--- title: "PHUDGE vs Made-With-ML" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/deshwalmahesh-phudge-vs-gokumohandas-made-with-ml" tools: ["deshwalmahesh-phudge", "gokumohandas-made-with-ml"] --- # PHUDGE vs Made-With-ML *GraphCanon updated Jul 15, 2026* ## Verdict Pick PHUDGE when tags unique to PHUDGE: ai, custom-dataset, evaluation, feedback-collection; pick Made-With-ML when tags unique to Made-With-ML: data-engineering, data-quality, data-science, deep-learning. [PHUDGE](https://arxiv.org/abs/2405.08029) reports 53 GitHub stars, 7 forks, and 1 open issues, last pushed Jul 10, 2024. [Made-With-ML](https://madewithml.com) has 49k stars, 7.7k forks, and 27 open issues, last pushed Mar 4, 2026. Figures are from public GitHub metadata via [PHUDGE's repository](https://github.com/deshwalmahesh/PHUDGE) and [Made-With-ML's repository](https://github.com/GokuMohandas/Made-With-ML). | | [PHUDGE](/tools/deshwalmahesh-phudge.md) | [Made-With-ML](/tools/gokumohandas-made-with-ml.md) | | --- | --- | --- | | Tagline | Official repo for the paper PHUDGE: Phi-3 as Scalable Judge. Evaluate your LLMs with or without custom rubric, reference answer, absolute, relative and much more. It contains a list of all the availab | Learn how to develop, deploy and iterate on production-grade ML applications. | | Stars | 53 | 48,703 | | Forks | 7 | 7,661 | | Open issues | 1 | 27 | | Language | Jupyter Notebook | Jupyter Notebook | | Adopt for | - | - | | Persona | - | - | | Runtime | - | - | | License | - | MIT | | Categories | Inference & Serving, LLM Frameworks, Model Training | AI Agents, LLM Frameworks, Model Training | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [PHUDGE](/tools/deshwalmahesh-phudge.md) | [Made-With-ML](/tools/gokumohandas-made-with-ml.md) | | --- | --- | --- | | Maintenance | Dormant (18%) | Slowing (36%) | | Days since push | 734d | 132d | | Open issues (now) | 1 | 27 | | Full report | [trust report](/tools/deshwalmahesh-phudge/trust.md) | [trust report](/tools/gokumohandas-made-with-ml/trust.md) | ## Shared compatibility - **Python**: [PHUDGE](/tools/deshwalmahesh-phudge.md) - Python runtime; [Made-With-ML](/tools/gokumohandas-made-with-ml.md) - Python runtime ## Choose when ### Choose PHUDGE if… - Tags unique to PHUDGE: ai, custom-dataset, evaluation, feedback-collection. - Also covers Inference & Serving. - Leaner open-issue backlog (1). ### Choose Made-With-ML if… - Tags unique to Made-With-ML: data-engineering, data-quality, data-science, deep-learning. - Also covers AI Agents. - More GitHub stars (49k vs 53) - visibility, not fit. ## When NOT to use PHUDGE - Last GitHub push was 734 days ago (dormant maintenance, Jul 10, 2024). Validate activity before betting a new project on PHUDGE. - Inference & Serving: Self-hosting rarely beats a hosted API on cost until you have steady, high-volume traffic. - LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves. - Model Training: Try prompting and RAG first; fine-tuning is the answer to style/format, not missing knowledge. ## When NOT to use Made-With-ML - Last GitHub push was 132 days ago (slowing maintenance, Mar 4, 2026). Validate activity before betting a new project on Made-With-ML. - AI Agents: Don't use an agent loop when a deterministic workflow would do; agents add latency, cost, and non-determinism. - LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves. - Model Training: Try prompting and RAG first; fine-tuning is the answer to style/format, not missing knowledge. ## Common questions ### What is the difference between PHUDGE and Made-With-ML? PHUDGE: Official repo for the paper PHUDGE: Phi-3 as Scalable Judge. Evaluate your LLMs with or without custom rubric, reference answer, absolute, relative and much more. It contains a list of all the availab. Made-With-ML: Learn how to develop, deploy and iterate on production-grade ML applications.. See the comparison table for live GitHub stats and shared categories. ### When should I choose PHUDGE over Made-With-ML? Choose PHUDGE over Made-With-ML when Tags unique to PHUDGE: ai, custom-dataset, evaluation, feedback-collection; Also covers Inference & Serving; Leaner open-issue backlog (1). ### When should I choose Made-With-ML over PHUDGE? Choose Made-With-ML over PHUDGE when Tags unique to Made-With-ML: data-engineering, data-quality, data-science, deep-learning; Also covers AI Agents; More GitHub stars (49k vs 53) - visibility, not fit. ### When should I avoid PHUDGE? Last GitHub push was 734 days ago (dormant maintenance, Jul 10, 2024). Validate activity before betting a new project on PHUDGE. Inference & Serving: Self-hosting rarely beats a hosted API on cost until you have steady, high-volume traffic. LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves. Model Training: Try prompting and RAG first; fine-tuning is the answer to style/format, not missing knowledge. ### When should I avoid Made-With-ML? Last GitHub push was 132 days ago (slowing maintenance, Mar 4, 2026). Validate activity before betting a new project on Made-With-ML. AI Agents: Don't use an agent loop when a deterministic workflow would do; agents add latency, cost, and non-determinism. LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves. Model Training: Try prompting and RAG first; fine-tuning is the answer to style/format, not missing knowledge. ### Is PHUDGE or Made-With-ML more popular on GitHub? Made-With-ML has more GitHub stars (48,703 vs 53). Stars measure visibility, not whether either tool fits your constraints. ### Are PHUDGE and Made-With-ML open source? Yes - both are open-source projects on GitHub. ### Where can I find alternatives to PHUDGE or Made-With-ML? GraphCanon lists graph-backed alternatives at [PHUDGE alternatives](/tools/deshwalmahesh-phudge/alternatives) and [Made-With-ML alternatives](/tools/gokumohandas-made-with-ml/alternatives) ([PHUDGE markdown twin](/tools/deshwalmahesh-phudge/alternatives.md), [Made-With-ML markdown twin](/tools/gokumohandas-made-with-ml/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/deshwalmahesh-phudge-vs-gokumohandas-made-with-ml.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, PHUDGE or Made-With-ML? PHUDGE: Dormant. Made-With-ML: Slowing. 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 PHUDGE and Made-With-ML? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [PHUDGE trust report](/tools/deshwalmahesh-phudge/trust); [Made-With-ML trust report](/tools/gokumohandas-made-with-ml/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=deshwalmahesh-phudge`](/api/graphcanon/graph?tool=deshwalmahesh-phudge) - 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/_