](/tools/eleutherai-lm-evaluation-harness.md) | [futureagi-sdk](/tools/future-agi-futureagi-sdk.md) | | --- | --- | --- | | Days since push | 24d | 25d | | Open issues (now) | 938 | 3 | | Full report | [trust report](/tools/eleutherai-lm-evaluation-harness/trust.md) | [trust report](/tools/future-agi-futureagi-sdk/trust.md) | ## Decision facts: lm-evaluation-harness - **Adopt for:** lm-evaluation-harness is a Python framework for evaluating language models in various parallelism modes using different checkpoint formats, compatible with the Megatron-LM backend. ## Decision facts: futureagi-sdk - **Requirements:** Supports Python and TypeScript languages; Automated evaluations with sub-100ms guardrails - **Adopt for:** Future AGI SDK is an innovative toolkit designed for production-grade AI evaluation, prompt management, and observability. It supports Python and TypeScript languages and is licensed under Apache-2.0. - **License detail:** The Future AGI SDK uses the Apache License, Version 2.0 (Apache-2.0). It allows users to freely use, modify, and distribute the software while maintaining copyright notices. ## Choose when ### Choose lm-evaluation-harness if… - License: lm-evaluation-harness is MIT, futureagi-sdk is Apache-2.0. - Tags unique to lm-evaluation-harness: data-parallelism, evaluation-framework, expert-parallelism, language-model. - - When you need to evaluate large language models across multiple GPUs in data or tensor parallel configurations. ### Choose futureagi-sdk if… - License: futureagi-sdk is Apache-2.0, lm-evaluation-harness is MIT. - Requirements: Supports Python and TypeScript languages; Automated evaluations with sub-100ms guardrails. - Tags unique to futureagi-sdk: ai-agents, annotations, dataset, development. - Future AGI SDK is an innovative toolkit designed for production-grade AI evaluation, prompt management, and observability. It supports Python and TypeScript languages and is licensed under Apache-2.0. ## When NOT to use lm-evaluation-harness - - If your evaluation setup requires pipeline parallelism not currently supported by this framework. ## When NOT to use futureagi-sdk - Evaluation & Observability: Defer heavyweight eval infra only until you have real traffic - never skip it once users depend on answers. ## Common questions ### What is the difference between lm-evaluation-harness and futureagi-sdk? lm-evaluation-harness: A framework for few-shot evaluation of language models.. futureagi-sdk: Production-grade AI evaluation, prompt management & observability SDK. See the comparison table for live GitHub stats and shared categories. ### When should I choose lm-evaluation-harness over futureagi-sdk? Choose lm-evaluation-harness over futureagi-sdk when License: lm-evaluation-harness is MIT, futureagi-sdk is Apache-2.0; Tags unique to lm-evaluation-harness: data-parallelism, evaluation-framework, expert-parallelism, language-model; - When you need to evaluate large language models across multiple GPUs in data or tensor parallel configurations. ### When should I choose futureagi-sdk over lm-evaluation-harness? Choose futureagi-sdk over lm-evaluation-harness when License: futureagi-sdk is Apache-2.0, lm-evaluation-harness is MIT; Requirements: Supports Python and TypeScript languages; Automated evaluations with sub-100ms guardrails; Tags unique to futureagi-sdk: ai-agents, annotations, dataset, development; Future AGI SDK is an innovative toolkit designed for production-grade AI evaluation, prompt management, and observability. It supports Python and TypeScript languages and is licensed under Apache-2.0. ### When should I avoid lm-evaluation-harness? - If your evaluation setup requires pipeline parallelism not currently supported by this framework. ### When should I avoid futureagi-sdk? Evaluation & Observability: Defer heavyweight eval infra only until you have real traffic - never skip it once users depend on answers. ### Is lm-evaluation-harness or futureagi-sdk more popular on GitHub? lm-evaluation-harness has more GitHub stars (13,560 vs 48). Stars measure visibility, not whether either tool fits your constraints. ### Are lm-evaluation-harness and futureagi-sdk open source? Yes - both are open-source projects on GitHub (lm-evaluation-harness: MIT, futureagi-sdk: Apache-2.0). ### Where can I find alternatives to lm-evaluation-harness or futureagi-sdk? GraphCanon lists graph-backed alternatives at [lm-evaluation-harness alternatives](/tools/eleutherai-lm-evaluation-harness/alternatives) and [futureagi-sdk alternatives](/tools/future-agi-futureagi-sdk/alternatives) ([lm-evaluation-harness markdown twin](/tools/eleutherai-lm-evaluation-harness/alternatives.md), [futureagi-sdk markdown twin](/tools/future-agi-futureagi-sdk/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/eleutherai-lm-evaluation-harness-vs-future-agi-futureagi-sdk.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, lm-evaluation-harness or futureagi-sdk? lm-evaluation-harness: Active. futureagi-sdk: 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 lm-evaluation-harness and futureagi-sdk? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [lm-evaluation-harness trust report](/tools/eleutherai-lm-evaluation-harness/trust); [futureagi-sdk trust report](/tools/future-agi-futureagi-sdk/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=eleutherai-lm-evaluation-harness`](/api/graphcanon/graph?tool=eleutherai-lm-evaluation-harness) - 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/_