DeepSpeed
deepspeed.ai
Spec sheet
- Purpose
- DeepSpeed is a deep learning optimization library for distributed model training and inference.Read 4 Oct 2026 · github.com
- Intended users
- The project describes its audience as deep learning researchers and practitioners working on large-scale training and inference.Read 4 Oct 2026 · microsoft.com
- Integrations
- The site lists integrations with Hugging Face Transformers, Accelerate, PyTorch Lightning and MosaicML.Read 4 Oct 2026 · deepspeed.ai
- Security
- The repository links to a SECURITY file and identifies the project as Apache-2.0 licensed.Read 4 Oct 2026 · github.com
- Support
- The GitHub repository says DeepSpeed holds public office hours on the last Tuesday of each month.Read 4 Oct 2026 · github.com
- License
- The GitHub repository identifies DeepSpeed as an open-source project under the Apache-2.0 license.Read 4 Oct 2026 · github.com
- 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.Read 4 Oct 2026 · deepspeed.ai
- 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.Read 4 Oct 2026 · deepspeed.ai
- Inference
- DeepSpeed-Inference supports model parallelism, inference-customized kernels and model quantization for transformer-based PyTorch models.Read 4 Oct 2026 · deepspeed.ai
- Megatron compatibility
- DeepSpeed states that it is fully compatible with Megatron and supports combining its data parallelism with model parallelism.Read 4 Oct 2026 · deepspeed.ai
- Monitoring
- The DeepSpeed Monitor can log live training metrics to TensorBoard, WandB or CSV files.Read 4 Oct 2026 · deepspeed.ai
- PyTorch API
- DeepSpeed describes its API as a lightweight wrapper around PyTorch that manages distributed training, mixed precision, gradient accumulation and checkpoints.Read 4 Oct 2026 · deepspeed.ai
- Training
- Its training features include mixed precision, data, model and pipeline parallelism, and the ZeRO optimizer.Read 4 Oct 2026 · deepspeed.ai
- ZeRO memory optimization
- ZeRO partitions model states and gradients across data-parallel processes to reduce memory use.Read 4 Oct 2026 · deepspeed.ai
Plans and prices
DeepSpeed Free Open-source software library · Apache-2.0 license Read 4 Oct 2026 · github.com
Where Specifiction places it
- Deep Learning Software#12 of 358.0