--- title: "budgetml vs ColossalAI" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/ebhy-budgetml-vs-hpcaitech-colossalai" tools: ["ebhy-budgetml", "hpcaitech-colossalai"] --- # budgetml vs ColossalAI *GraphCanon updated Jul 11, 2026* ## Verdict Pick budgetml when tags unique to budgetml: api, data-science, deployment, fastapi; pick ColossalAI when tags unique to ColossalAI: ai, big-model, data-parallelism, deep-learning. [budgetml](https://github.com/ebhy/budgetml) reports 1.3k GitHub stars, 65 forks, and 4 open issues, last pushed Feb 12, 2024. [ColossalAI](https://www.colossalai.org) has 41k stars, 4.5k forks, and 501 open issues, last pushed May 25, 2026. Figures are from public GitHub metadata via [budgetml's repository](https://github.com/ebhy/budgetml) and [ColossalAI's repository](https://github.com/hpcaitech/ColossalAI). | | [budgetml](/tools/ebhy-budgetml.md) | [ColossalAI](/tools/hpcaitech-colossalai.md) | | --- | --- | --- | | Tagline | Deploy a ML inference service on a budget in less than 10 lines of code. | Making large AI models cheaper, faster and more accessible | | Stars | 1,343 | 41,408 | | Forks | 65 | 4,504 | | Open issues | 4 | 501 | | 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 | Apache-2.0 | | Categories | Inference & Serving | Inference & Serving, Model Training | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [budgetml](/tools/ebhy-budgetml.md) | [ColossalAI](/tools/hpcaitech-colossalai.md) | | --- | --- | --- | | Maintenance | Dormant (18%) | Steady (60%) | | Days since push | 880d | 46d | | Open issues (now) | 4 | 501 | | Security scan | No criticals | No lockfile | | Full report | [trust report](/tools/ebhy-budgetml/trust.md) | [trust report](/tools/hpcaitech-colossalai/trust.md) | ## Shared compatibility - **Python**: [budgetml](/tools/ebhy-budgetml.md) - Python runtime; [ColossalAI](/tools/hpcaitech-colossalai.md) - Python runtime ## 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 budgetml if… - Tags unique to budgetml: api, data-science, deployment, fastapi. - Leaner open-issue backlog (4). ### Choose ColossalAI if… - Tags unique to ColossalAI: ai, big-model, data-parallelism, deep-learning. - Also covers Model Training. - You require handling extremely large AI models with massive context windows, such as over 2M tokens. ## When NOT to use budgetml - Last GitHub push was 880 days ago (dormant maintenance, Feb 12, 2024). Validate activity before betting a new project on budgetml. - 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 budgetml and ColossalAI? budgetml: Deploy a ML inference service on a budget in less than 10 lines of code.. 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 budgetml over ColossalAI? Choose budgetml over ColossalAI when Tags unique to budgetml: api, data-science, deployment, fastapi; Leaner open-issue backlog (4). ### When should I choose ColossalAI over budgetml? Choose ColossalAI over budgetml when Tags unique to ColossalAI: ai, big-model, data-parallelism, deep-learning; Also covers Model Training; You require handling extremely large AI models with massive context windows, such as over 2M tokens. ### When should I avoid budgetml? Last GitHub push was 880 days ago (dormant maintenance, Feb 12, 2024). Validate activity before betting a new project on budgetml. 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 budgetml or ColossalAI more popular on GitHub? ColossalAI has more GitHub stars (41,408 vs 1,343). Stars measure visibility, not whether either tool fits your constraints. ### Are budgetml and ColossalAI open source? Yes - both are open-source projects on GitHub (budgetml: Apache-2.0, ColossalAI: Apache-2.0). ### Where can I find alternatives to budgetml or ColossalAI? GraphCanon lists graph-backed alternatives at [budgetml alternatives](/tools/ebhy-budgetml/alternatives) and [ColossalAI alternatives](/tools/hpcaitech-colossalai/alternatives) ([budgetml markdown twin](/tools/ebhy-budgetml/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/ebhy-budgetml-vs-hpcaitech-colossalai.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, budgetml or ColossalAI? budgetml: Dormant. ColossalAI: Steady. 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 budgetml and ColossalAI? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [budgetml trust report](/tools/ebhy-budgetml/trust); [ColossalAI trust report](/tools/hpcaitech-colossalai/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=ebhy-budgetml`](/api/graphcanon/graph?tool=ebhy-budgetml) - 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/_