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
Trust & integrity
| Signal | instruct-eval | hallucination-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 (declare-lab/instruct-eval) · observed Aug 7, 2026
- GitHub forks (declare-lab/instruct-eval) · observed Aug 7, 2026
- Last push (declare-lab/instruct-eval) · observed Mar 10, 2024
- License file (Apache-2.0) · observed Aug 7, 2026
- Decision facts (enrichment) · observed Jul 12, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
- GitHub stars (rungalileo/hallucination-index) · observed Jul 29, 2026
- GitHub forks (rungalileo/hallucination-index) · observed Jul 29, 2026
- Last push (rungalileo/hallucination-index) · observed Jul 28, 2025
- License file (unknown) · observed Jul 29, 2026
- Decision facts (enrichment) · observed Jul 17, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
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.