Comparison
agent-learning-kit vs VLMEvalKit
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 VLMEvalKit if vLMEvalKit is an open-source Python evaluation toolkit for large vision-language models that offers one-command evaluation with support for various benchmarks and models.
Markdown twin · agent-learning-kit alternatives · VLMEvalKit alternatives
GraphCanon updated 3d
vs
Trust & integrity
| Signal | agent-learning-kit | VLMEvalKit |
|---|---|---|
| Maintenance | Very active (0d since push) As of 2w · github_public_v1 | Very active (0d since push) As of 3d · github_public_v1 |
| Provenance | Not a fork · Organization account As of 2w · github_public_v1 | Not a fork · Organization account As of 3d · github_public_v1 |
| OSV dependency advisories | No lockfile (source not queried) As of 1mo · osv@v1 | Published findings 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
- VLMEvalKit
- An open-source evaluation toolkit for large vision-language models
Stars
- agent-learning-kit
- 118
- VLMEvalKit
- 4.3k
Forks
- agent-learning-kit
- 43
- VLMEvalKit
- 745
Open issues
- agent-learning-kit
- 6
- VLMEvalKit
- 285
Language
- agent-learning-kit
- Python
- VLMEvalKit
- 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.
- VLMEvalKit
- VLMEvalKit is an open-source Python evaluation toolkit for large vision-language models that offers one-command evaluation with support for various benchmarks and models.
Persona
- agent-learning-kit
- -
- VLMEvalKit
- -
Runtime
- agent-learning-kit
- -
- VLMEvalKit
- -
License
- agent-learning-kit
- Apache-2.0
- VLMEvalKit
- Apache-2.0
Last pushed
- agent-learning-kit
- Aug 1, 2026
- VLMEvalKit
- Aug 17, 2026
Categories
- agent-learning-kit
- Evaluation & Observability
- VLMEvalKit
- Evaluation & Observability
Trust and health
Open issues (now)
- agent-learning-kit
- 6
- VLMEvalKit
- 285
Stars delta
- agent-learning-kit
- Unknown
- VLMEvalKit
- +60 (30d)
Open issues delta
- agent-learning-kit
- Unknown
- VLMEvalKit
- +21 (30d)
OSV dependency advisories
- agent-learning-kit
- No lockfile (source not queried)
- VLMEvalKit
- Published findings
Full report
- agent-learning-kit
- Trust report
- VLMEvalKit
- Trust report
Shared compatibility
- Python · agent-learning-kit: Python runtime · VLMEvalKit: Python runtime
Choose agent-learning-kit if…
- 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.
- Leaner open-issue backlog (6).
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 VLMEvalKit if…
- Tags unique to VLMEvalKit: computer-vision, large language models, llm, multi-modal.
- When you need to evaluate models supporting thinking mode, as it provides a custom split_thinking function improving accuracy.
- More GitHub stars (4.3k vs 118) - visibility, not fit.
When NOT to use VLMEvalKit
- If your project requires evaluation tools that generate Excel files with individual cells larger than the default support of 32,767 characters and cannot switch to TSV format.
- When you do not need generation-based evaluation methods with exact matching and LLM-based answer extraction.
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 (open-compass/VLMEvalKit) · observed Aug 17, 2026
- GitHub forks (open-compass/VLMEvalKit) · observed Aug 17, 2026
- Last push (open-compass/VLMEvalKit) · observed Aug 17, 2026
- License file (Apache-2.0) · observed Aug 17, 2026
- Decision facts (enrichment) · observed Jul 14, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
GitHub stars on cards: agent-learning-kit 118 · VLMEvalKit 4.3k (synced Aug 1, 2026).
Common questions
- What is the difference between agent-learning-kit and VLMEvalKit?
- agent-learning-kit: Evaluation Framework for all your AI related Workflows. VLMEvalKit: An open-source evaluation toolkit for large vision-language models. See the comparison table for live GitHub stats and shared categories.
- When should I choose agent-learning-kit over VLMEvalKit?
- Choose agent-learning-kit over VLMEvalKit when 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; Leaner open-issue backlog (6).
- When should I choose VLMEvalKit over agent-learning-kit?
- Choose VLMEvalKit over agent-learning-kit when Tags unique to VLMEvalKit: computer-vision, large language models, llm, multi-modal; When you need to evaluate models supporting thinking mode, as it provides a custom split_thinking function improving accuracy; More GitHub stars (4.3k vs 118) - visibility, not fit.
- 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 VLMEvalKit?
- If your project requires evaluation tools that generate Excel files with individual cells larger than the default support of 32,767 characters and cannot switch to TSV format. When you do not need generation-based evaluation methods with exact matching and LLM-based answer extraction.
- Is agent-learning-kit or VLMEvalKit more popular on GitHub?
- VLMEvalKit has more GitHub stars (4,345 vs 118). Stars measure visibility, not whether either tool fits your constraints.
- Are agent-learning-kit and VLMEvalKit open source?
- Yes - both are open-source projects on GitHub (agent-learning-kit: Apache-2.0, VLMEvalKit: Apache-2.0).
- Where can I find alternatives to agent-learning-kit or VLMEvalKit?
- GraphCanon lists graph-backed alternatives at agent-learning-kit alternatives and VLMEvalKit alternatives (agent-learning-kit markdown twin, VLMEvalKit 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 VLMEvalKit?
- agent-learning-kit: Very active. VLMEvalKit: 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-learning-kit and VLMEvalKit?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: agent-learning-kit trust report; VLMEvalKit trust report.