--- title: "ColossalAI vs onepanel" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/hpcaitech-colossalai-vs-onepanelio-onepanel" tools: ["hpcaitech-colossalai", "onepanelio-onepanel"] --- # ColossalAI vs onepanel *GraphCanon updated Jul 11, 2026* ## Verdict Pick ColossalAI when colossalAI is primarily Python; onepanel is Go; pick onepanel when onepanel is primarily Go; ColossalAI is Python. [ColossalAI](https://www.colossalai.org) reports 41k GitHub stars, 4.5k forks, and 501 open issues, last pushed May 25, 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 [ColossalAI's repository](https://github.com/hpcaitech/ColossalAI) and [onepanel's repository](https://github.com/onepanelio/onepanel). | | [ColossalAI](/tools/hpcaitech-colossalai.md) | [onepanel](/tools/onepanelio-onepanel.md) | | --- | --- | --- | | Tagline | Making large AI models cheaper, faster and more accessible | The open source, end-to-end computer vision platform. Label, build, train, tune, deploy and automate in a unified platform that runs on any cloud and on-premises. | | Stars | 41,408 | 730 | | Forks | 4,504 | 73 | | Open issues | 501 | 102 | | Language | Python | Go | | Adopt for | ColossalAI is a Python library that leverages advanced parallelism techniques for more efficient and cost-effective development of large-scale AI models. | - | | Persona | - | - | | Runtime | - | - | | License | Apache-2.0 | Apache-2.0 | | Categories | Inference & Serving, Model Training | Inference & Serving, Model Training, Vector Databases | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [ColossalAI](/tools/hpcaitech-colossalai.md) | [onepanel](/tools/onepanelio-onepanel.md) | | --- | --- | --- | | Maintenance | Steady (60%) | Dormant (18%) | | Days since push | 46d | 1232d | | Open issues (now) | 501 | 102 | | Security scan | No lockfile | 113 low (113 low) | | Full report | [trust report](/tools/hpcaitech-colossalai/trust.md) | [trust report](/tools/onepanelio-onepanel/trust.md) | ## Decision facts: ColossalAI - **Adopt for:** ColossalAI is a Python library that leverages advanced parallelism techniques for more efficient and cost-effective development of large-scale AI models. ## Choose when ### Choose ColossalAI if… - ColossalAI is primarily Python; onepanel is Go. - Tags unique to ColossalAI: big-model, data-parallelism, deep-learning, distributed-computing. - You require handling extremely large AI models with massive context windows, such as over 2M tokens. ### Choose onepanel if… - onepanel is primarily Go; ColossalAI is Python. - Tags unique to onepanel: aiops, annotation, computer-vision, deeplearning. - Also covers Vector Databases. - onepanel ships Docker support for self-hosted deployment. ## When NOT to use ColossalAI - You are working in an environment that does not support Linux OS, as ColossalAI currently offers no support for other operating systems. - Your current CUDA version is less than 11.0 or your GPU compute capability is below 7.0 (pre-V100/RTX20 series). - You cannot satisfy the minimum hardware and software requirements specified, such as PyTorch >= 2.2 and Python >= 3.7. ## When NOT to use onepanel - Last GitHub push was 1233 days ago (dormant maintenance, Feb 25, 2023). Validate activity before betting a new project on onepanel. - Inference & Serving: Self-hosting rarely beats a hosted API on cost until you have steady, high-volume traffic. - Model Training: Try prompting and RAG first; fine-tuning is the answer to style/format, not missing knowledge. - Vector Databases: Don't reach for a dedicated vector DB under ~100k vectors; pgvector on your existing Postgres is simpler to operate. ## Common questions ### What is the difference between ColossalAI and onepanel? ColossalAI: Making large AI models cheaper, faster and more accessible. onepanel: The open source, end-to-end computer vision platform. Label, build, train, tune, deploy and automate in a unified platform that runs on any cloud and on-premises.. See the comparison table for live GitHub stats and shared categories. ### When should I choose ColossalAI over onepanel? Choose ColossalAI over onepanel when ColossalAI is primarily Python; onepanel is Go; Tags unique to ColossalAI: big-model, data-parallelism, deep-learning, distributed-computing; You require handling extremely large AI models with massive context windows, such as over 2M tokens. ### When should I choose onepanel over ColossalAI? Choose onepanel over ColossalAI when onepanel is primarily Go; ColossalAI is Python; Tags unique to onepanel: aiops, annotation, computer-vision, deeplearning; Also covers Vector Databases; onepanel ships Docker support for self-hosted deployment. ### When should I avoid ColossalAI? You are working in an environment that does not support Linux OS, as ColossalAI currently offers no support for other operating systems. Your current CUDA version is less than 11.0 or your GPU compute capability is below 7.0 (pre-V100/RTX20 series). You cannot satisfy the minimum hardware and software requirements specified, such as PyTorch >= 2.2 and Python >= 3.7. ### When should I avoid onepanel? Last GitHub push was 1233 days ago (dormant maintenance, Feb 25, 2023). Validate activity before betting a new project on onepanel. Inference & Serving: Self-hosting rarely beats a hosted API on cost until you have steady, high-volume traffic. Model Training: Try prompting and RAG first; fine-tuning is the answer to style/format, not missing knowledge. Vector Databases: Don't reach for a dedicated vector DB under ~100k vectors; pgvector on your existing Postgres is simpler to operate. ### Is ColossalAI or onepanel more popular on GitHub? ColossalAI has more GitHub stars (41,408 vs 730). Stars measure visibility, not whether either tool fits your constraints. ### Are ColossalAI and onepanel open source? Yes - both are open-source projects on GitHub (ColossalAI: Apache-2.0, onepanel: Apache-2.0). ### Where can I find alternatives to ColossalAI or onepanel? GraphCanon lists graph-backed alternatives at [ColossalAI alternatives](/tools/hpcaitech-colossalai/alternatives) and [onepanel alternatives](/tools/onepanelio-onepanel/alternatives) ([ColossalAI markdown twin](/tools/hpcaitech-colossalai/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/hpcaitech-colossalai-vs-onepanelio-onepanel.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, ColossalAI or onepanel? ColossalAI: Steady. 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 ColossalAI and onepanel? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [ColossalAI trust report](/tools/hpcaitech-colossalai/trust); [onepanel trust report](/tools/onepanelio-onepanel/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=hpcaitech-colossalai`](/api/graphcanon/graph?tool=hpcaitech-colossalai) - 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/_