--- title: "aikit vs onepanel" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/kaito-project-aikit-vs-onepanelio-onepanel" tools: ["kaito-project-aikit", "onepanelio-onepanel"] --- # aikit vs onepanel *GraphCanon updated Aug 24, 2026* ## Verdict Pick aikit if aikit is a toolkit designed for fine-tuning, building and deploying large language models (LLMs) with an emphasis on open-source technologies; pick onepanel if onepanel is an open source tool designed for computer vision projects with capabilities spanning from data labeling to model tuning and deployment, all supported by a Go-based codebase under the Apache-2.0 license. [aikit](https://kaito-project.github.io/aikit/) reports 537 GitHub stars, 57 forks, and 40 open issues, last pushed Aug 24, 2026. [onepanel](https://docs.onepanel.ai/) has 730 stars, 73 forks, and 102 open issues, last pushed Feb 25, 2023. Figures are from public GitHub metadata via [aikit's repository](https://github.com/kaito-project/aikit) and [onepanel's repository](https://github.com/onepanelio/onepanel). | | [aikit](/tools/kaito-project-aikit.md) | [onepanel](/tools/onepanelio-onepanel.md) | | --- | --- | --- | | Tagline | Fine-tune, build, and deploy open-source LLMs easily! | The open source, end-to-end computer vision platform. | | Stars | 537 | 730 | | Forks | 57 | 73 | | Open issues | 40 | 102 | | Language | Go | Go | | Adopt for | Aikit is a toolkit designed for fine-tuning, building and deploying large language models (LLMs) with an emphasis on open-source technologies. | Onepanel is an open source tool designed for computer vision projects with capabilities spanning from data labeling to model tuning and deployment, all supported by a Go-based codebase under the Apache-2.0 license. | | Persona | - | - | | Runtime | - | - | | License | MIT | Apache-2.0 | | Categories | Inference & Serving, LLM Frameworks, Model Training | Computer Vision, Inference & Serving, Model Training | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [aikit](/tools/kaito-project-aikit.md) | [onepanel](/tools/onepanelio-onepanel.md) | | --- | --- | --- | | Maintenance | Very active (96%) | Dormant (18%) | | Days since push | 0d | 1252d | | Open issues (now) | 40 | 102 | | Stars delta | +3 (30d) | Unknown | | Open issues delta | -3 (30d) | Unknown | | Full report | [trust report](/tools/kaito-project-aikit/trust.md) | [trust report](/tools/onepanelio-onepanel/trust.md) | ## Decision facts: aikit - **Adopt for:** Aikit is a toolkit designed for fine-tuning, building and deploying large language models (LLMs) with an emphasis on open-source technologies. ## Decision facts: onepanel - **Adopt for:** Onepanel is an open source tool designed for computer vision projects with capabilities spanning from data labeling to model tuning and deployment, all supported by a Go-based codebase under the Apache-2.0 license. ## Choose when ### Choose aikit if… - License: aikit is MIT, onepanel is Apache-2.0. - Tags unique to aikit: ai, buildkit, chatgpt, docker. - Also covers LLM Frameworks. - - You need a flexible solution specifically built using Go and prefer its concurrency model. ### Choose onepanel if… - License: onepanel is Apache-2.0, aikit is MIT. - Tags unique to onepanel: aiops, annotation, deeplearning, hyperparameter-tuning. - Also covers Computer Vision. - When you need an end-to-end platform that supports multiple aspects of computer vision including advanced functionalities such as hyperparameter tuning and automated workflows. ## When NOT to use aikit - - You have a preference or requirement for Python-based tools due to the lack of native support in Aikit. - - If your deployment setup strictly uses cloud-specific platforms and you do not use Kubernetes or Docker, as Aikit heavily integrates with containerized environments like these. ## When NOT to use onepanel - Avoid using Onepanel for projects that require extensive Java-based development because it is written in Go. - Not suitable if you seek a platform focusing solely on model serving or inference without capabilities to go back upstream into data labeling and preprocessing stages. ## Common questions ### What is the difference between aikit and onepanel? aikit: Fine-tune, build, and deploy open-source LLMs easily!. onepanel: The open source, end-to-end computer vision platform.. See the comparison table for live GitHub stats and shared categories. ### When should I choose aikit over onepanel? Choose aikit over onepanel when License: aikit is MIT, onepanel is Apache-2.0; Tags unique to aikit: ai, buildkit, chatgpt, docker; Also covers LLM Frameworks; - You need a flexible solution specifically built using Go and prefer its concurrency model. ### When should I choose onepanel over aikit? Choose onepanel over aikit when License: onepanel is Apache-2.0, aikit is MIT; Tags unique to onepanel: aiops, annotation, deeplearning, hyperparameter-tuning; Also covers Computer Vision; When you need an end-to-end platform that supports multiple aspects of computer vision including advanced functionalities such as hyperparameter tuning and automated workflows. ### When should I avoid aikit? - You have a preference or requirement for Python-based tools due to the lack of native support in Aikit. - If your deployment setup strictly uses cloud-specific platforms and you do not use Kubernetes or Docker, as Aikit heavily integrates with containerized environments like these. ### When should I avoid onepanel? Avoid using Onepanel for projects that require extensive Java-based development because it is written in Go. Not suitable if you seek a platform focusing solely on model serving or inference without capabilities to go back upstream into data labeling and preprocessing stages. ### Is aikit or onepanel more popular on GitHub? onepanel has more GitHub stars (730 vs 537). Stars measure visibility, not whether either tool fits your constraints. ### Are aikit and onepanel open source? Yes - both are open-source projects on GitHub (aikit: MIT, onepanel: Apache-2.0). ### Where can I find alternatives to aikit or onepanel? GraphCanon lists graph-backed alternatives at [aikit alternatives](/tools/kaito-project-aikit/alternatives) and [onepanel alternatives](/tools/onepanelio-onepanel/alternatives) ([aikit markdown twin](/tools/kaito-project-aikit/alternatives.md), [onepanel markdown twin](/tools/onepanelio-onepanel/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/kaito-project-aikit-vs-onepanelio-onepanel.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, aikit or onepanel? aikit: Very active. onepanel: 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 aikit and onepanel? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [aikit trust report](/tools/kaito-project-aikit/trust); [onepanel trust report](/tools/onepanelio-onepanel/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=kaito-project-aikit`](/api/graphcanon/graph?tool=kaito-project-aikit) - 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/_