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Tools/DeepSpeed vs Beam
DeepSpeed

DeepSpeed

infrastructure
vs
Beam

Beam

infrastructure

DeepSpeed vs Beam — Comparison

Overview
What each tool does and who it's for

DeepSpeed

DeepSpeed is a deep learning optimization library that makes distributed training easy, efficient, and effective.

[2025/12] DeepSpeed Core API updates: PyTorch-style backward and low-precision master states [2025/10] SuperOffload: Unleashing the Power of Large-Scale LLM Training on Superchips [2025/10] Study of ZenFlow and ZeRO offload performance with DeepSpeed CPU core binding [2025/08] ZenFlow: Stall-Free Offloading Engine for LLM Training [2025/06] Arctic Long Sequence Training (ALST) with DeepSpeed: Scalable And Efficient Training For Multi-Million Token Sequences DeepSpeed has been used to train many different large-scale models. Below is a list of several examples that we are aware of (if you’d like to include your model please submit a PR): DeepSpeed has been integrated with several different popular open-source DL frameworks such as: DeepSpeed is an integral part of Microsoft’s AI at Scale initiative to enable next-generation AI capabilities at scale. DeepSpeed welcomes your contributions! Please see our contributing guide for more details on formatting, testing, etc. This project welcomes contributions and suggestions. Most contributions require you to agree to a Developer Certificate of Origin (DCO)[https://wiki.linuxfoundation.org/dco] stating that they agree to the terms published at https://developercertificate.org for that particular contribution. DCOs are per-commit, so each commit needs to be signed off. These can be signed in the commit by adding the -s flag. DCO enforcement can also be signed off in the PR itself by clicking on the DCO enforcement check. Xinyu Lian, Sam Ade Jacobs, Lev Kurilenko, Masahiro Tanaka, Stas Bekman, Olatunji Ruwase, Minjia Zhang. (2024) Universal Checkpointing: Efficient and Flexible Checkpointing for Large Scale Distributed Training arXiv:2406.18820

Beam

Run sandboxes, inference, and training with ultrafast boot times, instant autoscaling, and a developer experience that just works.

Run sandboxes, inference, and training with ultrafast boot times, instant autoscaling, and a developer experience that just works.

Key Metrics
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Avg Rating
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0
Mentions (30d)
0
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GitHub Stars
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GitHub Forks
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npm Downloads/wk
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PyPI Downloads/mo
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Community Sentiment
How developers feel about each tool based on mentions and reviews

DeepSpeed

0% positive100% neutral0% negative

Beam

0% positive100% neutral0% negative
Pricing

DeepSpeed

tiered

Beam

Features

Only in DeepSpeed (1)

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Developer Ecosystem
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GitHub Repos
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GitHub Followers
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20
npm Packages
20
40
HuggingFace Models
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SO Reputation
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Product Screenshots

DeepSpeed

No screenshots

Beam

Beam screenshot 1
Company Intel
design
Industry
information technology & services
1
Employees
4
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Funding
$3.6M
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Stage
Seed
Supported Languages & Categories

DeepSpeed

AI/MLDeveloper Tools

Beam

AImachine learningcloud computingGPUPython
View DeepSpeed Profile View Beam Profile