Comparison
agent-learning-kit vs lighteval
Verdict
Pick agent-learning-kit if agent-learning-kit is a Python framework for evaluating AI-related workflows with modules for faithfulness assessment, embedding similarity analysis, and feedback loop integration via ChromaDB; pick lighteval if lighteval is designed for evaluating language models across multiple backends. It integrates well with Hugging Face and provides a wide range of extras, making it particularly handy in non-Windows environments.
Markdown twin · agent-learning-kit alternatives · lighteval alternatives
GraphCanon updated 2w
vs
Trust & integrity
| Signal | agent-learning-kit | lighteval |
|---|---|---|
| Maintenance | Very active (0d since push) As of 2w · github_public_v1 | Steady (38d since push) As of 2w · github_public_v1 |
| Provenance | Not a fork · Organization account As of 2w · github_public_v1 | Not a fork · Organization account As of 2w · 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
- agent-learning-kit
- Evaluation Framework for all your AI related Workflows
- lighteval
- All-in-one toolkit for evaluating LLMs across multiple backends
Stars
- agent-learning-kit
- 118
- lighteval
- 2.5k
Forks
- agent-learning-kit
- 43
- lighteval
- 523
Open issues
- agent-learning-kit
- 6
- lighteval
- 366
Language
- agent-learning-kit
- Python
- lighteval
- Python
Adopt for
- agent-learning-kit
- Agent-learning-kit is a Python framework for evaluating AI-related workflows with modules for faithfulness assessment, embedding similarity analysis, and feedback loop integration via ChromaDB.
- lighteval
- Lighteval is designed for evaluating language models across multiple backends. It integrates well with Hugging Face and provides a wide range of extras, making it particularly handy in non-Windows environments.
Persona
- agent-learning-kit
- -
- lighteval
- -
Runtime
- agent-learning-kit
- -
- lighteval
- -
License
- agent-learning-kit
- Apache-2.0
- lighteval
- MIT
Last pushed
- agent-learning-kit
- Aug 1, 2026
- lighteval
- Jun 29, 2026
Categories
- agent-learning-kit
- Evaluation & Observability
- lighteval
- Evaluation & Observability
Trust and health
Maintenance
- agent-learning-kit
- Very active (96%)
- lighteval
- Steady (60%)
Days since push
- agent-learning-kit
- 0d
- lighteval
- 38d
Open issues (now)
- agent-learning-kit
- 6
- lighteval
- 366
Full report
- agent-learning-kit
- Trust report
- lighteval
- Trust report
Shared compatibility
- Python · agent-learning-kit: Python runtime · lighteval: Python runtime
Choose agent-learning-kit if…
- License: agent-learning-kit is Apache-2.0, lighteval is MIT.
- Tags unique to agent-learning-kit: ai-agents, ci-cd, ml.
- When you need comprehensive evaluation of your AI models including faithfulness checks using DeBERTa NLI model installed.
When NOT to use agent-learning-kit
- If your workflow does not align with the specific evaluation criteria and methods supported by agent-learning-kit.
- When you seek a framework that integrates with backend systems other than those provided as optional extras, such as MongoDB or DynamoDB instead of ChromaDB.
Choose lighteval if…
- License: lighteval is MIT, agent-learning-kit is Apache-2.0.
- Tags unique to lighteval: evaluation-framework, evaluation-metrics, huggingface, python.
- When you need to evaluate the performance of various LLMs on different backend infrastructures, especially if you are working within Mac/Linux environments.
When NOT to use lighteval
- Avoid Lighteval for evaluations on Windows systems as it is currently untested and not supported there.
- Should you require a solution that does not integrate with or depend on the Hugging Face ecosystem, Lighteval might not fulfill your needs.
Explore
Sources
Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.
- GitHub stars (future-agi/agent-learning-kit) · observed Aug 1, 2026
- GitHub forks (future-agi/agent-learning-kit) · observed Aug 1, 2026
- Last push (future-agi/agent-learning-kit) · observed Aug 1, 2026
- License file (Apache-2.0) · observed Aug 1, 2026
- Decision facts (enrichment) · observed Jul 14, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
- GitHub stars (huggingface/lighteval) · observed Aug 7, 2026
- GitHub forks (huggingface/lighteval) · observed Aug 7, 2026
- Last push (huggingface/lighteval) · observed Jun 29, 2026
- License file (MIT) · observed Aug 7, 2026
- Decision facts (enrichment) · observed Jul 12, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
GitHub stars on cards: agent-learning-kit 118 · lighteval 2.5k (synced Aug 1, 2026).
Common questions
- What is the difference between agent-learning-kit and lighteval?
- agent-learning-kit: Evaluation Framework for all your AI related Workflows. lighteval: All-in-one toolkit for evaluating LLMs across multiple backends. See the comparison table for live GitHub stats and shared categories.
- When should I choose agent-learning-kit over lighteval?
- Choose agent-learning-kit over lighteval when License: agent-learning-kit is Apache-2.0, lighteval is MIT; Tags unique to agent-learning-kit: ai-agents, ci-cd, ml; When you need comprehensive evaluation of your AI models including faithfulness checks using DeBERTa NLI model installed.
- When should I choose lighteval over agent-learning-kit?
- Choose lighteval over agent-learning-kit when License: lighteval is MIT, agent-learning-kit is Apache-2.0; Tags unique to lighteval: evaluation-framework, evaluation-metrics, huggingface, python; When you need to evaluate the performance of various LLMs on different backend infrastructures, especially if you are working within Mac/Linux environments.
- When should I avoid agent-learning-kit?
- If your workflow does not align with the specific evaluation criteria and methods supported by agent-learning-kit. When you seek a framework that integrates with backend systems other than those provided as optional extras, such as MongoDB or DynamoDB instead of ChromaDB.
- When should I avoid lighteval?
- Avoid Lighteval for evaluations on Windows systems as it is currently untested and not supported there. Should you require a solution that does not integrate with or depend on the Hugging Face ecosystem, Lighteval might not fulfill your needs.
- Is agent-learning-kit or lighteval more popular on GitHub?
- lighteval has more GitHub stars (2,508 vs 118). Stars measure visibility, not whether either tool fits your constraints.
- Are agent-learning-kit and lighteval open source?
- Yes - both are open-source projects on GitHub (agent-learning-kit: Apache-2.0, lighteval: MIT).
- Where can I find alternatives to agent-learning-kit or lighteval?
- GraphCanon lists graph-backed alternatives at agent-learning-kit alternatives and lighteval alternatives (agent-learning-kit markdown twin, lighteval 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, agent-learning-kit or lighteval?
- agent-learning-kit: Very active. lighteval: Steady. 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-learning-kit and lighteval?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: agent-learning-kit trust report; lighteval trust report.