--- title: "onepanel vs geti_v2" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/onepanelio-onepanel-vs-open-edge-platform-geti-v2" tools: ["onepanelio-onepanel", "open-edge-platform-geti-v2"] --- # onepanel vs geti_v2 *GraphCanon updated Aug 24, 2026* ## Verdict 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; pick geti_v2 if geti_v2 is designed for developers who need to build computer vision models quickly using limited datasets. It supports TypeScript and integrates with. [onepanel](https://docs.onepanel.ai/) reports 730 GitHub stars, 73 forks, and 102 open issues, last pushed Feb 25, 2023. [geti_v2](https://docs.geti.intel.com/docs/2.0/user-guide/getting-started/introduction) has 483 stars, 50 forks, and 87 open issues, last pushed Jul 30, 2026. Figures are from public GitHub metadata via [onepanel's repository](https://github.com/onepanelio/onepanel) and [geti_v2's repository](https://github.com/open-edge-platform/geti_v2). | | [onepanel](/tools/onepanelio-onepanel.md) | [geti_v2](/tools/open-edge-platform-geti-v2.md) | | --- | --- | --- | | Tagline | The open source, end-to-end computer vision platform. | Build computer vision models quickly with less data | | Stars | 730 | 483 | | Forks | 73 | 50 | | Open issues | 102 | 87 | | Language | Go | TypeScript | | 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. | geti_v2 is designed for developers who need to build computer vision models quickly using limited datasets. It supports TypeScript and integrates with frameworks like OpenVINO. | | Persona | - | - | | Runtime | - | - | | License | Apache-2.0 | The licensing type is listed as 'Other', implying that the license details should be closely reviewed for specific terms. | | Categories | Computer Vision, Inference & Serving, Model Training | Computer Vision, Inference & Serving, Model Training | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [onepanel](/tools/onepanelio-onepanel.md) | [geti_v2](/tools/open-edge-platform-geti-v2.md) | | --- | --- | --- | | Maintenance | Dormant (18%) | Archived (8%) | | Days since push | 1252d | 25d | | Archived on GitHub | No | Yes | | Open issues (now) | 102 | 87 | | Stars delta | Unknown | -1 (30d) | | Open issues delta | Unknown | +1 (30d) | | Full report | [trust report](/tools/onepanelio-onepanel/trust.md) | [trust report](/tools/open-edge-platform-geti-v2/trust.md) | ## 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. ## Decision facts: geti_v2 - **Pricing:** unknown - Pricing information is not provided. - **Requirements:** Min 0 GB RAM - **Adopt for:** geti_v2 is designed for developers who need to build computer vision models quickly using limited datasets. It supports TypeScript and integrates with frameworks like OpenVINO. - **License detail:** The licensing type is listed as 'Other', implying that the license details should be closely reviewed for specific terms. ## Choose when ### Choose onepanel if… - onepanel is primarily Go; geti_v2 is TypeScript. - License: onepanel is Apache-2.0, geti_v2 is Other. - Tags unique to onepanel: aiops, annotation, deeplearning, hyperparameter-tuning. - onepanel ships Docker support for self-hosted deployment. - 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. ### Choose geti_v2 if… - geti_v2 is primarily TypeScript; onepanel is Go. - License: geti_v2 is Other, onepanel is Apache-2.0. - Pricing: Pricing information is not provided.. - Requirements: Min 0 GB RAM. - Tags unique to geti_v2: computer-vision, deep-learning, fine-tuning. - When you have a shortage of labeled data but still require high accuracy in your computer vision model. ## 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. ## When NOT to use geti_v2 - When you need to work with languages other than TypeScript, as geti_v2 is specifically designed for use with TypeScript environments. - In scenarios where you have abundant labeled data and can afford longer training times, which may not leverage the key advantage of geti_v2's efficiency in low-data conditions. ## Common questions ### What is the difference between onepanel and geti_v2? onepanel: The open source, end-to-end computer vision platform.. geti_v2: Build computer vision models quickly with less data. See the comparison table for live GitHub stats and shared categories. ### When should I choose onepanel over geti_v2? Choose onepanel over geti_v2 when onepanel is primarily Go; geti_v2 is TypeScript; License: onepanel is Apache-2.0, geti_v2 is Other; Tags unique to onepanel: aiops, annotation, deeplearning, hyperparameter-tuning; onepanel ships Docker support for self-hosted deployment; 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 choose geti_v2 over onepanel? Choose geti_v2 over onepanel when geti_v2 is primarily TypeScript; onepanel is Go; License: geti_v2 is Other, onepanel is Apache-2.0; Pricing: Pricing information is not provided.; Requirements: Min 0 GB RAM; Tags unique to geti_v2: computer-vision, deep-learning, fine-tuning; When you have a shortage of labeled data but still require high accuracy in your computer vision model. ### 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. ### When should I avoid geti_v2? When you need to work with languages other than TypeScript, as geti_v2 is specifically designed for use with TypeScript environments. In scenarios where you have abundant labeled data and can afford longer training times, which may not leverage the key advantage of geti_v2's efficiency in low-data conditions. ### Is onepanel or geti_v2 more popular on GitHub? onepanel has more GitHub stars (730 vs 483). Stars measure visibility, not whether either tool fits your constraints. ### Are onepanel and geti_v2 open source? Yes - both are open-source projects on GitHub (onepanel: Apache-2.0, geti_v2: Other). ### Where can I find alternatives to onepanel or geti_v2? GraphCanon lists graph-backed alternatives at [onepanel alternatives](/tools/onepanelio-onepanel/alternatives) and [geti_v2 alternatives](/tools/open-edge-platform-geti-v2/alternatives) ([onepanel markdown twin](/tools/onepanelio-onepanel/alternatives.md), [geti_v2 markdown twin](/tools/open-edge-platform-geti-v2/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/onepanelio-onepanel-vs-open-edge-platform-geti-v2.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, onepanel or geti_v2? onepanel: Dormant. geti_v2: Archived. 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 onepanel and geti_v2? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [onepanel trust report](/tools/onepanelio-onepanel/trust); [geti_v2 trust report](/tools/open-edge-platform-geti-v2/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=onepanelio-onepanel`](/api/graphcanon/graph?tool=onepanelio-onepanel) - 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/_