Home/Compare/deepeval vs Open-LLM-Leaderboard

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

deepeval logo

deepeval

confident-ai/deepeval

18kpushed Sep 18, 2026
vs
Open-LLM-Leaderboard logo

Open-LLM-Leaderboard

VILA-Lab/Open-LLM-Leaderboard

53pushed Jun 27, 2024

Trust & integrity

SignaldeepevalOpen-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 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.

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