DeepSpeed
DeepSpeed is a deep learning optimization library that makes distributed training and inference easy, efficient, and effective.
Our verdict
A usable project with some maintenance caveats. This assessment is derived from GitHub's own repository metrics on 2026-08-30, not from hands-on testing.
DeepSpeed is a deep learning optimization library that makes distributed training and inference easy, efficient, and effective. The project is written primarily in Python, released under Apache-2.0, and has 43,022 stars and 4,950 forks on GitHub. 506 contributors have committed to it, and the most recent push was 2026-08-29. The latest tagged release is v0.19.6 (2026-08-27). Figures come from the GitHub API on 2026-08-30 and are refreshed daily; the score below weighs adoption, maintenance, release discipline, contributor breadth, licence clarity and issue hygiene.
Repository
- Licence
- Apache-2.0
- Language
- Python
- Last push
- 2026-08-29
Releases
-
v0.19.6v0.19.6 Patch Release -
v0.19.5v0.19.5 Patch Release -
v0.19.4v0.19.4 Patch Release -
v0.19.3v0.19.3 Patch Release -
v0.19.2v0.19.2 Patch Release -
v0.19.1v0.19.1
Pros and cons
Pros
Cons
Pricing
- Free tierYes
- LicenceApache-2.0
- Self-hostYes, source is public
- Public price listNot published
DeepSpeed does not publish a web price list. For consumer apps that usually means pricing appears inside the product; for enterprise tools it means talking to sales. Why we do this
Visit www.deepspeed.aiTrends
Price points are recorded when a price moves, not on a schedule, so a flat run means the price held. Release cadence comes from GitHub releases. A series appears only once we have watched it for long enough to have more than one observation.
User reviews
No one has reviewed DeepSpeed here yet. Reviews are moderated before they appear, and our own score is editorial and separate from user ratings, though once reviews land they do lift it.
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DeepSpeed alternatives
PEFT
🤗 PEFT: State-of-the-art Parameter-Efficient Fine-Tuning.
PyTorch Image Models (timm)
The largest collection of PyTorch image encoders / backbones.…
fastai
The fastai deep learning library
LlamaFactory
Unified Efficient Fine-Tuning of 100+ LLMs & VLMs (ACL…
Hugging Face Datasets
🤗 The largest hub of ready-to-use datasets for AI…
Label Studio
Label Studio is a multi-type data labeling and annotation…
Side by side
| Tool | Our score | From | Free tier | Best for | |
|---|---|---|---|---|---|
| DeepSpeed this page | 7 | - | Yes | ||
| PEFT | 7.7 | - | Yes | ||
| PyTorch Image Models (timm) | 7.7 | - | Yes | ||
| fastai | 7.4 | - | Yes | ||
| LlamaFactory | 7.3 | - | Yes | ||
| Hugging Face Datasets | 7 | - | Yes | ||
| Label Studio | 6.7 | - | Yes |
Questions
Is DeepSpeed free?
Yes. DeepSpeed advertises a free tier on its own site.
How much does DeepSpeed cost?
DeepSpeed does not publish a web price list. For consumer apps that usually means pricing appears inside the product; for enterprise tools it means talking to sales.
Is DeepSpeed open source?
Yes. DeepSpeed is a public repository released under Apache-2.0. You can self-host or inspect the source directly.
How is DeepSpeed scored here?
DeepSpeed scores 7.0 out of 10. That comes from a desk review of public evidence, which is capped at 8.5 out of 10: public pricing, documentation, maintenance signals and how much we could actually verify. Affiliate relationships are excluded from scoring entirely. The full rubric is published on our methodology page.