Comparison
deepeval vs auto-evaluator
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 auto-evaluator if auto-evaluator is a Python-based tool designed for evaluating LLM QA chains with the capability to auto-generate question-answer pairs from user-provided documents and evaluate answers using configurations chosen via UI.
Markdown twin · deepeval alternatives · auto-evaluator alternatives
GraphCanon updated Sep 20, 2026
vs
Trust & integrity
| Signal | deepeval | auto-evaluator |
|---|---|---|
| Maintenance | Very active (1d since push) As of Sep 20, 2026 · github_public_v1 | Dormant (1216d since push) As of Sep 8, 2026 · github_public_v1 |
| Provenance | Not a fork · Organization account As of Sep 20, 2026 · github_public_v1 | Not a fork · Personal account As of Sep 8, 2026 · github_public_v1 |
| OSV dependency advisories | No lockfile (source not queried) As of Jul 11, 2026 · osv@v1 | Published findings As of Jul 11, 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.
- auto-evaluator
- A lightweight evaluation tool for question-answering using Langchain
Stars
- deepeval
- 18k
- auto-evaluator
- 1.1k
Forks
- deepeval
- 2.0k
- auto-evaluator
- 92
Open issues
- deepeval
- 624
- auto-evaluator
- 3
Language
- deepeval
- Python
- auto-evaluator
- Python
Adopt for
- deepeval
- Deepeval is a Python-based framework designed for evaluating large language models with an array of metrics and evaluation methodologies.
- auto-evaluator
- Auto-evaluator is a Python-based tool designed for evaluating LLM QA chains with the capability to auto-generate question-answer pairs from user-provided documents and evaluate answers using configurations chosen via UI.
Persona
- deepeval
- -
- auto-evaluator
- -
Runtime
- deepeval
- -
- auto-evaluator
- -
License
- deepeval
- Apache-2.0 License
- auto-evaluator
- -
Last pushed
- deepeval
- Sep 18, 2026
- auto-evaluator
- May 10, 2023
Categories
- deepeval
- Evaluation & Observability
- auto-evaluator
- Evaluation & Observability
Trust and health
Maintenance
- deepeval
- Very active (96%)
- auto-evaluator
- Dormant (18%)
Days since push
- deepeval
- 1d
- auto-evaluator
- 1216d
Open issues (now)
- deepeval
- 624
- auto-evaluator
- 3
Stars delta
- deepeval
- +1.1k (30d)
- auto-evaluator
- -3 (30d)
Open issues delta
- deepeval
- +220 (30d)
- auto-evaluator
- 0 (30d)
Owner type
- deepeval
- Organization
- auto-evaluator
- User
OSV dependency advisories
- deepeval
- No lockfile (source not queried)
- auto-evaluator
- Published findings
Full report
- deepeval
- Trust report
- auto-evaluator
- Trust report
Shared compatibility
- Python · deepeval: Python runtime · auto-evaluator: Python runtime
Choose deepeval if…
- Requirements: Requires Python environment and familiarity with large language models to effectively utilize Deepeval's capabilities..
- Tags unique to deepeval: llm-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 auto-evaluator if…
- Tags unique to auto-evaluator: gpt-3.5-turbo, langchain, llm, question-answering.
- Use when you need a lightweight solution for testing question-answering capabilities of Langchain models.
- Leaner open-issue backlog (3).
When NOT to use auto-evaluator
- Avoid using this tool when you do not have access to an OpenAI API key providing access to GPT-4, as it uses that by default for optimal settings.
- If you are looking for a tool that does not require you to input documents for question generation and prefer a more customized prompt approach rather than the auto-generation feature.
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 (rlancemartin/auto-evaluator) · observed Sep 20, 2026
- GitHub forks (rlancemartin/auto-evaluator) · observed Sep 20, 2026
- Last push (rlancemartin/auto-evaluator) · observed May 10, 2023
- License file (unknown) · observed Sep 20, 2026
- Decision facts (enrichment) · observed Jul 15, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
GitHub stars on cards: deepeval 18k · auto-evaluator 1.1k (synced Sep 20, 2026).
Common questions
- What is the difference between deepeval and auto-evaluator?
- deepeval: LLM Evaluation Framework.. auto-evaluator: A lightweight evaluation tool for question-answering using Langchain. See the comparison table for live GitHub stats and shared categories.
- When should I choose deepeval over auto-evaluator?
- Choose deepeval over auto-evaluator when Requirements: Requires Python environment and familiarity with large language models to effectively utilize Deepeval's capabilities.; Tags unique to deepeval: llm-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 auto-evaluator over deepeval?
- Choose auto-evaluator over deepeval when Tags unique to auto-evaluator: gpt-3.5-turbo, langchain, llm, question-answering; Use when you need a lightweight solution for testing question-answering capabilities of Langchain models; Leaner open-issue backlog (3).
- 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 auto-evaluator?
- Avoid using this tool when you do not have access to an OpenAI API key providing access to GPT-4, as it uses that by default for optimal settings. If you are looking for a tool that does not require you to input documents for question generation and prefer a more customized prompt approach rather than the auto-generation feature.
- Is deepeval or auto-evaluator more popular on GitHub?
- deepeval has more GitHub stars (18,342 vs 1,102). Stars measure visibility, not whether either tool fits your constraints.
- Are deepeval and auto-evaluator open source?
- Yes - both are open-source projects on GitHub.
- Where can I find alternatives to deepeval or auto-evaluator?
- GraphCanon lists graph-backed alternatives at deepeval alternatives and auto-evaluator alternatives (deepeval markdown twin, auto-evaluator 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 auto-evaluator?
- deepeval: Very active. auto-evaluator: 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 auto-evaluator?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: deepeval trust report; auto-evaluator trust report.