--- title: "ALERT vs bigcode-evaluation-harness" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/babelscape-alert-vs-bigcode-project-bigcode-evaluation-harness" tools: ["babelscape-alert", "bigcode-project-bigcode-evaluation-harness"] --- # ALERT vs bigcode-evaluation-harness *GraphCanon updated Sep 20, 2026* ## Verdict Pick ALERT if aLERT is designed specifically for red-teaming based safety evaluation on large language models, using MIT licensed prompts and adversarial augmentation; 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. [ALERT](https://arxiv.org/abs/2404.08676) reports 59 GitHub stars, 8 forks, and 0 open issues, last pushed Sep 20, 2024. [bigcode-evaluation-harness](https://github.com/bigcode-project/bigcode-evaluation-harness) has 1.1k stars, 259 forks, and 96 open issues, last pushed Jul 22, 2025. Figures are from public GitHub metadata via [ALERT's repository](https://github.com/Babelscape/ALERT) and [bigcode-evaluation-harness's repository](https://github.com/bigcode-project/bigcode-evaluation-harness). | | [ALERT](/tools/babelscape-alert.md) | [bigcode-evaluation-harness](/tools/bigcode-project-bigcode-evaluation-harness.md) | | --- | --- | --- | | Tagline | A Comprehensive Benchmark for Assessing Large Language Models' Safety Through Red Teaming | A framework for evaluating autoregressive code generation language models. | | Stars | 59 | 1,058 | | Forks | 8 | 259 | | Open issues | 0 | 96 | | Language | Python | Python | | Adopt for | ALERT is designed specifically for red-teaming based safety evaluation on large language models, using MIT licensed prompts and adversarial augmentation. | bigcode-evaluation-harness is tailored towards evaluating autoregressive code generation models via Python and Docker containers for secure and reproducible execution environments. | | Persona | - | - | | Runtime | - | - | | License | Other | bigcode-evaluation-harness is distributed under the Apache-2.0 license. | | Categories | Evaluation & Observability | Evaluation & Observability | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [ALERT](/tools/babelscape-alert.md) | [bigcode-evaluation-harness](/tools/bigcode-project-bigcode-evaluation-harness.md) | | --- | --- | --- | | Days since push | 719d | 409d | | Open issues (now) | 0 | 96 | | Stars delta | 0 (30d) | +3 (30d) | | Full report | [trust report](/tools/babelscape-alert/trust.md) | [trust report](/tools/bigcode-project-bigcode-evaluation-harness/trust.md) | ## Decision facts: ALERT - **Adopt for:** ALERT is designed specifically for red-teaming based safety evaluation on large language models, using MIT licensed prompts and adversarial augmentation. ## Decision facts: bigcode-evaluation-harness - **Requirements:** Users must have Docker installed to leverage the isolated execution environments for model output evaluation. - **Adopt for:** bigcode-evaluation-harness is tailored towards evaluating autoregressive code generation models via Python and Docker containers for secure and reproducible execution environments. - **License detail:** bigcode-evaluation-harness is distributed under the Apache-2.0 license. ## Choose when ### Choose ALERT if… - License: ALERT is Other, bigcode-evaluation-harness is Apache-2.0. - Tags unique to ALERT: ai, artificial-intelligence, benchmark, bias-detection. - When evaluating safety metrics of large language models through red-teaming approaches ### Choose bigcode-evaluation-harness if… - License: bigcode-evaluation-harness is Apache-2.0, ALERT is Other. - 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 ALERT - If your evaluation does not require bias detection or safety assessment under adversarial conditions - In scenarios where a broader range of model aspects beyond safety is needed, as ALERT focuses primarily on safety benchmarks ## 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. ## Common questions ### What is the difference between ALERT and bigcode-evaluation-harness? ALERT: A Comprehensive Benchmark for Assessing Large Language Models' Safety Through Red Teaming. bigcode-evaluation-harness: A framework for evaluating autoregressive code generation language models.. See the comparison table for live GitHub stats and shared categories. ### When should I choose ALERT over bigcode-evaluation-harness? Choose ALERT over bigcode-evaluation-harness when License: ALERT is Other, bigcode-evaluation-harness is Apache-2.0; Tags unique to ALERT: ai, artificial-intelligence, benchmark, bias-detection; When evaluating safety metrics of large language models through red-teaming approaches. ### When should I choose bigcode-evaluation-harness over ALERT? Choose bigcode-evaluation-harness over ALERT when License: bigcode-evaluation-harness is Apache-2.0, ALERT is Other; 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 avoid ALERT? If your evaluation does not require bias detection or safety assessment under adversarial conditions In scenarios where a broader range of model aspects beyond safety is needed, as ALERT focuses primarily on safety benchmarks ### 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. ### Is ALERT or bigcode-evaluation-harness more popular on GitHub? bigcode-evaluation-harness has more GitHub stars (1,058 vs 59). Stars measure visibility, not whether either tool fits your constraints. ### Are ALERT and bigcode-evaluation-harness open source? Yes - both are open-source projects on GitHub (ALERT: Other, bigcode-evaluation-harness: Apache-2.0). ### Where can I find alternatives to ALERT or bigcode-evaluation-harness? GraphCanon lists graph-backed alternatives at [ALERT alternatives](/tools/babelscape-alert/alternatives) and [bigcode-evaluation-harness alternatives](/tools/bigcode-project-bigcode-evaluation-harness/alternatives) ([ALERT markdown twin](/tools/babelscape-alert/alternatives.md), [bigcode-evaluation-harness markdown twin](/tools/bigcode-project-bigcode-evaluation-harness/alternatives.md)), 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](/compare/babelscape-alert-vs-bigcode-project-bigcode-evaluation-harness.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, ALERT or bigcode-evaluation-harness? ALERT: Dormant. bigcode-evaluation-harness: 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 ALERT and bigcode-evaluation-harness? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [ALERT trust report](/tools/babelscape-alert/trust); [bigcode-evaluation-harness trust report](/tools/bigcode-project-bigcode-evaluation-harness/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=babelscape-alert`](/api/graphcanon/graph?tool=babelscape-alert) - LLM index: [/llms.txt](/llms.txt) - Full corpus: [/llms-full.txt](/llms-full.txt) _GraphCanon - The knowledge graph for AI development. https://www.graphcanon.com/_