Comparison
simple-evals vs auto-evaluator
Verdict
Pick simple-evals if simple-evals provides lightweight tools for evaluating language models using reference implementations from HealthBench, BrowseComp, SimpleQA. Last updates July 2025; 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 · simple-evals alternatives · auto-evaluator alternatives
GraphCanon updated 2w
vs
Trust & integrity
| Signal | simple-evals | auto-evaluator |
|---|---|---|
| Maintenance | Slowing (106d 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 lockfile (source not queried) 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 |
Tagline
- simple-evals
- A lightweight library for evaluating language models.
- auto-evaluator
- A lightweight evaluation tool for question-answering using Langchain
Stars
- simple-evals
- 4.6k
- auto-evaluator
- 1.1k
Forks
- simple-evals
- 501
- auto-evaluator
- 92
Open issues
- simple-evals
- 56
- auto-evaluator
- 3
Language
- simple-evals
- Python
- auto-evaluator
- Python
Adopt for
- simple-evals
- simple-evals provides lightweight tools for evaluating language models using reference implementations from HealthBench, BrowseComp, SimpleQA. Last updates July 2025.
- 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
- simple-evals
- -
- auto-evaluator
- -
Runtime
- simple-evals
- -
- auto-evaluator
- -
License
- simple-evals
- MIT licensed Python library for transparent language model evaluations with specific benchmark support until July 2025.
- auto-evaluator
- -
Last pushed
- simple-evals
- Apr 22, 2026
- auto-evaluator
- May 10, 2023
Categories
- simple-evals
- Evaluation & Observability
- auto-evaluator
- Evaluation & Observability
Trust and health
Maintenance
- simple-evals
- Slowing (36%)
- auto-evaluator
- Dormant (18%)
Days since push
- simple-evals
- 106d
- auto-evaluator
- 1186d
Open issues (now)
- simple-evals
- 56
- auto-evaluator
- 3
Owner type
- simple-evals
- Organization
- auto-evaluator
- User
OSV dependency advisories
- simple-evals
- No lockfile (source not queried)
- auto-evaluator
- Published findings
Full report
- simple-evals
- Trust report
- auto-evaluator
- Trust report
Choose simple-evals if…
- Tags unique to simple-evals: benchmark, depreciation notice, language-models.
- When you need a stable baseline to evaluate model performance with specific benchmarks like MMLU, HumanEval, and DROP that won't change after July 2025
- More GitHub stars (4.6k vs 1.1k) - visibility, not fit.
When NOT to use simple-evals
- For evaluating models released or significantly updated after July 2025, as this tool does not include future benchmarks
- When you need a tool that will adapt and expand its benchmark set with emerging model releases and evaluation tasks beyond 2025
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 (openai/simple-evals) · observed Aug 7, 2026
- GitHub forks (openai/simple-evals) · observed Aug 7, 2026
- Last push (openai/simple-evals) · observed Apr 22, 2026
- License file (MIT) · observed Aug 7, 2026
- Decision facts (enrichment) · observed Jul 14, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
- GitHub stars (rlancemartin/auto-evaluator) · observed Aug 8, 2026
- GitHub forks (rlancemartin/auto-evaluator) · observed Aug 8, 2026
- Last push (rlancemartin/auto-evaluator) · observed May 10, 2023
- License file (unknown) · observed Aug 8, 2026
- Decision facts (enrichment) · observed Jul 15, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
GitHub stars on cards: simple-evals 4.6k · auto-evaluator 1.1k (synced Aug 7, 2026).
Common questions
- What is the difference between simple-evals and auto-evaluator?
- simple-evals: A lightweight library for evaluating language models.. 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 simple-evals over auto-evaluator?
- Choose simple-evals over auto-evaluator when Tags unique to simple-evals: benchmark, depreciation notice, language-models; When you need a stable baseline to evaluate model performance with specific benchmarks like MMLU, HumanEval, and DROP that won't change after July 2025; More GitHub stars (4.6k vs 1.1k) - visibility, not fit.
- When should I choose auto-evaluator over simple-evals?
- Choose auto-evaluator over simple-evals 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 simple-evals?
- For evaluating models released or significantly updated after July 2025, as this tool does not include future benchmarks When you need a tool that will adapt and expand its benchmark set with emerging model releases and evaluation tasks beyond 2025
- 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 simple-evals or auto-evaluator more popular on GitHub?
- simple-evals has more GitHub stars (4,595 vs 1,105). Stars measure visibility, not whether either tool fits your constraints.
- Are simple-evals and auto-evaluator open source?
- Yes - both are open-source projects on GitHub.
- Where can I find alternatives to simple-evals or auto-evaluator?
- GraphCanon lists graph-backed alternatives at simple-evals alternatives and auto-evaluator alternatives (simple-evals 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, simple-evals or auto-evaluator?
- simple-evals: Slowing. 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 simple-evals and auto-evaluator?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: simple-evals trust report; auto-evaluator trust report.