--- title: "paperless-ai vs ColossalAI" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/clusterzx-paperless-ai-vs-hpcaitech-colossalai" tools: ["clusterzx-paperless-ai", "hpcaitech-colossalai"] --- # paperless-ai vs ColossalAI *GraphCanon updated Jul 15, 2026* ## Verdict Pick paperless-ai when paperless-ai is primarily JavaScript; ColossalAI is Python; pick ColossalAI when colossalAI is primarily Python; paperless-ai is JavaScript. [paperless-ai](https://clusterzx.github.io/paperless-ai/) reports 5.8k GitHub stars, 318 forks, and 56 open issues, last pushed Jul 5, 2026. [ColossalAI](https://www.colossalai.org) has 41k stars, 4.5k forks, and 499 open issues, last pushed Jul 13, 2026. Figures are from public GitHub metadata via [paperless-ai's repository](https://github.com/clusterzx/paperless-ai) and [ColossalAI's repository](https://github.com/hpcaitech/ColossalAI). | | [paperless-ai](/tools/clusterzx-paperless-ai.md) | [ColossalAI](/tools/hpcaitech-colossalai.md) | | --- | --- | --- | | Tagline | An automated document analyzer for Paperless-ngx using OpenAI API, Ollama, Deepseek-r1, Azure and all OpenAI API compatible Services to automatically analyze and tag your documents. | Making large AI models cheaper, faster and more accessible | | Stars | 5,819 | 41,413 | | Forks | 318 | 4,502 | | Open issues | 56 | 499 | | Language | JavaScript | 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 | MIT | Apache-2.0 | | Categories | Inference & Serving | Inference & Serving, Model Training | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [paperless-ai](/tools/clusterzx-paperless-ai.md) | [ColossalAI](/tools/hpcaitech-colossalai.md) | | --- | --- | --- | | Maintenance | Active (82%) | Very active (96%) | | Days since push | 10d | 0d | | Open issues (now) | 56 | 499 | | Owner type | User | Organization | | Full report | [trust report](/tools/clusterzx-paperless-ai/trust.md) | [trust report](/tools/hpcaitech-colossalai/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 paperless-ai if… - paperless-ai is primarily JavaScript; ColossalAI is Python. - License: paperless-ai is MIT, ColossalAI is Apache-2.0. - Tags unique to paperless-ai: automation, gemma, llama, mistral. ### Choose ColossalAI if… - ColossalAI is primarily Python; paperless-ai is JavaScript. - License: ColossalAI is Apache-2.0, paperless-ai is MIT. - Tags unique to ColossalAI: big model, data-parallelism, deep-learning, distributed-computing. - Also covers Model Training. - You require handling extremely large AI models with massive context windows, such as over 2M tokens. ## When NOT to use paperless-ai - Inference & Serving: Self-hosting rarely beats a hosted API on cost until you have steady, high-volume traffic. ## 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. ## Common questions ### What is the difference between paperless-ai and ColossalAI? paperless-ai: An automated document analyzer for Paperless-ngx using OpenAI API, Ollama, Deepseek-r1, Azure and all OpenAI API compatible Services to automatically analyze and tag your documents.. ColossalAI: Making large AI models cheaper, faster and more accessible. See the comparison table for live GitHub stats and shared categories. ### When should I choose paperless-ai over ColossalAI? Choose paperless-ai over ColossalAI when paperless-ai is primarily JavaScript; ColossalAI is Python; License: paperless-ai is MIT, ColossalAI is Apache-2.0; Tags unique to paperless-ai: automation, gemma, llama, mistral. ### When should I choose ColossalAI over paperless-ai? Choose ColossalAI over paperless-ai when ColossalAI is primarily Python; paperless-ai is JavaScript; License: ColossalAI is Apache-2.0, paperless-ai is MIT; Tags unique to ColossalAI: big model, data-parallelism, deep-learning, distributed-computing; Also covers Model Training; You require handling extremely large AI models with massive context windows, such as over 2M tokens. ### When should I avoid paperless-ai? Inference & Serving: Self-hosting rarely beats a hosted API on cost until you have steady, high-volume traffic. ### 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. ### Is paperless-ai or ColossalAI more popular on GitHub? ColossalAI has more GitHub stars (41,413 vs 5,819). Stars measure visibility, not whether either tool fits your constraints. ### Are paperless-ai and ColossalAI open source? Yes - both are open-source projects on GitHub (paperless-ai: MIT, ColossalAI: Apache-2.0). ### Where can I find alternatives to paperless-ai or ColossalAI? GraphCanon lists graph-backed alternatives at [paperless-ai alternatives](/tools/clusterzx-paperless-ai/alternatives) and [ColossalAI alternatives](/tools/hpcaitech-colossalai/alternatives) ([paperless-ai markdown twin](/tools/clusterzx-paperless-ai/alternatives.md), [ColossalAI markdown twin](/tools/hpcaitech-colossalai/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/clusterzx-paperless-ai-vs-hpcaitech-colossalai.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, paperless-ai or ColossalAI? paperless-ai: Active. ColossalAI: Very active. 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 paperless-ai and ColossalAI? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [paperless-ai trust report](/tools/clusterzx-paperless-ai/trust); [ColossalAI trust report](/tools/hpcaitech-colossalai/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=clusterzx-paperless-ai`](/api/graphcanon/graph?tool=clusterzx-paperless-ai) - 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/_