DeepSpeed
MicrosoftDeepSpeed is a deep-learning optimization library for efficient distributed training and inference of very large models. It provides system-level innovations including ZeRO memory optimization, ZeRO-Infinity, 3D parallelism, and mixture-of-experts support, and has powered training of models like BLOOM (176B) and Megatron-Turing NLG (530B). It is maintained by Microsoft and integrates with Hugging Face Transformers, PyTorch Lightning, and others.
Verified 2026-08-13 via GitHub and the LICENSE body.
Openness
5 high confidence- license
- Apache-2.0(OSI)
- source
- public
- core-gated
- ungated
Apache-2.0 license body confirmed; full source public. The repository is public and unarchived, and the README describes the whole library with no paid, enterprise or hosted tier beside it, so source is public and the core ungated.
- https://github.com/deepspeedai/DeepSpeed/blob/master/LICENSE recorded 2026-08-13
LICENSE file is the verbatim Apache License Version 2.0 text
- https://api.github.com/repos/deepspeedai/DeepSpeed recorded 2026-08-13
Repo metadata - license spdx_id Apache-2.0, private false, archived false, default branch master - for deepspeedai/DeepSpeed.
- https://raw.githubusercontent.com/deepspeedai/DeepSpeed/master/README.md recorded 2026-08-13
README describes the training and inference optimization stack - ZeRO, 3D parallelism, MoE - with everything installed from the public package. No paid tier appears.
Adoption
4 high confidence1,112,723 PyPI downloads of `deepspeed` in the trailing 30 days, which falls in the 1M-10M a month band of the software usage scale, level 4.
- https://pypistats.org/api/packages/deepspeed/recent recorded 2026-08-13
last_month downloads = 1,112,723 for deepspeed
Capability
5 high confidenceFoundational scale-out training stack used for many of the largest published models.
- https://github.com/deepspeedai/DeepSpeed recorded 2026-08-13
README still describes ZeRO, ZeRO-Infinity, 3D parallelism and MoE, and the models it trained
Verified 2026-08-13