Comparison
olmo-eval vs instruct-eval
Verdict
Pick olmo-eval if olmo-eval is an evaluation framework for large language models, using uv for reproducible builds. It focuses on modular task implementations and integrates with various datasets via defined tasks; pick instruct-eval if key facts about instruct-eval.
Markdown twin · olmo-eval alternatives · instruct-eval alternatives
GraphCanon updated 2w
vs
Trust & integrity
| Signal | olmo-eval | instruct-eval |
|---|---|---|
| Maintenance | Very active (0d since push) As of 2w · github_public_v1 | Dormant (879d since push) As of 2w · github_public_v1 |
| Provenance | Not a fork · Organization account As of 2w · github_public_v1 | Not a fork · Organization 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
- olmo-eval
- Olmo Evaluation Framework for LLM Tasks
- instruct-eval
- Quantitative evaluation for instruction-tuned language models
Stars
- olmo-eval
- 65
- instruct-eval
- 552
Forks
- olmo-eval
- 14
- instruct-eval
- 45
Open issues
- olmo-eval
- 38
- instruct-eval
- 24
Language
- olmo-eval
- Python
- instruct-eval
- Python
Adopt for
- olmo-eval
- Olmo-eval is an evaluation framework for large language models, using uv for reproducible builds. It focuses on modular task implementations and integrates with various datasets via defined tasks.
- instruct-eval
- Key facts about instruct-eval
Persona
- olmo-eval
- -
- instruct-eval
- -
Runtime
- olmo-eval
- -
- instruct-eval
- -
License
- olmo-eval
- Apache-2.0
- instruct-eval
- The tool is distributed under Apache-2.0 license
Last pushed
- olmo-eval
- Aug 6, 2026
- instruct-eval
- Mar 10, 2024
Categories
- olmo-eval
- Evaluation & Observability
- instruct-eval
- Evaluation & Observability
Trust and health
Maintenance
- olmo-eval
- Very active (96%)
- instruct-eval
- Dormant (18%)
Days since push
- olmo-eval
- 0d
- instruct-eval
- 879d
Open issues (now)
- olmo-eval
- 38
- instruct-eval
- 24
OSV dependency advisories
- olmo-eval
- No lockfile (source not queried)
- instruct-eval
- Published findings
Full report
- olmo-eval
- Trust report
- instruct-eval
- Trust report
Choose olmo-eval if…
- Tags unique to olmo-eval: datasets, python, tasks, uv.
- olmo-eval ships Docker support for self-hosted deployment.
- When you need a flexible evaluation setup that works with a variety of LLMs and datasets.
When NOT to use olmo-eval
- When you require a simpler setup that doesn't need the reproducibility constraints of uv builds.
- If your project already has an established evaluation toolchain and does not benefit from introducing a new framework for manageability reasons.
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, instruct-tuning, safety.
- 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.
Explore
Sources
Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.
- GitHub stars (allenai/olmo-eval) · observed Aug 7, 2026
- GitHub forks (allenai/olmo-eval) · observed Aug 7, 2026
- Last push (allenai/olmo-eval) · observed Aug 6, 2026
- 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 (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 on cards: olmo-eval 65 · instruct-eval 552 (synced Aug 7, 2026).
Common questions
- What is the difference between olmo-eval and instruct-eval?
- olmo-eval: Olmo Evaluation Framework for LLM Tasks. instruct-eval: Quantitative evaluation for instruction-tuned language models. See the comparison table for live GitHub stats and shared categories.
- When should I choose olmo-eval over instruct-eval?
- Choose olmo-eval over instruct-eval when Tags unique to olmo-eval: datasets, python, tasks, uv; olmo-eval ships Docker support for self-hosted deployment; When you need a flexible evaluation setup that works with a variety of LLMs and datasets.
- When should I choose instruct-eval over olmo-eval?
- Choose instruct-eval over olmo-eval 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, instruct-tuning, safety; 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 avoid olmo-eval?
- When you require a simpler setup that doesn't need the reproducibility constraints of uv builds. If your project already has an established evaluation toolchain and does not benefit from introducing a new framework for manageability reasons.
- 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.
- Is olmo-eval or instruct-eval more popular on GitHub?
- instruct-eval has more GitHub stars (552 vs 65). Stars measure visibility, not whether either tool fits your constraints.
- Are olmo-eval and instruct-eval open source?
- Yes - both are open-source projects on GitHub (olmo-eval: Apache-2.0, instruct-eval: Apache-2.0).
- Where can I find alternatives to olmo-eval or instruct-eval?
- GraphCanon lists graph-backed alternatives at olmo-eval alternatives and instruct-eval alternatives (olmo-eval markdown twin, instruct-eval 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, olmo-eval or instruct-eval?
- olmo-eval: Very active. instruct-eval: 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 olmo-eval and instruct-eval?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: olmo-eval trust report; instruct-eval trust report.