DeepSpeed

DeepSpeed is ranked #10 of 35 in deep learning software on The Geeks Club. It runs on Linux, macOS, Self-hosted. There is a free plan.

DeepSpeed plans and pricing

All plans

DeepSpeed Free Open-source software library · Apache-2.0 license github.com · 4 Oct 2026

Compared on deep learning software

Free plan: Yes
Training mode: local
Deployment targets: multiple
GPU acceleration: Yes
Distributed training: Yes
Supported languages: Python

Best DeepSpeed alternatives

See all 12

7.6 ONNX Runtime Free plan

7.5 Amazon SageMaker Autopilot Free trial

7.5 Paperspace Gradient Free plan

7.4 Apache TVM Free plan

7.4 MATLAB Grader Free plan

7.2 TensorFlow Free plan

DeepSpeed

Purpose: DeepSpeed is a deep learning optimization library for distributed model training and inference.
Training: Its training features include mixed precision, data, model and pipeline parallelism, and the ZeRO optimizer.
Inference: DeepSpeed-Inference supports model parallelism, inference-customized kernels and model quantization for transformer-based PyTorch models.
PyTorch API: DeepSpeed describes its API as a lightweight wrapper around PyTorch that manages distributed training, mixed precision, gradient accumulation and checkpoints.
Integrations: The site lists integrations with Hugging Face Transformers, Accelerate, PyTorch Lightning and MosaicML.
Megatron compatibility: DeepSpeed states that it is fully compatible with Megatron and supports combining its data parallelism with model parallelism.
Accelerators: The getting-started guide names AMD ROCm, Intel Xeon CPU, Intel Data Center Max Series XPU, Intel Gaudi HPU and Huawei Ascend NPU support.
ZeRO memory optimization: ZeRO partitions model states and gradients across data-parallel processes to reduce memory use.
Data efficiency: The Data Efficiency Library uses curriculum learning and random layerwise token dropping, with the site reporting up to 2x data and time savings for specified workloads.
Monitoring: The DeepSpeed Monitor can log live training metrics to TensorBoard, WandB or CSV files.
Intended users: The project describes its audience as deep learning researchers and practitioners working on large-scale training and inference.
Support: The GitHub repository says DeepSpeed holds public office hours on the last Tuesday of each month.
Security: The repository links to a SECURITY file and identifies the project as Apache-2.0 licensed.
License: The GitHub repository identifies DeepSpeed as an open-source project under the Apache-2.0 license.
Price from: Free

Visit site Alternatives

Where it ranks on The Geeks Club

Best Deep Learning Software in 2026#10 of 35

Is DeepSpeed yours?

Claim it for free: prove the domain, then correct facts, plans and screenshots. An editor reviews every change.

Claim it free Promote DeepSpeed

Sources

github.com/deepspeedai/DeepSpeed· checked 4 Oct 2026
deepspeed.ai/training/· checked 4 Oct 2026
deepspeed.ai/inference/· checked 4 Oct 2026
deepspeed.ai· checked 4 Oct 2026
deepspeed.ai/getting-started/· checked 4 Oct 2026
microsoft.com/en-us/research/project/deepspeed/· checked 4 Oct 2026