--- title: "ColossalAI vs stt" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/hpcaitech-colossalai-vs-jianchang512-stt" tools: ["hpcaitech-colossalai", "jianchang512-stt"] --- # ColossalAI vs stt *GraphCanon updated Jul 11, 2026* ## Verdict Pick ColossalAI when license: ColossalAI is Apache-2.0, stt is GPL-3.0; pick stt when license: stt 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. [stt](https://pyvideotrans.com) has 4.7k stars, 494 forks, and 100 open issues, last pushed Jan 22, 2026. Figures are from public GitHub metadata via [ColossalAI's repository](https://github.com/hpcaitech/ColossalAI) and [stt's repository](https://github.com/jianchang512/stt). | | [ColossalAI](/tools/hpcaitech-colossalai.md) | [stt](/tools/jianchang512-stt.md) | | --- | --- | --- | | Tagline | Making large AI models cheaper, faster and more accessible | Voice Recognition to Text Tool / 一个离线运行的本地音视频转字幕工具，输出json、srt字幕、纯文字格式 | | Stars | 41,408 | 4,664 | | Forks | 4,504 | 494 | | Open issues | 501 | 100 | | 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 | Model Training, Inference & Serving | Model Training, Speech & Audio, Inference & Serving | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [ColossalAI](/tools/hpcaitech-colossalai.md) | [stt](/tools/jianchang512-stt.md) | | --- | --- | --- | | Maintenance | Steady (60%) | Slowing (36%) | | Days since push | 46d | 170d | | Open issues (now) | 501 | 100 | | Owner type | Organization | User | | Security scan | No lockfile | 1 critical, 2 high, 3 medium, 21 low (1 critical, 2 high, 3 medium, 21 low) | | Full report | [trust report](/tools/hpcaitech-colossalai/trust.md) | [trust report](/tools/jianchang512-stt/trust.md) | ## Shared compatibility - **Python**: [ColossalAI](/tools/hpcaitech-colossalai.md) - Python runtime; [stt](/tools/jianchang512-stt.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, stt is GPL-3.0. - Tags unique to ColossalAI: deep-learning, ai, big-model, heterogeneous-training. - You require handling extremely large AI models with massive context windows, such as over 2M tokens. ### Choose stt if… - License: stt is GPL-3.0, ColossalAI is Apache-2.0. - Tags unique to stt: speech, speech-to-text, python, stt. - Also covers Speech & Audio. ## 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 stt - Last GitHub push was 171 days ago (slowing maintenance, Jan 22, 2026). Validate activity before betting a new project on stt. - Model Training: Try prompting and RAG first; fine-tuning is the answer to style/format, not missing knowledge. - Inference & Serving: Self-hosting rarely beats a hosted API on cost until you have steady, high-volume traffic. ## Common questions ### What is the difference between ColossalAI and stt? ColossalAI: Making large AI models cheaper, faster and more accessible. stt: Voice Recognition to Text Tool / 一个离线运行的本地音视频转字幕工具，输出json、srt字幕、纯文字格式. See the comparison table for live GitHub stats and shared categories. ### When should I choose ColossalAI over stt? Choose ColossalAI over stt when License: ColossalAI is Apache-2.0, stt is GPL-3.0; Tags unique to ColossalAI: deep-learning, ai, big-model, heterogeneous-training; You require handling extremely large AI models with massive context windows, such as over 2M tokens. ### When should I choose stt over ColossalAI? Choose stt over ColossalAI when License: stt is GPL-3.0, ColossalAI is Apache-2.0; Tags unique to stt: speech, speech-to-text, python, stt; Also covers Speech & Audio. ### 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 stt? Last GitHub push was 171 days ago (slowing maintenance, Jan 22, 2026). Validate activity before betting a new project on stt. Model Training: Try prompting and RAG first; fine-tuning is the answer to style/format, not missing knowledge. Inference & Serving: Self-hosting rarely beats a hosted API on cost until you have steady, high-volume traffic. ### Is ColossalAI or stt more popular on GitHub? ColossalAI has more GitHub stars (41,408 vs 4,664). Stars measure visibility, not whether either tool fits your constraints. ### Are ColossalAI and stt open source? Yes - both are open-source projects on GitHub (ColossalAI: Apache-2.0, stt: GPL-3.0). ### Where can I find alternatives to ColossalAI or stt? GraphCanon lists graph-backed alternatives at [ColossalAI alternatives](/tools/hpcaitech-colossalai/alternatives) and [stt alternatives](/tools/jianchang512-stt/alternatives) ([ColossalAI markdown twin](/tools/hpcaitech-colossalai/alternatives.md), [stt markdown twin](/tools/jianchang512-stt/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-jianchang512-stt.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, ColossalAI or stt? ColossalAI: Steady. stt: Slowing. 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 stt? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [ColossalAI trust report](/tools/hpcaitech-colossalai/trust); [stt trust report](/tools/jianchang512-stt/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/_