Tech riderRev. 4 Oct 2026
DeepSpeed
- 1Runs onLinux, Mac, self-hosted
- 2CostsFree plan
- 3Training modelocal
- 4Deployment targetsmultiple
- 5GPU accelerationYes
- 6Distributed trainingYes
- 7Supported languagesPython
7 lines stated Written from the maker's own pages: deepspeed.ai, github.com
Overview
DeepSpeed is ranked #13 of 36 in deep learning software on Specifiction. It runs on Linux, macOS, Self-hosted. There is a free plan.
DeepSpeed plans and pricing
All plansCompared on deep learning software
- Free plan
- Yesdeepspeed.ai
- Training mode
- localdeepspeed.ai
- Deployment targets
- multipledeepspeed.ai
- GPU acceleration
- Yesdeepspeed.ai
- Distributed training
- Yesdeepspeed.ai
- Supported languages
- Pythondeepspeed.ai
Facts
- Purpose
- DeepSpeed is a deep learning optimization library for distributed model training and inference.github.com · 4 Oct 2026
- Training
- Its training features include mixed precision, data, model and pipeline parallelism, and the ZeRO optimizer.deepspeed.ai · 4 Oct 2026
- Inference
- DeepSpeed-Inference supports model parallelism, inference-customized kernels and model quantization for transformer-based PyTorch models.deepspeed.ai · 4 Oct 2026
- PyTorch API
- DeepSpeed describes its API as a lightweight wrapper around PyTorch that manages distributed training, mixed precision, gradient accumulation and checkpoints.deepspeed.ai · 4 Oct 2026
- Integrations
- The site lists integrations with Hugging Face Transformers, Accelerate, PyTorch Lightning and MosaicML.deepspeed.ai · 4 Oct 2026
- Megatron compatibility
- DeepSpeed states that it is fully compatible with Megatron and supports combining its data parallelism with model parallelism.deepspeed.ai · 4 Oct 2026
- 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.deepspeed.ai · 4 Oct 2026
- ZeRO memory optimization
- ZeRO partitions model states and gradients across data-parallel processes to reduce memory use.deepspeed.ai · 4 Oct 2026
- 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.deepspeed.ai · 4 Oct 2026
- Monitoring
- The DeepSpeed Monitor can log live training metrics to TensorBoard, WandB or CSV files.deepspeed.ai · 4 Oct 2026
- Intended users
- The project describes its audience as deep learning researchers and practitioners working on large-scale training and inference.microsoft.com · 4 Oct 2026
- Support
- The GitHub repository says DeepSpeed holds public office hours on the last Tuesday of each month.github.com · 4 Oct 2026
- Security
- The repository links to a SECURITY file and identifies the project as Apache-2.0 licensed.github.com · 4 Oct 2026
- License
- The GitHub repository identifies DeepSpeed as an open-source project under the Apache-2.0 license.github.com · 4 Oct 2026
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Where it ranks on Specifiction
- Best Deep Learning Software in 2026#13 of 36
Is DeepSpeed yours?
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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