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Comparison

DeepSpeed vs surogate

Verdict

Pick DeepSpeed if decisions for DeepSpeed use are driven by its capacity to handle large models efficiently using techniques such as data parallelism, model parallelism, pipeline parallelism, and compression; pick surogate if surogate is a C++-based repository that accelerates training and fine-tuning for generative AI models using CUDA on NVIDIA GPUs.

Markdown twin · DeepSpeed alternatives · surogate alternatives

GraphCanon updated Sep 20, 2026

10views this month

DeepSpeed logo

DeepSpeed

deepspeedai/DeepSpeed

★ 43kpushed Sep 6, 2026
vs
surogate logo

surogate

invergent-ai/surogate

★ 813pushed Sep 19, 2026

Trust & integrity

SignalDeepSpeedsurogate
Maintenance
Very active (0d since push)
As of Sep 6, 2026 · github_public_v1
Very active (0d since push)
As of Sep 19, 2026 · github_public_v1
Provenance
Not a fork · Organization account
As of Sep 6, 2026 · github_public_v1
Not a fork · Organization account
As of Sep 19, 2026 · github_public_v1
OSV dependency advisories
No lockfile (source not queried)
As of Jul 11, 2026 · osv@v1
No lockfile (source not queried)
As of Jul 11, 2026 · osv@v1
deps.dev advisories
Not queried
deps.dev@v1
Not queried
deps.dev@v1
OpenSSF Scorecard
Not queried
openssf-scorecard@v1
Not queried
openssf-scorecard@v1
DeepSpeed trust reportsurogate trust reportTrust methodology

Tagline

DeepSpeed
Deep learning optimization library for efficient distributed training and inference
surogate
Training/Fine-tuning at the speed of light

Stars

DeepSpeed
43k
surogate
813

Forks

DeepSpeed
5.0k
surogate
10

Open issues

DeepSpeed
1.4k
surogate
6

Language

DeepSpeed
Python
surogate
C++

Adopt for

DeepSpeed
Decisions for DeepSpeed use are driven by its capacity to handle large models efficiently using techniques such as data parallelism, model parallelism, pipeline parallelism, and compression.
surogate
surogate is a C++-based repository that accelerates training and fine-tuning for generative AI models using CUDA on NVIDIA GPUs

Persona

DeepSpeed
-
surogate
-

Runtime

DeepSpeed
-
surogate
-

License

DeepSpeed
Apache-2.0
surogate
Apache-2.0

Last pushed

DeepSpeed
Sep 6, 2026
surogate
Sep 19, 2026

Categories

DeepSpeed
Inference & Serving, Model Training
surogate
Model Training

Trust and health

Open issues (now)

DeepSpeed
1.4k
surogate
6

Stars delta

DeepSpeed
+195 (30d)
surogate
+7 (30d)

Open issues delta

DeepSpeed
+77 (30d)
surogate
0 (30d)

Full report

DeepSpeed
Trust report
surogate
Trust report

Choose DeepSpeed if…

  • DeepSpeed is primarily Python; surogate is C++.
  • Tags unique to DeepSpeed: billion-parameters, compression, data-parallelism, gpu.
  • Also covers Inference & Serving.
  • - When training or inferring with PyTorch on large datasets or complex deep learning models (up to trillion parameters)

When NOT to use DeepSpeed

  • - When you are working in an environment that only supports CPU-based training without access to CUDA or ROCm compatible GPUs
  • - If your project's PyTorch version is less than 2.0, DeepSpeed may not support all of its features and optimizations effectively
GitHubDetails

Choose surogate if…

  • surogate is primarily C++; DeepSpeed is Python.
  • Tags unique to surogate: cuda, fine-tuning, generative-ai, llama.
  • When needing rapid training and fine-tuning capabilities for generative AI models that take full advantage of NVIDIA GPU acceleration via CUDA.

When NOT to use surogate

  • If working in an environment without access to NVIDIA GPUs, as surogate leverages CUDA for its speed optimizations specifically designed for these hardware configurations.
  • When looking to use a more accessible language like Python for training and fine-tuning, since surogate is based on C++ which may offer less ease-of-use.
GitHubDetails

Explore

DeepSpeed trust report →surogate trust report →Inference & Serving category →Model Training category →All comparisonsStack workflowsTrending tools

Sources

Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.

GitHub stars on cards: DeepSpeed 43k · surogate 813 (synced Sep 20, 2026).

Common questions

What is the difference between DeepSpeed and surogate?
DeepSpeed: Deep learning optimization library for efficient distributed training and inference. surogate: Training/Fine-tuning at the speed of light. See the comparison table for live GitHub stats and shared categories.
When should I choose DeepSpeed over surogate?
Choose DeepSpeed over surogate when DeepSpeed is primarily Python; surogate is C++; Tags unique to DeepSpeed: billion-parameters, compression, data-parallelism, gpu; Also covers Inference & Serving; - When training or inferring with PyTorch on large datasets or complex deep learning models (up to trillion parameters).
When should I choose surogate over DeepSpeed?
Choose surogate over DeepSpeed when surogate is primarily C++; DeepSpeed is Python; Tags unique to surogate: cuda, fine-tuning, generative-ai, llama; When needing rapid training and fine-tuning capabilities for generative AI models that take full advantage of NVIDIA GPU acceleration via CUDA.
When should I avoid DeepSpeed?
- When you are working in an environment that only supports CPU-based training without access to CUDA or ROCm compatible GPUs - If your project's PyTorch version is less than 2.0, DeepSpeed may not support all of its features and optimizations effectively
When should I avoid surogate?
If working in an environment without access to NVIDIA GPUs, as surogate leverages CUDA for its speed optimizations specifically designed for these hardware configurations. When looking to use a more accessible language like Python for training and fine-tuning, since surogate is based on C++ which may offer less ease-of-use.
Is DeepSpeed or surogate more popular on GitHub?
DeepSpeed has more GitHub stars (43,065 vs 813). Stars measure visibility, not whether either tool fits your constraints.
Are DeepSpeed and surogate open source?
Yes - both are open-source projects on GitHub (DeepSpeed: Apache-2.0, surogate: Apache-2.0).
Where can I find alternatives to DeepSpeed or surogate?
GraphCanon lists graph-backed alternatives at DeepSpeed alternatives and surogate alternatives (DeepSpeed markdown twin, surogate markdown twin), ranked by typed relationship edges rather than popularity votes.
Is there a machine-readable version of this comparison?
Yes. The markdown twin at this comparison mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers.
Which is better maintained, DeepSpeed or surogate?
DeepSpeed: Very active. surogate: Very active. Compare maintenance labels, days since push, and release cadence in the trust section below - stars alone do not measure maintenance.
Where are the full trust reports for DeepSpeed and surogate?
GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: DeepSpeed trust report; surogate trust report.

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