--- title: "DeepSpeed vs stt" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/deepspeedai-deepspeed-vs-jianchang512-stt" tools: ["deepspeedai-deepspeed", "jianchang512-stt"] --- # DeepSpeed vs stt *GraphCanon updated Jul 11, 2026* ## Verdict Pick DeepSpeed when license: DeepSpeed is Apache-2.0, stt is GPL-3.0; pick stt when license: stt is GPL-3.0, DeepSpeed is Apache-2.0. [DeepSpeed](https://www.deepspeed.ai/) reports 43k GitHub stars, 4.9k forks, and 1.3k open issues, last pushed Jul 11, 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 [DeepSpeed's repository](https://github.com/deepspeedai/DeepSpeed) and [stt's repository](https://github.com/jianchang512/stt). | | [DeepSpeed](/tools/deepspeedai-deepspeed.md) | [stt](/tools/jianchang512-stt.md) | | --- | --- | --- | | Tagline | Deep learning optimization library for efficient distributed training and inference | 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 | 42,685 | 4,664 | | Forks | 4,883 | 494 | | Open issues | 1,302 | 100 | | Language | Python | Python | | Adopt for | Decisions for DeepSpeed use are driven by its capacity to handle large models efficiently using techniques such as data parallelism, model parallelism, pipeline parallelism, and compression. | - | | Persona | - | - | | Runtime | - | - | | License | Apache-2.0 | GPL-3.0 | | Categories | Inference & Serving, Model Training | Inference & Serving, Model Training, Speech & Audio | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [DeepSpeed](/tools/deepspeedai-deepspeed.md) | [stt](/tools/jianchang512-stt.md) | | --- | --- | --- | | Maintenance | Very active (96%) | Slowing (36%) | | Days since push | 0d | 170d | | Open issues (now) | 1.3k | 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/deepspeedai-deepspeed/trust.md) | [trust report](/tools/jianchang512-stt/trust.md) | ## Decision facts: DeepSpeed - **Adopt for:** Decisions for DeepSpeed use are driven by its capacity to handle large models efficiently using techniques such as data parallelism, model parallelism, pipeline parallelism, and compression. ## Choose when ### Choose DeepSpeed if… - License: DeepSpeed is Apache-2.0, stt is GPL-3.0. - Tags unique to DeepSpeed: billion-parameters, compression, data-parallelism, deep-learning. - - When training or inferring with PyTorch on large datasets or complex deep learning models (up to trillion parameters) ### Choose stt if… - License: stt is GPL-3.0, DeepSpeed is Apache-2.0. - Tags unique to stt: python, speech, speech-recognition, speech-to-text. - Also covers Speech & Audio. ## When NOT to use DeepSpeed - - When you are working in an environment that only supports CPU-based training without access to CUDA or ROCm compatible GPUs - - If your project's PyTorch version is less than 2.0, DeepSpeed may not support all of its features and optimizations effectively ## 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. - 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 DeepSpeed and stt? DeepSpeed: Deep learning optimization library for efficient distributed training and inference. 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 DeepSpeed over stt? Choose DeepSpeed over stt when License: DeepSpeed is Apache-2.0, stt is GPL-3.0; Tags unique to DeepSpeed: billion-parameters, compression, data-parallelism, deep-learning; - When training or inferring with PyTorch on large datasets or complex deep learning models (up to trillion parameters). ### When should I choose stt over DeepSpeed? Choose stt over DeepSpeed when License: stt is GPL-3.0, DeepSpeed is Apache-2.0; Tags unique to stt: python, speech, speech-recognition, speech-to-text; Also covers Speech & Audio. ### When should I avoid DeepSpeed? - When you are working in an environment that only supports CPU-based training without access to CUDA or ROCm compatible GPUs - If your project's PyTorch version is less than 2.0, DeepSpeed may not support all of its features and optimizations effectively ### 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. 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 DeepSpeed or stt more popular on GitHub? DeepSpeed has more GitHub stars (42,685 vs 4,664). Stars measure visibility, not whether either tool fits your constraints. ### Are DeepSpeed and stt open source? Yes - both are open-source projects on GitHub (DeepSpeed: Apache-2.0, stt: GPL-3.0). ### Where can I find alternatives to DeepSpeed or stt? GraphCanon lists graph-backed alternatives at [DeepSpeed alternatives](/tools/deepspeedai-deepspeed/alternatives) and [stt alternatives](/tools/jianchang512-stt/alternatives) ([DeepSpeed markdown twin](/tools/deepspeedai-deepspeed/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/deepspeedai-deepspeed-vs-jianchang512-stt.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, DeepSpeed or stt? DeepSpeed: Very active. 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 DeepSpeed and stt? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [DeepSpeed trust report](/tools/deepspeedai-deepspeed/trust); [stt trust report](/tools/jianchang512-stt/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=deepspeedai-deepspeed`](/api/graphcanon/graph?tool=deepspeedai-deepspeed) - 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/_