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Comparison

human-eval vs auto-evaluator

Verdict

Pick human-eval if human-eval is a tool designed for evaluating large language models trained specifically on code through human-written tests; 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 · human-eval alternatives · auto-evaluator alternatives

GraphCanon updated 2w

human-eval logo

human-eval

openai/human-eval

★ 3.3kpushed Jan 17, 2025
vs
auto-evaluator logo

auto-evaluator

rlancemartin/auto-evaluator

★ 1.1kpushed May 10, 2023

Trust & integrity

Signalhuman-evalauto-evaluator
Maintenance
Dormant (564d since push)
As of 2w · github_public_v1
Dormant (1186d since push)
As of 2w · github_public_v1
Provenance
Not a fork · Organization account
As of 2w · github_public_v1
Not a fork · Personal account
As of 2w · github_public_v1
OSV dependency advisories
No published findings from this source as of 2026-07-11
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
human-eval trust reportauto-evaluator trust reportTrust methodology

Tagline

human-eval
Evaluating Large Language Models Trained on Code
auto-evaluator
A lightweight evaluation tool for question-answering using Langchain

Stars

human-eval
3.3k
auto-evaluator
1.1k

Forks

human-eval
452
auto-evaluator
92

Open issues

human-eval
44
auto-evaluator
3

Language

human-eval
Python
auto-evaluator
Python

Adopt for

human-eval
human-eval is a tool designed for evaluating large language models trained specifically on code through human-written tests.
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

human-eval
-
auto-evaluator
-

Runtime

human-eval
-
auto-evaluator
-

License

human-eval
MIT
auto-evaluator
-

Last pushed

human-eval
Jan 17, 2025
auto-evaluator
May 10, 2023

Categories

human-eval
Evaluation & Observability
auto-evaluator
Evaluation & Observability

Trust and health

Days since push

human-eval
564d
auto-evaluator
1186d

Open issues (now)

human-eval
44
auto-evaluator
3

Owner type

human-eval
Organization
auto-evaluator
User

OSV dependency advisories

human-eval
No published findings from this source as of 2026-07-11
auto-evaluator
Published findings

Full report

human-eval
Trust report
auto-evaluator
Trust report

Shared compatibility

  • Python · human-eval: Python runtime · auto-evaluator: Python runtime

Choose human-eval if…

  • This evaluation framework must be installed and set up in your own environment, ensuring full control over the testing process.
  • Pricing: The software is available under an MIT license for free use, yet advanced features or services beyond its core functionality might incur costs..
  • Tags unique to human-eval: code evaluation, large language models, python.
  • When you need to evaluate the performance of AI systems that have been trained exclusively on code datasets, as it allows testing via human-created benchmarks relevant only to code-based models.

When NOT to use human-eval

  • If you are interested in evaluating general natural language processing tasks without coding context, as human-eval is tailored specifically for assessing code-focused AI systems.
  • When the required Python version is below 3.7; this tool mandates at least Python 3.7 to ensure compatibility with its dependencies.
GitHubDetails

Choose auto-evaluator if…

  • Tags unique to auto-evaluator: evaluation, gpt-3.5-turbo, langchain, llm.
  • 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.
GitHubDetails

Explore

human-eval trust report →auto-evaluator trust report →Evaluation & Observability category →All comparisonsStack workflowsTrending tools

Sources

Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.

GitHub stars on cards: human-eval 3.3k · auto-evaluator 1.1k (synced Aug 5, 2026).

Common questions

What is the difference between human-eval and auto-evaluator?
human-eval: Evaluating Large Language Models Trained on Code. 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 human-eval over auto-evaluator?
Choose human-eval over auto-evaluator when This evaluation framework must be installed and set up in your own environment, ensuring full control over the testing process; Pricing: The software is available under an MIT license for free use, yet advanced features or services beyond its core functionality might incur costs.; Tags unique to human-eval: code evaluation, large language models, python; When you need to evaluate the performance of AI systems that have been trained exclusively on code datasets, as it allows testing via human-created benchmarks relevant only to code-based models.
When should I choose auto-evaluator over human-eval?
Choose auto-evaluator over human-eval when Tags unique to auto-evaluator: evaluation, gpt-3.5-turbo, langchain, llm; Use when you need a lightweight solution for testing question-answering capabilities of Langchain models; Leaner open-issue backlog (3).
When should I avoid human-eval?
If you are interested in evaluating general natural language processing tasks without coding context, as human-eval is tailored specifically for assessing code-focused AI systems. When the required Python version is below 3.7; this tool mandates at least Python 3.7 to ensure compatibility with its dependencies.
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 human-eval or auto-evaluator more popular on GitHub?
human-eval has more GitHub stars (3,331 vs 1,105). Stars measure visibility, not whether either tool fits your constraints.
Are human-eval and auto-evaluator open source?
Yes - both are open-source projects on GitHub.
Where can I find alternatives to human-eval or auto-evaluator?
GraphCanon lists graph-backed alternatives at human-eval alternatives and auto-evaluator alternatives (human-eval 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, human-eval or auto-evaluator?
human-eval: Dormant. 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 human-eval and auto-evaluator?
GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: human-eval trust report; auto-evaluator trust report.

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