Home/Compare/deepeval vs awesome-hallucination-detection

Comparison

deepeval vs awesome-hallucination-detection

Verdict

Pick deepeval when tags unique to deepeval: evaluation framework, evaluation-metrics, llm-evaluation, llm-evaluation-framework; pick awesome-hallucination-detection when tags unique to awesome-hallucination-detection: evaluation, hallucination, llms, nlp.

Markdown twin · deepeval alternatives · awesome-hallucination-detection alternatives

GraphCanon updated today

deepeval logo

deepeval

confident-ai/deepeval

17kpushed Jul 10, 2026
vs
awesome-hallucination-detection logo

awesome-hallucination-detection

EdinburghNLP/awesome-hallucination-detection

1.1kpushed Jun 6, 2026

Trust & integrity

Signaldeepevalawesome-hallucination-detection
Maintenance
Very active (0d since push)
As of today · github_public_v1
Steady (35d since push)
As of today · github_public_v1
Provenance
Not a fork · Organization account
As of today · github_public_v1
Not a fork · Organization account
As of today · github_public_v1
Security (OSV)
No lockfile
As of today · none
No lockfile
As of today · none

Tagline

deepeval
The LLM Evaluation Framework
awesome-hallucination-detection
List of papers on hallucination detection in LLMs.

Stars

deepeval
17k
awesome-hallucination-detection
1.1k

Forks

deepeval
1.6k
awesome-hallucination-detection
89

Open issues

deepeval
334
awesome-hallucination-detection
0

Language

deepeval
Python
awesome-hallucination-detection
-

Adopt for

deepeval
-
awesome-hallucination-detection
awesome-hallucination-detection provides a curated list of research papers focused on techniques to detect and mitigate hallucinations in large language models (LLMs), including process supervision methods for factual QA

Persona

deepeval
-
awesome-hallucination-detection
-

Runtime

deepeval
-
awesome-hallucination-detection
-

License

deepeval
Apache-2.0
awesome-hallucination-detection
Apache-2.0

Last pushed

deepeval
Jul 10, 2026
awesome-hallucination-detection
Jun 6, 2026

Categories

deepeval
Evaluation & Observability, LLM Frameworks
awesome-hallucination-detection
Evaluation & Observability

Trust and health

Maintenance

deepeval
Very active (96%)
awesome-hallucination-detection
Steady (60%)

Days since push

deepeval
0d
awesome-hallucination-detection
35d

Open issues (now)

deepeval
334
awesome-hallucination-detection
0

Full report

deepeval
Trust report
awesome-hallucination-detection
Trust report

Choose deepeval if…

  • Tags unique to deepeval: evaluation framework, evaluation-metrics, llm-evaluation, llm-evaluation-framework.
  • Also covers LLM Frameworks.
  • More GitHub stars (17k vs 1.1k) - visibility, not fit.

When NOT to use deepeval

  • Evaluation & Observability: Defer heavyweight eval infra only until you have real traffic - never skip it once users depend on answers.
  • LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves.

Choose awesome-hallucination-detection if…

  • Tags unique to awesome-hallucination-detection: evaluation, hallucination, llms, nlp.
  • - When focusing on specific methodologies like Corpus Verify (CorVer) from the paper 'Verifiable Rewards Beyond Math and Code' which utilizes lightweight, process-based rewards to mitigate hallucinat
  • Leaner open-issue backlog (0).

When NOT to use awesome-hallucination-detection

  • - When the need is for immediate implementation or code rather than research papers — this repository only curates information about methodologies and benchmarks
  • - If your focus is on general LLM training techniques without a specific emphasis on hallucination detection or calibration

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 17k · awesome-hallucination-detection 1.1k (synced Jul 11, 2026).

Common questions

What is the difference between deepeval and awesome-hallucination-detection?
deepeval: The LLM Evaluation Framework. awesome-hallucination-detection: List of papers on hallucination detection in LLMs.. See the comparison table for live GitHub stats and shared categories.
When should I choose deepeval over awesome-hallucination-detection?
Choose deepeval over awesome-hallucination-detection when Tags unique to deepeval: evaluation framework, evaluation-metrics, llm-evaluation, llm-evaluation-framework; Also covers LLM Frameworks; More GitHub stars (17k vs 1.1k) - visibility, not fit.
When should I choose awesome-hallucination-detection over deepeval?
Choose awesome-hallucination-detection over deepeval when Tags unique to awesome-hallucination-detection: evaluation, hallucination, llms, nlp; - When focusing on specific methodologies like Corpus Verify (CorVer) from the paper 'Verifiable Rewards Beyond Math and Code' which utilizes lightweight, process-based rewards to mitigate hallucinat; Leaner open-issue backlog (0).
When should I avoid deepeval?
Evaluation & Observability: Defer heavyweight eval infra only until you have real traffic - never skip it once users depend on answers. LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves.
When should I avoid awesome-hallucination-detection?
- When the need is for immediate implementation or code rather than research papers — this repository only curates information about methodologies and benchmarks - If your focus is on general LLM training techniques without a specific emphasis on hallucination detection or calibration
Is deepeval or awesome-hallucination-detection more popular on GitHub?
deepeval has more GitHub stars (16,767 vs 1,116). Stars measure visibility, not whether either tool fits your constraints.
Are deepeval and awesome-hallucination-detection open source?
Yes - both are open-source projects on GitHub (deepeval: Apache-2.0, awesome-hallucination-detection: Apache-2.0).
Where can I find alternatives to deepeval or awesome-hallucination-detection?
GraphCanon lists graph-backed alternatives at deepeval alternatives and awesome-hallucination-detection alternatives (deepeval markdown twin, awesome-hallucination-detection 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 awesome-hallucination-detection?
deepeval: Very active. awesome-hallucination-detection: 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 deepeval and awesome-hallucination-detection?
GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: deepeval trust report; awesome-hallucination-detection trust report.