--- title: "deepeval vs just-eval" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/confident-ai-deepeval-vs-re-align-just-eval" tools: ["confident-ai-deepeval", "re-align-just-eval"] --- # deepeval vs just-eval *GraphCanon updated Sep 20, 2026* ## Verdict Pick deepeval if deepeval is a Python-based framework designed for evaluating large language models with an array of metrics and evaluation methodologies; pick just-eval if just-eval provides a straightforward GPT-based framework for evaluating LLMs across multiple dimensions with clear outputs. [deepeval](https://deepeval.com) reports 18k GitHub stars, 2.0k forks, and 624 open issues, last pushed Sep 18, 2026. [just-eval](https://allenai.github.io/re-align/) has 90 stars, 7 forks, and 2 open issues, last pushed Jan 29, 2024. Figures are from public GitHub metadata via [deepeval's repository](https://github.com/confident-ai/deepeval) and [just-eval's repository](https://github.com/Re-Align/just-eval). | | [deepeval](/tools/confident-ai-deepeval.md) | [just-eval](/tools/re-align-just-eval.md) | | --- | --- | --- | | Tagline | LLM Evaluation Framework. | A simple GPT-based evaluation tool for multi-aspect, interpretable assessment of LLMs. | | Stars | 18,342 | 90 | | Forks | 1,953 | 7 | | Open issues | 624 | 2 | | Language | Python | Python | | Adopt for | Deepeval is a Python-based framework designed for evaluating large language models with an array of metrics and evaluation methodologies. | just-eval provides a straightforward GPT-based framework for evaluating LLMs across multiple dimensions with clear outputs. | | Persona | - | - | | Runtime | - | - | | License | Apache-2.0 License | MIT | | Categories | Evaluation & Observability | Evaluation & Observability | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [deepeval](/tools/confident-ai-deepeval.md) | [just-eval](/tools/re-align-just-eval.md) | | --- | --- | --- | | Maintenance | Very active (96%) | Dormant (18%) | | Days since push | 1d | 953d | | Open issues (now) | 624 | 2 | | Stars delta | +1.1k (30d) | 0 (30d) | | Open issues delta | +220 (30d) | 0 (30d) | | Full report | [trust report](/tools/confident-ai-deepeval/trust.md) | [trust report](/tools/re-align-just-eval/trust.md) | ## Shared compatibility - **Python**: [deepeval](/tools/confident-ai-deepeval.md) - Python runtime; [just-eval](/tools/re-align-just-eval.md) - Python runtime ## Decision facts: deepeval - **Requirements:** Requires Python environment and familiarity with large language models to effectively utilize Deepeval's capabilities. - **Adopt for:** Deepeval is a Python-based framework designed for evaluating large language models with an array of metrics and evaluation methodologies. - **License detail:** Apache-2.0 License ## Decision facts: just-eval - **Adopt for:** just-eval provides a straightforward GPT-based framework for evaluating LLMs across multiple dimensions with clear outputs. ## Choose when ### Choose deepeval if… - License: deepeval is Apache-2.0, just-eval is MIT. - Requirements: Requires Python environment and familiarity with large language models to effectively utilize Deepeval's capabilities.. - Tags unique to deepeval: metrics. - When developing large language models and you need a comprehensive evaluation framework to measure their performance across various metrics. ### Choose just-eval if… - License: just-eval is MIT, deepeval is Apache-2.0. - Tags unique to just-eval: gpt4, llm, llm-eval, llm-evaluation-toolkit. - When your team requires an in-depth yet interpretable evaluation of LLM performance, focusing on various aspects. ## When NOT to use deepeval - For small-scale applications that do not require the depth of metrics and evaluations offered by Deepeval, as it might be overkill. - In situations where there is a need for real-time performance monitoring, since Deepeval focuses more on post-development evaluation rather than continuous runtime analysis. ## When NOT to use just-eval - Avoid if direct integration with competing API services is needed as just-eval focuses solely on OpenAI API key configuration. - Not suitable when your project demands a custom evaluation framework that extends beyond simple GPT-based assessments. ## Common questions ### What is the difference between deepeval and just-eval? deepeval: LLM Evaluation Framework.. just-eval: A simple GPT-based evaluation tool for multi-aspect, interpretable assessment of LLMs.. See the comparison table for live GitHub stats and shared categories. ### When should I choose deepeval over just-eval? Choose deepeval over just-eval when License: deepeval is Apache-2.0, just-eval is MIT; Requirements: Requires Python environment and familiarity with large language models to effectively utilize Deepeval's capabilities.; Tags unique to deepeval: metrics; When developing large language models and you need a comprehensive evaluation framework to measure their performance across various metrics. ### When should I choose just-eval over deepeval? Choose just-eval over deepeval when License: just-eval is MIT, deepeval is Apache-2.0; Tags unique to just-eval: gpt4, llm, llm-eval, llm-evaluation-toolkit; When your team requires an in-depth yet interpretable evaluation of LLM performance, focusing on various aspects. ### When should I avoid deepeval? For small-scale applications that do not require the depth of metrics and evaluations offered by Deepeval, as it might be overkill. In situations where there is a need for real-time performance monitoring, since Deepeval focuses more on post-development evaluation rather than continuous runtime analysis. ### When should I avoid just-eval? Avoid if direct integration with competing API services is needed as just-eval focuses solely on OpenAI API key configuration. Not suitable when your project demands a custom evaluation framework that extends beyond simple GPT-based assessments. ### Is deepeval or just-eval more popular on GitHub? deepeval has more GitHub stars (18,342 vs 90). Stars measure visibility, not whether either tool fits your constraints. ### Are deepeval and just-eval open source? Yes - both are open-source projects on GitHub (deepeval: Apache-2.0, just-eval: MIT). ### Where can I find alternatives to deepeval or just-eval? GraphCanon lists graph-backed alternatives at [deepeval alternatives](/tools/confident-ai-deepeval/alternatives) and [just-eval alternatives](/tools/re-align-just-eval/alternatives) ([deepeval markdown twin](/tools/confident-ai-deepeval/alternatives.md), [just-eval markdown twin](/tools/re-align-just-eval/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/confident-ai-deepeval-vs-re-align-just-eval.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, deepeval or just-eval? deepeval: Very active. just-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 deepeval and just-eval? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [deepeval trust report](/tools/confident-ai-deepeval/trust); [just-eval trust report](/tools/re-align-just-eval/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=confident-ai-deepeval`](/api/graphcanon/graph?tool=confident-ai-deepeval) - 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/_