Comparison
deepeval vs Open-LLM-Leaderboard
Verdict
Pick deepeval if deepeval is a Python-based framework designed for evaluating large language models with an array of metrics and evaluation methodologies; pick Open-LLM-Leaderboard if open-LLM-Leaderboard evaluates large language models on open-style questions using a GPT-4-based evaluator and aggregates results in an accessible leaderboard format.
Markdown twin · deepeval alternatives · Open-LLM-Leaderboard alternatives
GraphCanon updated Sep 20, 2026
12views this month
Trust & integrity
| Signal | deepeval | Open-LLM-Leaderboard |
|---|---|---|
| Maintenance | Very active (1d since push) As of Sep 20, 2026 · github_public_v1 | Dormant (804d since push) As of Sep 10, 2026 · github_public_v1 |
| Provenance | Not a fork · Organization account As of Sep 20, 2026 · github_public_v1 | Not a fork · Organization account As of Sep 10, 2026 · github_public_v1 |
| OSV dependency advisories | No lockfile (source not queried) As of Jul 11, 2026 · osv@v1 | No lockfile (source not queried) As of Jul 15, 2026 · 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
- deepeval
- LLM Evaluation Framework.
- Open-LLM-Leaderboard
- Tracks LLM performance on open-style questions
Stars
- deepeval
- 18k
- Open-LLM-Leaderboard
- 53
Forks
- deepeval
- 2.0k
- Open-LLM-Leaderboard
- 7
Open issues
- deepeval
- 624
- Open-LLM-Leaderboard
- 1
Language
- deepeval
- Python
- Open-LLM-Leaderboard
- Python
Adopt for
- deepeval
- Deepeval is a Python-based framework designed for evaluating large language models with an array of metrics and evaluation methodologies.
- Open-LLM-Leaderboard
- Open-LLM-Leaderboard evaluates large language models on open-style questions using a GPT-4-based evaluator and aggregates results in an accessible leaderboard format.
Persona
- deepeval
- -
- Open-LLM-Leaderboard
- -
Runtime
- deepeval
- -
- Open-LLM-Leaderboard
- -
License
- deepeval
- Apache-2.0 License
- Open-LLM-Leaderboard
- CC-BY-4.0
Last pushed
- deepeval
- Sep 18, 2026
- Open-LLM-Leaderboard
- Jun 27, 2024
Categories
- deepeval
- Evaluation & Observability
- Open-LLM-Leaderboard
- Evaluation & Observability
Trust and health
Maintenance
- deepeval
- Very active (96%)
- Open-LLM-Leaderboard
- Dormant (18%)
Days since push
- deepeval
- 1d
- Open-LLM-Leaderboard
- 804d
Open issues (now)
- deepeval
- 624
- Open-LLM-Leaderboard
- 1
Stars delta
- deepeval
- +1.1k (30d)
- Open-LLM-Leaderboard
- 0 (30d)
Open issues delta
- deepeval
- +220 (30d)
- Open-LLM-Leaderboard
- 0 (30d)
Full report
- deepeval
- Trust report
- Open-LLM-Leaderboard
- Trust report
Shared compatibility
- Python · deepeval: Python runtime · Open-LLM-Leaderboard: Python runtime
Choose deepeval if…
- License: deepeval is Apache-2.0, Open-LLM-Leaderboard is CC-BY-4.0.
- Requirements: Requires Python environment and familiarity with large language models to effectively utilize Deepeval's capabilities..
- Tags unique to deepeval: evaluation, metrics.
- When developing large language models and you need a comprehensive evaluation framework to measure their performance across various metrics.
When NOT to use deepeval
- For small-scale applications that do not require the depth of metrics and evaluations offered by Deepeval, as it might be overkill.
- In situations where there is a need for real-time performance monitoring, since Deepeval focuses more on post-development evaluation rather than continuous runtime analysis.
Choose Open-LLM-Leaderboard if…
- License: Open-LLM-Leaderboard is CC-BY-4.0, deepeval is Apache-2.0.
- Tags unique to Open-LLM-Leaderboard: leaderboard, model-performance-tracking, open-style-questions.
- You need to evaluate your LLM's performance on open-ended, human-like question formats across multiple datasets without setting up the evaluation process yourself.
When NOT to use Open-LLM-Leaderboard
- You are seeking evaluations solely based on closed-response or multiple-choice questions where specific answers can be easily verified by non-LLM means.
- Your project has constraints against using commercial LLMs like GPT-4 for evaluation due to cost, licensing issues, or the need for open-source alternatives.
Explore
Sources
Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.
- GitHub stars (confident-ai/deepeval) · observed Sep 20, 2026
- GitHub forks (confident-ai/deepeval) · observed Sep 20, 2026
- Last push (confident-ai/deepeval) · observed Sep 18, 2026
- License file (Apache-2.0) · observed Sep 20, 2026
- Decision facts (enrichment) · observed Jul 17, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
- GitHub stars (VILA-Lab/Open-LLM-Leaderboard) · observed Sep 20, 2026
- GitHub forks (VILA-Lab/Open-LLM-Leaderboard) · observed Sep 20, 2026
- Last push (VILA-Lab/Open-LLM-Leaderboard) · observed Jun 27, 2024
- License file (CC-BY-4.0) · observed Sep 20, 2026
- Decision facts (enrichment) · observed Jul 16, 2026
- Trust scan (lockfile / OSV) · observed Jul 15, 2026
GitHub stars on cards: deepeval 18k · Open-LLM-Leaderboard 53 (synced Sep 20, 2026).
Common questions
- What is the difference between deepeval and Open-LLM-Leaderboard?
- deepeval: LLM Evaluation Framework.. Open-LLM-Leaderboard: Tracks LLM performance on open-style questions. See the comparison table for live GitHub stats and shared categories.
- When should I choose deepeval over Open-LLM-Leaderboard?
- Choose deepeval over Open-LLM-Leaderboard when License: deepeval is Apache-2.0, Open-LLM-Leaderboard is CC-BY-4.0; Requirements: Requires Python environment and familiarity with large language models to effectively utilize Deepeval's capabilities.; Tags unique to deepeval: evaluation, metrics; When developing large language models and you need a comprehensive evaluation framework to measure their performance across various metrics.
- When should I choose Open-LLM-Leaderboard over deepeval?
- Choose Open-LLM-Leaderboard over deepeval when License: Open-LLM-Leaderboard is CC-BY-4.0, deepeval is Apache-2.0; Tags unique to Open-LLM-Leaderboard: leaderboard, model-performance-tracking, open-style-questions; You need to evaluate your LLM's performance on open-ended, human-like question formats across multiple datasets without setting up the evaluation process yourself.
- When should I avoid deepeval?
- For small-scale applications that do not require the depth of metrics and evaluations offered by Deepeval, as it might be overkill. In situations where there is a need for real-time performance monitoring, since Deepeval focuses more on post-development evaluation rather than continuous runtime analysis.
- When should I avoid Open-LLM-Leaderboard?
- You are seeking evaluations solely based on closed-response or multiple-choice questions where specific answers can be easily verified by non-LLM means. Your project has constraints against using commercial LLMs like GPT-4 for evaluation due to cost, licensing issues, or the need for open-source alternatives.
- Is deepeval or Open-LLM-Leaderboard more popular on GitHub?
- deepeval has more GitHub stars (18,341 vs 53). Stars measure visibility, not whether either tool fits your constraints.
- Are deepeval and Open-LLM-Leaderboard open source?
- Yes - both are open-source projects on GitHub (deepeval: Apache-2.0, Open-LLM-Leaderboard: CC-BY-4.0).
- Where can I find alternatives to deepeval or Open-LLM-Leaderboard?
- GraphCanon lists graph-backed alternatives at deepeval alternatives and Open-LLM-Leaderboard alternatives (deepeval markdown twin, Open-LLM-Leaderboard 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, deepeval or Open-LLM-Leaderboard?
- deepeval: Very active. Open-LLM-Leaderboard: Dormant. 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 deepeval and Open-LLM-Leaderboard?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: deepeval trust report; Open-LLM-Leaderboard trust report.