--- title: "ColossalAI vs optuna" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/hpcaitech-colossalai-vs-optuna-optuna" tools: ["hpcaitech-colossalai", "optuna-optuna"] --- # ColossalAI vs optuna *GraphCanon updated Jul 11, 2026* ## Verdict Pick ColossalAI when license: ColossalAI is Apache-2.0, optuna is MIT; pick optuna when license: optuna is MIT, 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. [optuna](https://optuna.org) has 14k stars, 1.4k forks, and 23 open issues, last pushed Jul 10, 2026. Figures are from public GitHub metadata via [ColossalAI's repository](https://github.com/hpcaitech/ColossalAI) and [optuna's repository](https://github.com/optuna/optuna). | | [ColossalAI](/tools/hpcaitech-colossalai.md) | [optuna](/tools/optuna-optuna.md) | | --- | --- | --- | | Tagline | Making large AI models cheaper, faster and more accessible | A hyperparameter optimization framework | | Stars | 41,408 | 14,482 | | Forks | 4,504 | 1,354 | | Open issues | 501 | 23 | | 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 | MIT | | Categories | Inference & Serving, Model Training | Model Training | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [ColossalAI](/tools/hpcaitech-colossalai.md) | [optuna](/tools/optuna-optuna.md) | | --- | --- | --- | | Maintenance | Steady (60%) | Very active (96%) | | Days since push | 46d | 1d | | Open issues (now) | 501 | 23 | | Full report | [trust report](/tools/hpcaitech-colossalai/trust.md) | [trust report](/tools/optuna-optuna/trust.md) | ## Shared compatibility - **Python**: [ColossalAI](/tools/hpcaitech-colossalai.md) - Python runtime; [optuna](/tools/optuna-optuna.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 ColossalAI if… - License: ColossalAI is Apache-2.0, optuna is MIT. - Tags unique to ColossalAI: ai, big model, data-parallelism, deep-learning. - Also covers Inference & Serving. - You require handling extremely large AI models with massive context windows, such as over 2M tokens. ### Choose optuna if… - License: optuna is MIT, ColossalAI is Apache-2.0. - Tags unique to optuna: distributed, hyperparameter-optimization, machine-learning, parallel. - More recently updated (last pushed Jul 10, 2026). ## 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 optuna - 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 optuna? ColossalAI: Making large AI models cheaper, faster and more accessible. optuna: A hyperparameter optimization framework. See the comparison table for live GitHub stats and shared categories. ### When should I choose ColossalAI over optuna? Choose ColossalAI over optuna when License: ColossalAI is Apache-2.0, optuna is MIT; Tags unique to ColossalAI: ai, big model, data-parallelism, deep-learning; Also covers Inference & Serving; You require handling extremely large AI models with massive context windows, such as over 2M tokens. ### When should I choose optuna over ColossalAI? Choose optuna over ColossalAI when License: optuna is MIT, ColossalAI is Apache-2.0; Tags unique to optuna: distributed, hyperparameter-optimization, machine-learning, parallel; More recently updated (last pushed Jul 10, 2026). ### 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 optuna? Model Training: Try prompting and RAG first; fine-tuning is the answer to style/format, not missing knowledge. ### Is ColossalAI or optuna more popular on GitHub? ColossalAI has more GitHub stars (41,408 vs 14,482). Stars measure visibility, not whether either tool fits your constraints. ### Are ColossalAI and optuna open source? Yes - both are open-source projects on GitHub (ColossalAI: Apache-2.0, optuna: MIT). ### Where can I find alternatives to ColossalAI or optuna? GraphCanon lists graph-backed alternatives at [ColossalAI alternatives](/tools/hpcaitech-colossalai/alternatives) and [optuna alternatives](/tools/optuna-optuna/alternatives) ([ColossalAI markdown twin](/tools/hpcaitech-colossalai/alternatives.md), [optuna markdown twin](/tools/optuna-optuna/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-optuna-optuna.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, ColossalAI or optuna? ColossalAI: Steady. optuna: 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 ColossalAI and optuna? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [ColossalAI trust report](/tools/hpcaitech-colossalai/trust); [optuna trust report](/tools/optuna-optuna/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/_