--- title: "ColossalAI vs RobustVideoMatting" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/hpcaitech-colossalai-vs-peterl1n-robustvideomatting" tools: ["hpcaitech-colossalai", "peterl1n-robustvideomatting"] --- # ColossalAI vs RobustVideoMatting *GraphCanon updated Jul 11, 2026* ## Verdict Pick ColossalAI when license: ColossalAI is Apache-2.0, RobustVideoMatting is GPL-3.0; pick RobustVideoMatting when license: RobustVideoMatting is GPL-3.0, ColossalAI is Apache-2.0. [ColossalAI](https://www.colossalai.org) reports 41k GitHub stars, 4.5k forks, and 501 open issues, last pushed May 25, 2026. [RobustVideoMatting](https://peterl1n.github.io/RobustVideoMatting/) has 9.4k stars, 1.2k forks, and 122 open issues, last pushed Apr 2, 2024. Figures are from public GitHub metadata via [ColossalAI's repository](https://github.com/hpcaitech/ColossalAI) and [RobustVideoMatting's repository](https://github.com/PeterL1n/RobustVideoMatting). | | [ColossalAI](/tools/hpcaitech-colossalai.md) | [RobustVideoMatting](/tools/peterl1n-robustvideomatting.md) | | --- | --- | --- | | Tagline | Making large AI models cheaper, faster and more accessible | Robust Video Matting in PyTorch, TensorFlow, TensorFlow.js, ONNX, CoreML! | | Stars | 41,408 | 9,422 | | Forks | 4,504 | 1,197 | | Open issues | 501 | 122 | | Language | Python | Python | | 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 | GPL-3.0 | | Categories | Inference & Serving, Model Training | Computer Vision, Inference & Serving, Model Training | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [ColossalAI](/tools/hpcaitech-colossalai.md) | [RobustVideoMatting](/tools/peterl1n-robustvideomatting.md) | | --- | --- | --- | | Maintenance | Steady (60%) | Dormant (18%) | | Days since push | 46d | 829d | | Open issues (now) | 501 | 122 | | Owner type | Organization | User | | Full report | [trust report](/tools/hpcaitech-colossalai/trust.md) | [trust report](/tools/peterl1n-robustvideomatting/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… - License: ColossalAI is Apache-2.0, RobustVideoMatting is GPL-3.0. - Tags unique to ColossalAI: big-model, data-parallelism, distributed-computing, foundation models. - You require handling extremely large AI models with massive context windows, such as over 2M tokens. ### Choose RobustVideoMatting if… - License: RobustVideoMatting is GPL-3.0, ColossalAI is Apache-2.0. - Tags unique to RobustVideoMatting: computer-vision, machine-learning, matting, python. - Also covers Computer Vision. ## 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 RobustVideoMatting - Last GitHub push was 830 days ago (dormant maintenance, Apr 2, 2024). Validate activity before betting a new project on RobustVideoMatting. - 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. ## Common questions ### What is the difference between ColossalAI and RobustVideoMatting? ColossalAI: Making large AI models cheaper, faster and more accessible. RobustVideoMatting: Robust Video Matting in PyTorch, TensorFlow, TensorFlow.js, ONNX, CoreML!. See the comparison table for live GitHub stats and shared categories. ### When should I choose ColossalAI over RobustVideoMatting? Choose ColossalAI over RobustVideoMatting when License: ColossalAI is Apache-2.0, RobustVideoMatting is GPL-3.0; Tags unique to ColossalAI: big-model, data-parallelism, distributed-computing, foundation models; You require handling extremely large AI models with massive context windows, such as over 2M tokens. ### When should I choose RobustVideoMatting over ColossalAI? Choose RobustVideoMatting over ColossalAI when License: RobustVideoMatting is GPL-3.0, ColossalAI is Apache-2.0; Tags unique to RobustVideoMatting: computer-vision, machine-learning, matting, python; Also covers Computer Vision. ### 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 RobustVideoMatting? Last GitHub push was 830 days ago (dormant maintenance, Apr 2, 2024). Validate activity before betting a new project on RobustVideoMatting. 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. ### Is ColossalAI or RobustVideoMatting more popular on GitHub? ColossalAI has more GitHub stars (41,408 vs 9,422). Stars measure visibility, not whether either tool fits your constraints. ### Are ColossalAI and RobustVideoMatting open source? Yes - both are open-source projects on GitHub (ColossalAI: Apache-2.0, RobustVideoMatting: GPL-3.0). ### Where can I find alternatives to ColossalAI or RobustVideoMatting? GraphCanon lists graph-backed alternatives at [ColossalAI alternatives](/tools/hpcaitech-colossalai/alternatives) and [RobustVideoMatting alternatives](/tools/peterl1n-robustvideomatting/alternatives) ([ColossalAI markdown twin](/tools/hpcaitech-colossalai/alternatives.md), [RobustVideoMatting markdown twin](/tools/peterl1n-robustvideomatting/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-peterl1n-robustvideomatting.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, ColossalAI or RobustVideoMatting? ColossalAI: Steady. RobustVideoMatting: 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 RobustVideoMatting? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [ColossalAI trust report](/tools/hpcaitech-colossalai/trust); [RobustVideoMatting trust report](/tools/peterl1n-robustvideomatting/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/_