Home/Compare/instruct-eval vs hallucination-index

Comparison

instruct-eval vs hallucination-index

Verdict

Pick instruct-eval if key facts about instruct-eval; pick hallucination-index if hallucination-Index helps users identify LLMs with the lowest propensity for factual errors across varying context lengths and source types.

Markdown twin · instruct-eval alternatives · hallucination-index alternatives

GraphCanon updated 2w

instruct-eval logo

instruct-eval

declare-lab/instruct-eval

552pushed Mar 10, 2024
vs
hallucination-index logo

hallucination-index

rungalileo/hallucination-index

116pushed Jul 28, 2025

Trust & integrity

Signalinstruct-evalhallucination-index
Maintenance
Dormant (879d since push)
As of 2w · github_public_v1
Dormant (365d since push)
As of 3w · github_public_v1
Provenance
Not a fork · Organization account
As of 2w · github_public_v1
Not a fork · Organization account
As of 3w · github_public_v1
OSV dependency advisories
Published findings
As of 1mo · osv@v1
No lockfile (source not queried)
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

instruct-eval
Quantitative evaluation for instruction-tuned language models
hallucination-index
Initiative to evaluate and rank popular LLMs based on hallucination propensity

Stars

instruct-eval
552
hallucination-index
116

Forks

instruct-eval
45
hallucination-index
8

Open issues

instruct-eval
24
hallucination-index
1

Language

instruct-eval
Python
hallucination-index
-

Adopt for

instruct-eval
Key facts about instruct-eval
hallucination-index
Hallucination-Index helps users identify LLMs with the lowest propensity for factual errors across varying context lengths and source types.

Persona

instruct-eval
-
hallucination-index
-

Runtime

instruct-eval
-
hallucination-index
-

License

instruct-eval
The tool is distributed under Apache-2.0 license
hallucination-index
-

Last pushed

instruct-eval
Mar 10, 2024
hallucination-index
Jul 28, 2025

Categories

instruct-eval
Evaluation & Observability
hallucination-index
Evaluation & Observability

Trust and health

Days since push

instruct-eval
879d
hallucination-index
365d

Open issues (now)

instruct-eval
24
hallucination-index
1

OSV dependency advisories

instruct-eval
Published findings
hallucination-index
No lockfile (source not queried)

Full report

instruct-eval
Trust report
hallucination-index
Trust report

Choose instruct-eval if…

  • Requirements: Min 8 GB RAM; Requires Python environment setup and specific dependencies as outlined in the repository's documentation..
  • Tags unique to instruct-eval: benchmarking, evaluation, instruct-tuning, llm.
  • When you need to quantitatively evaluate the performance of instruction-tuned large language models such as Alpaca and Flan-T5 on held-out tasks.

When NOT to use instruct-eval

  • When primarily interested in general model evaluation without a focus on instruction-tuned LMs.
  • If your primary interest lies in qualitative assessment rather than quantitative metrics.
  • If you need support for non-HuggingFace Transformer models, as instruct-eval mainly supports models from the HuggingFace ecosystem.

Choose hallucination-index if…

  • Tags unique to hallucination-index: hallucinations, large language models, llm-evaluation, openai.
  • Use when you need to ensure accuracy in short-context tasks, as it tests models like Chain-of-Note prompting techniques specifically for such scenarios.
  • More recently updated (last pushed Jul 28, 2025).

When NOT to use hallucination-index

  • Avoid using Hallucination-Index when your application requires real-time evaluation of hallucinations, as it focuses on predefined tests rather than live model performance.
  • Do not rely solely on this index if your primary concern is the latest updates to LLM models; its data might not reflect recent improvements in models or the introduction of new ones.

Explore

Sources

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

GitHub stars on cards: instruct-eval 552 · hallucination-index 116 (synced Aug 7, 2026).

Common questions

What is the difference between instruct-eval and hallucination-index?
instruct-eval: Quantitative evaluation for instruction-tuned language models. hallucination-index: Initiative to evaluate and rank popular LLMs based on hallucination propensity. See the comparison table for live GitHub stats and shared categories.
When should I choose instruct-eval over hallucination-index?
Choose instruct-eval over hallucination-index when Requirements: Min 8 GB RAM; Requires Python environment setup and specific dependencies as outlined in the repository's documentation.; Tags unique to instruct-eval: benchmarking, evaluation, instruct-tuning, llm; When you need to quantitatively evaluate the performance of instruction-tuned large language models such as Alpaca and Flan-T5 on held-out tasks.
When should I choose hallucination-index over instruct-eval?
Choose hallucination-index over instruct-eval when Tags unique to hallucination-index: hallucinations, large language models, llm-evaluation, openai; Use when you need to ensure accuracy in short-context tasks, as it tests models like Chain-of-Note prompting techniques specifically for such scenarios; More recently updated (last pushed Jul 28, 2025).
When should I avoid instruct-eval?
When primarily interested in general model evaluation without a focus on instruction-tuned LMs. If your primary interest lies in qualitative assessment rather than quantitative metrics. If you need support for non-HuggingFace Transformer models, as instruct-eval mainly supports models from the HuggingFace ecosystem.
When should I avoid hallucination-index?
Avoid using Hallucination-Index when your application requires real-time evaluation of hallucinations, as it focuses on predefined tests rather than live model performance. Do not rely solely on this index if your primary concern is the latest updates to LLM models; its data might not reflect recent improvements in models or the introduction of new ones.
Is instruct-eval or hallucination-index more popular on GitHub?
instruct-eval has more GitHub stars (552 vs 116). Stars measure visibility, not whether either tool fits your constraints.
Are instruct-eval and hallucination-index open source?
Yes - both are open-source projects on GitHub.
Where can I find alternatives to instruct-eval or hallucination-index?
GraphCanon lists graph-backed alternatives at instruct-eval alternatives and hallucination-index alternatives (instruct-eval markdown twin, hallucination-index 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, instruct-eval or hallucination-index?
instruct-eval: Dormant. hallucination-index: 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 instruct-eval and hallucination-index?
GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: instruct-eval trust report; hallucination-index trust report.

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