--- title: "deepeval vs PHUDGE" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/confident-ai-deepeval-vs-deshwalmahesh-phudge" tools: ["confident-ai-deepeval", "deshwalmahesh-phudge"] --- # deepeval vs PHUDGE *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 PHUDGE if pHUDGE grades LLM responses using scalable configurations with custom rubrics and reference answers for both relative and absolute grading. [deepeval](https://deepeval.com) reports 18k GitHub stars, 2.0k forks, and 624 open issues, last pushed Sep 18, 2026. [PHUDGE](https://arxiv.org/abs/2405.08029) has 53 stars, 7 forks, and 1 open issues, last pushed Jul 10, 2024. Figures are from public GitHub metadata via [deepeval's repository](https://github.com/confident-ai/deepeval) and [PHUDGE's repository](https://github.com/deshwalmahesh/PHUDGE). | | [deepeval](/tools/confident-ai-deepeval.md) | [PHUDGE](/tools/deshwalmahesh-phudge.md) | | --- | --- | --- | | Tagline | LLM Evaluation Framework. | Evaluation toolkit for LLM responses with scalable grading and hallucination detection. | | Stars | 18,342 | 53 | | Forks | 1,953 | 7 | | Open issues | 624 | 1 | | Language | Python | Jupyter Notebook | | Adopt for | Deepeval is a Python-based framework designed for evaluating large language models with an array of metrics and evaluation methodologies. | PHUDGE grades LLM responses using scalable configurations with custom rubrics and reference answers for both relative and absolute grading. | | Persona | - | - | | Runtime | - | - | | License | Apache-2.0 License | No clear open-source license listed. Verify usage rights before incorporation into projects. | | Categories | Evaluation & Observability | Evaluation & Observability | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [deepeval](/tools/confident-ai-deepeval.md) | [PHUDGE](/tools/deshwalmahesh-phudge.md) | | --- | --- | --- | | Maintenance | Very active (96%) | Dormant (18%) | | Days since push | 1d | 791d | | Open issues (now) | 624 | 1 | | Stars delta | +1.1k (30d) | 0 (30d) | | Open issues delta | +220 (30d) | 0 (30d) | | Owner type | Organization | User | | Full report | [trust report](/tools/confident-ai-deepeval/trust.md) | [trust report](/tools/deshwalmahesh-phudge/trust.md) | ## Shared compatibility - **Python**: [deepeval](/tools/confident-ai-deepeval.md) - Python runtime; [PHUDGE](/tools/deshwalmahesh-phudge.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: PHUDGE - **Pricing:** freemium - Primary model is free; potential costs associated with training and running on specific hardware. - **Adopt for:** PHUDGE grades LLM responses using scalable configurations with custom rubrics and reference answers for both relative and absolute grading. - **License detail:** No clear open-source license listed. Verify usage rights before incorporation into projects. ## Choose when ### Choose deepeval if… - deepeval is primarily Python; PHUDGE is Jupyter Notebook. - Requirements: Requires Python environment and familiarity with large language models to effectively utilize Deepeval's capabilities.. - Tags unique to deepeval: evaluation, metrics. - When developing large language models and you need a comprehensive evaluation framework to measure their performance across various metrics. ### Choose PHUDGE if… - PHUDGE is primarily Jupyter Notebook; deepeval is Python. - Pricing: Primary model is free; potential costs associated with training and running on specific hardware.. - Tags unique to PHUDGE: absolute-grading, custom-rubric, hallucination-detection, phi-3. - Need robust evaluation of LLM responses on a scale from one to five ## 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 PHUDGE - Looking for real-time deployment without setup for different environments - Need support for models not compatible with Phi-3 architecture ## Common questions ### What is the difference between deepeval and PHUDGE? deepeval: LLM Evaluation Framework.. PHUDGE: Evaluation toolkit for LLM responses with scalable grading and hallucination detection.. See the comparison table for live GitHub stats and shared categories. ### When should I choose deepeval over PHUDGE? Choose deepeval over PHUDGE when deepeval is primarily Python; PHUDGE is Jupyter Notebook; Requirements: Requires Python environment and familiarity with large language models to effectively utilize Deepeval's capabilities.; Tags unique to deepeval: evaluation, metrics; When developing large language models and you need a comprehensive evaluation framework to measure their performance across various metrics. ### When should I choose PHUDGE over deepeval? Choose PHUDGE over deepeval when PHUDGE is primarily Jupyter Notebook; deepeval is Python; Pricing: Primary model is free; potential costs associated with training and running on specific hardware.; Tags unique to PHUDGE: absolute-grading, custom-rubric, hallucination-detection, phi-3; Need robust evaluation of LLM responses on a scale from one to five. ### 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 PHUDGE? Looking for real-time deployment without setup for different environments Need support for models not compatible with Phi-3 architecture ### Is deepeval or PHUDGE more popular on GitHub? deepeval has more GitHub stars (18,342 vs 53). Stars measure visibility, not whether either tool fits your constraints. ### Are deepeval and PHUDGE open source? Yes - both are open-source projects on GitHub. ### Where can I find alternatives to deepeval or PHUDGE? GraphCanon lists graph-backed alternatives at [deepeval alternatives](/tools/confident-ai-deepeval/alternatives) and [PHUDGE alternatives](/tools/deshwalmahesh-phudge/alternatives) ([deepeval markdown twin](/tools/confident-ai-deepeval/alternatives.md), [PHUDGE markdown twin](/tools/deshwalmahesh-phudge/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-deshwalmahesh-phudge.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, deepeval or PHUDGE? deepeval: Very active. PHUDGE: 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 PHUDGE? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [deepeval trust report](/tools/confident-ai-deepeval/trust); [PHUDGE trust report](/tools/deshwalmahesh-phudge/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/_