Comparison
bigcode-evaluation-harness vs every_eval_ever
Verdict
Pick bigcode-evaluation-harness if bigcode-evaluation-harness is tailored towards evaluating autoregressive code generation models via Python and Docker containers for secure and reproducible execution environments; pick every_eval_ever if every Eval Ever is dedicated to providing a standardized metadata framework and a crowdsourced evaluation database for AI results.
Markdown twin · bigcode-evaluation-harness alternatives · every_eval_ever alternatives
GraphCanon updated Sep 20, 2026
vs
Trust & integrity
| Signal | bigcode-evaluation-harness | every_eval_ever |
|---|---|---|
| Maintenance | Dormant (409d since push) As of Sep 5, 2026 · github_public_v1 | Very active (1d since push) As of Sep 9, 2026 · github_public_v1 |
| Provenance | Not a fork · Organization account As of Sep 5, 2026 · github_public_v1 | Not a fork · Organization account As of Sep 9, 2026 · github_public_v1 |
| OSV dependency advisories | Published findings As of Jul 11, 2026 · osv@v1 | No lockfile (source not queried) As of Jul 15, 2026 · 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
- bigcode-evaluation-harness
- A framework for evaluating autoregressive code generation language models.
- every_eval_ever
- Shared schema and crowdsourced eval database
Stars
- bigcode-evaluation-harness
- 1.1k
- every_eval_ever
- 111
Forks
- bigcode-evaluation-harness
- 259
- every_eval_ever
- 49
Open issues
- bigcode-evaluation-harness
- 96
- every_eval_ever
- 27
Language
- bigcode-evaluation-harness
- Python
- every_eval_ever
- Python
Adopt for
- bigcode-evaluation-harness
- bigcode-evaluation-harness is tailored towards evaluating autoregressive code generation models via Python and Docker containers for secure and reproducible execution environments.
- every_eval_ever
- Every Eval Ever is dedicated to providing a standardized metadata framework and a crowdsourced evaluation database for AI results.
Persona
- bigcode-evaluation-harness
- -
- every_eval_ever
- -
Runtime
- bigcode-evaluation-harness
- -
- every_eval_ever
- -
License
- bigcode-evaluation-harness
- bigcode-evaluation-harness is distributed under the Apache-2.0 license.
- every_eval_ever
- MIT
Last pushed
- bigcode-evaluation-harness
- Jul 22, 2025
- every_eval_ever
- Sep 7, 2026
Categories
- bigcode-evaluation-harness
- Evaluation & Observability
- every_eval_ever
- Evaluation & Observability
Trust and health
Maintenance
- bigcode-evaluation-harness
- Dormant (18%)
- every_eval_ever
- Very active (96%)
Days since push
- bigcode-evaluation-harness
- 409d
- every_eval_ever
- 1d
Open issues (now)
- bigcode-evaluation-harness
- 96
- every_eval_ever
- 27
Stars delta
- bigcode-evaluation-harness
- +3 (30d)
- every_eval_ever
- +9 (30d)
Open issues delta
- bigcode-evaluation-harness
- 0 (30d)
- every_eval_ever
- +3 (30d)
OSV dependency advisories
- bigcode-evaluation-harness
- Published findings
- every_eval_ever
- No lockfile (source not queried)
Full report
- bigcode-evaluation-harness
- Trust report
- every_eval_ever
- Trust report
Choose bigcode-evaluation-harness if…
- License: bigcode-evaluation-harness is Apache-2.0, every_eval_ever is MIT.
- Requirements: Users must have Docker installed to leverage the isolated execution environments for model output evaluation..
- Tags unique to bigcode-evaluation-harness: autoregressive-models, code-generation, docker, python.
- bigcode-evaluation-harness ships Docker support for self-hosted deployment.
- When you need to isolate the evaluation environment from your local development setup, ensuring that no external variables affect the outcomes of model performance assessments.
When NOT to use bigcode-evaluation-harness
- When you require real-time evaluation without the overhead of generating outputs locally and then evaluating them within isolated environments via Docker.
- If your model's evaluation process does not necessitate autoregressive setup or the security features provided by Docker, using bigcode-evaluation-harness might introduce unnecessary complexity.
Choose every_eval_ever if…
- License: every_eval_ever is MIT, bigcode-evaluation-harness is Apache-2.0.
- Pricing: Every Eval Ever is open-source under the MIT license, allowing free use and modification. No direct costs are associated with using the schema or contributing to the database..
- Requirements: Min 2 GB RAM; To utilize all features, you need to install specific converter dependencies via pip..
- Tags unique to every_eval_ever: agent-evaluation, ai-evaluation, evaluations, infra.
- Use Every Eval Ever if you need to compare evaluation results from different frameworks in a consistent manner, ensuring results can be easily reproduced or reused as they conform to a defined schema.
When NOT to use every_eval_ever
- Avoid Every Eval Ever if you require real-time updates on evaluation results, as the database relies on contributions from a community to maintain and update its dataset.
- If your project needs to integrate evaluation outcomes without an explicit need for extensive metadata validation or standardization, this tool might be less suitable.
Explore
Sources
Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.
- GitHub stars (bigcode-project/bigcode-evaluation-harness) · observed Sep 20, 2026
- GitHub forks (bigcode-project/bigcode-evaluation-harness) · observed Sep 20, 2026
- Last push (bigcode-project/bigcode-evaluation-harness) · observed Jul 22, 2025
- License file (Apache-2.0) · observed Sep 20, 2026
- Decision facts (enrichment) · observed Jul 17, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
- GitHub stars (evaleval/every_eval_ever) · observed Sep 20, 2026
- GitHub forks (evaleval/every_eval_ever) · observed Sep 20, 2026
- Last push (evaleval/every_eval_ever) · observed Sep 7, 2026
- License file (MIT) · observed Sep 20, 2026
- Decision facts (enrichment) · observed Jul 16, 2026
- Trust scan (lockfile / OSV) · observed Jul 15, 2026
GitHub stars on cards: bigcode-evaluation-harness 1.1k · every_eval_ever 111 (synced Sep 20, 2026).
Common questions
- What is the difference between bigcode-evaluation-harness and every_eval_ever?
- bigcode-evaluation-harness: A framework for evaluating autoregressive code generation language models.. every_eval_ever: Shared schema and crowdsourced eval database. See the comparison table for live GitHub stats and shared categories.
- When should I choose bigcode-evaluation-harness over every_eval_ever?
- Choose bigcode-evaluation-harness over every_eval_ever when License: bigcode-evaluation-harness is Apache-2.0, every_eval_ever is MIT; Requirements: Users must have Docker installed to leverage the isolated execution environments for model output evaluation.; Tags unique to bigcode-evaluation-harness: autoregressive-models, code-generation, docker, python; bigcode-evaluation-harness ships Docker support for self-hosted deployment; When you need to isolate the evaluation environment from your local development setup, ensuring that no external variables affect the outcomes of model performance assessments.
- When should I choose every_eval_ever over bigcode-evaluation-harness?
- Choose every_eval_ever over bigcode-evaluation-harness when License: every_eval_ever is MIT, bigcode-evaluation-harness is Apache-2.0; Pricing: Every Eval Ever is open-source under the MIT license, allowing free use and modification. No direct costs are associated with using the schema or contributing to the database.; Requirements: Min 2 GB RAM; To utilize all features, you need to install specific converter dependencies via pip.; Tags unique to every_eval_ever: agent-evaluation, ai-evaluation, evaluations, infra; Use Every Eval Ever if you need to compare evaluation results from different frameworks in a consistent manner, ensuring results can be easily reproduced or reused as they conform to a defined schema.
- When should I avoid bigcode-evaluation-harness?
- When you require real-time evaluation without the overhead of generating outputs locally and then evaluating them within isolated environments via Docker. If your model's evaluation process does not necessitate autoregressive setup or the security features provided by Docker, using bigcode-evaluation-harness might introduce unnecessary complexity.
- When should I avoid every_eval_ever?
- Avoid Every Eval Ever if you require real-time updates on evaluation results, as the database relies on contributions from a community to maintain and update its dataset. If your project needs to integrate evaluation outcomes without an explicit need for extensive metadata validation or standardization, this tool might be less suitable.
- Is bigcode-evaluation-harness or every_eval_ever more popular on GitHub?
- bigcode-evaluation-harness has more GitHub stars (1,058 vs 111). Stars measure visibility, not whether either tool fits your constraints.
- Are bigcode-evaluation-harness and every_eval_ever open source?
- Yes - both are open-source projects on GitHub (bigcode-evaluation-harness: Apache-2.0, every_eval_ever: MIT).
- Where can I find alternatives to bigcode-evaluation-harness or every_eval_ever?
- GraphCanon lists graph-backed alternatives at bigcode-evaluation-harness alternatives and every_eval_ever alternatives (bigcode-evaluation-harness markdown twin, every_eval_ever 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, bigcode-evaluation-harness or every_eval_ever?
- bigcode-evaluation-harness: Dormant. every_eval_ever: Very active. 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 bigcode-evaluation-harness and every_eval_ever?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: bigcode-evaluation-harness trust report; every_eval_ever trust report.