Open Source
DeepSpeed
DeepSpeed is a deep learning optimization library that makes distributed training and inference easy, efficient, and effective.
Our verdict
We have not reviewed DeepSpeed yet
No one at Enterprise DNA has checked this listing against its sources. The description comes from public listings gathered automatically. Any fact below shows where it came from and when it was last checked.
From the listing
About DeepSpeed
DeepSpeed is a Python library for optimizing distributed training and inference of large language models and deep neural networks. It reduces memory footprint, accelerates training speed, and enables efficient multi-GPU and multi-node setups through techniques like gradient checkpointing, mixed precision, and ZeRO optimizer states partitioning.
Best for
Teams training large models who need to maximize GPU efficiency and scale across multiple devices.
Use cases
- Training large models on limited GPU memory
- Scaling training across multiple GPUs or nodes
- Reducing inference latency for deployed models
Notes
42,436 stars on GitHub. Last updated 2026-06-01. Licensed Apache-2.0.
Pros
- Significant memory savings enable training larger models on existing hardware
- Production-ready with strong community adoption and Microsoft backing
- Works with existing PyTorch code with minimal integration effort
Cons
- Steep learning curve for advanced features like ZeRO stages and custom configurations
- Debugging distributed training issues remains complex despite optimizations
- Performance gains vary significantly based on hardware, model architecture, and tuning
Key facts
What we have checked
- Latest version
- 0.19.8 (released 20 Oct 2026)
- GitHub stars
- 43,161
Each value shows when we last confirmed it and where it came from. Values we have not confirmed are left out, never guessed.
Stars and usage
How DeepSpeed is growing
42,436 to 43,161
Alternatives
Alternatives to DeepSpeed
| Record | Type | How we know | Checked |
|---|---|---|---|
| BMTrainAlternative to this | Open source | Named in the listing | Not dated |
| Colossal-AIAlternative to this | Open source | Named in the listing | Not dated |
| HorovodAlternative to this | Open source | Named in the listing | Not dated |
| Liger-KernelAlternative to this | Open source | Named in the listing | Not dated |
| maxtextAlternative to this | Open source | Named in the listing | Not dated |
| Megatron-LMAlternative to this | Open source | Named in the listing | Not dated |
| Mesh TensorflowAlternative to this | Open source | Named in the listing | Not dated |
| MInferenceAlternative to this | Open source | Named in the listing | Not dated |
| nanotronAlternative to this | Open source | Named in the listing | Not dated |
| NeMo FrameworkAlternative to this | Open source | Named in the listing | Not dated |
| OneCompAlternative to this | Open source | Named in the listing | Not dated |
| torchtitanAlternative to this | Open source | Named in the listing | Not dated |
Compare
Compare DeepSpeed side by side
Sources
Where this comes from
- GitHubOfficial
- github api via nightly crawl, recovered from git history 20e874270887c1008f860ee0198e461a23c9e438Registry
A source shows what was published when we checked it. It does not certify security, performance or a working installation. Read our method.
Changelog
What changed
Released 0.19.8
Released 0.19.7
Released 0.19.6
Released 0.19.5
Released 0.19.4
Released 0.19.3
Released 0.19.2
Released 0.19.1
Released 0.19.0
Released 0.18.9
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