--- title: "Kiln vs starwhale" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/kiln-ai-kiln-vs-star-whale-starwhale" tools: ["kiln-ai-kiln", "star-whale-starwhale"] --- # Kiln vs starwhale *GraphCanon updated Sep 29, 2026* ## Verdict Pick Kiln if kiln is a versatile AI systems development toolkit that excels in comprehensive evaluation frameworks for agents, RAG components, and fine-tuning processes; pick starwhale if starwhale is an MLOps/LLMOps platform that focuses on model management for AI and large language models through various runtime setups. [Kiln](https://kiln.tech) reports 5.1k GitHub stars, 380 forks, and 72 open issues, last pushed Sep 19, 2026. [starwhale](https://starwhale.ai) has 236 stars, 37 forks, and 120 open issues, last pushed Dec 20, 2024. Figures are from public GitHub metadata via [Kiln's repository](https://github.com/Kiln-AI/Kiln) and [starwhale's repository](https://github.com/star-whale/starwhale). | | [Kiln](/tools/kiln-ai-kiln.md) | [starwhale](/tools/star-whale-starwhale.md) | | --- | --- | --- | | Tagline | Build, Evaluate, and Optimize AI Systems | an MLOps/LLMOps platform | | Stars | 5,076 | 236 | | Forks | 380 | 37 | | Open issues | 72 | 120 | | Language | Python | Java | | Adopt for | Kiln is a versatile AI systems development toolkit that excels in comprehensive evaluation frameworks for agents, RAG components, and fine-tuning processes. | Starwhale is an MLOps/LLMOps platform that focuses on model management for AI and large language models through various runtime setups. | | Persona | - | - | | Runtime | - | - | | License | Other | Starwhale uses the Apache License 2.0, which is permissive and allows for usage in both open source and commercial applications with attribution. | | Categories | AI Agents, Data & Retrieval, Evaluation & Observability, Model Training | Data & Retrieval, Evaluation & Observability, Inference & Serving, LLM Frameworks, Model Training | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [Kiln](/tools/kiln-ai-kiln.md) | [starwhale](/tools/star-whale-starwhale.md) | | --- | --- | --- | | Maintenance | Very active (96%) | Dormant (18%) | | Days since push | 0d | 648d | | Open issues (now) | 72 | 120 | | Stars delta | +105 (30d) | -1 (30d) | | Open issues delta | +6 (30d) | 0 (30d) | | Full report | [trust report](/tools/kiln-ai-kiln/trust.md) | [trust report](/tools/star-whale-starwhale/trust.md) | ## Decision facts: Kiln - **Adopt for:** Kiln is a versatile AI systems development toolkit that excels in comprehensive evaluation frameworks for agents, RAG components, and fine-tuning processes. ## Decision facts: starwhale - **Requirements:** Requires Docker; Supports runtime builds through Docker images for compatibility across various system environments. - **Adopt for:** Starwhale is an MLOps/LLMOps platform that focuses on model management for AI and large language models through various runtime setups. - **License detail:** Starwhale uses the Apache License 2.0, which is permissive and allows for usage in both open source and commercial applications with attribution. ## Choose when ### Choose Kiln if… - Kiln is primarily Python; starwhale is Java. - License: Kiln is Other, starwhale is Apache-2.0. - Tags unique to Kiln: chain-of-thought, collaboration, dataset-generation, evals. - Also covers AI Agents. - When you need extensive tools for evaluating custom AI agents ### Choose starwhale if… - starwhale is primarily Java; Kiln is Python. - License: starwhale is Apache-2.0, Kiln is Other. - Requirements: Requires Docker; Supports runtime builds through Docker images for compatibility across various system environments.. - Tags unique to starwhale: cloud-native, dataset, datastore, infra. - Also covers Inference & Serving, LLM Frameworks. - When the need arises to manage models across different runtimes, including local environment configurations via runtime.yaml or conda environments, Docker images, or shell commands. ## When NOT to use Kiln - If your project strictly requires a lightweight tool without comprehensive dataset management options - Avoid if you do not require advanced synthetic data generation capabilities ## When NOT to use starwhale - In scenarios where an exclusive user preference leans towards Python-based operations over Java and the tool's CLI interactions do not meet operational demands. - For teams that require real-time model serving and have strict latency requirements, as Starwhale may not optimize for such use cases beyond its MLOps capabilities. ## Common questions ### What is the difference between Kiln and starwhale? Kiln: Build, Evaluate, and Optimize AI Systems. starwhale: an MLOps/LLMOps platform. See the comparison table for live GitHub stats and shared categories. ### When should I choose Kiln over starwhale? Choose Kiln over starwhale when Kiln is primarily Python; starwhale is Java; License: Kiln is Other, starwhale is Apache-2.0; Tags unique to Kiln: chain-of-thought, collaboration, dataset-generation, evals; Also covers AI Agents; When you need extensive tools for evaluating custom AI agents. ### When should I choose starwhale over Kiln? Choose starwhale over Kiln when starwhale is primarily Java; Kiln is Python; License: starwhale is Apache-2.0, Kiln is Other; Requirements: Requires Docker; Supports runtime builds through Docker images for compatibility across various system environments.; Tags unique to starwhale: cloud-native, dataset, datastore, infra; Also covers Inference & Serving, LLM Frameworks; When the need arises to manage models across different runtimes, including local environment configurations via runtime.yaml or conda environments, Docker images, or shell commands. ### When should I avoid Kiln? If your project strictly requires a lightweight tool without comprehensive dataset management options Avoid if you do not require advanced synthetic data generation capabilities ### When should I avoid starwhale? In scenarios where an exclusive user preference leans towards Python-based operations over Java and the tool's CLI interactions do not meet operational demands. For teams that require real-time model serving and have strict latency requirements, as Starwhale may not optimize for such use cases beyond its MLOps capabilities. ### Is Kiln or starwhale more popular on GitHub? Kiln has more GitHub stars (5,076 vs 236). Stars measure visibility, not whether either tool fits your constraints. ### Are Kiln and starwhale open source? Yes - both are open-source projects on GitHub (Kiln: Other, starwhale: Apache-2.0). ### Where can I find alternatives to Kiln or starwhale? GraphCanon lists graph-backed alternatives at [Kiln alternatives](/tools/kiln-ai-kiln/alternatives) and [starwhale alternatives](/tools/star-whale-starwhale/alternatives) ([Kiln markdown twin](/tools/kiln-ai-kiln/alternatives.md), [starwhale markdown twin](/tools/star-whale-starwhale/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/kiln-ai-kiln-vs-star-whale-starwhale.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, Kiln or starwhale? Kiln: Very active. starwhale: 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 Kiln and starwhale? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [Kiln trust report](/tools/kiln-ai-kiln/trust); [starwhale trust report](/tools/star-whale-starwhale/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=kiln-ai-kiln`](/api/graphcanon/graph?tool=kiln-ai-kiln) - 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/_