Home/Compare/accelerate vs surogate

Comparison

accelerate vs surogate

Verdict

Pick accelerate if tool: accelerate; 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 · accelerate alternatives · surogate alternatives

GraphCanon updated 1d

accelerate logo

accelerate

huggingface/accelerate

9.8kpushed Jul 30, 2026
vs
surogate logo

surogate

invergent-ai/surogate

813pushed Aug 23, 2026

Trust & integrity

Signalacceleratesurogate
Maintenance
Very active (3d since push)
As of 3w · github_public_v1
Very active (1d since push)
As of 1d · github_public_v1
Provenance
Not a fork · Organization account
As of 3w · github_public_v1
Not a fork · Organization account
As of 1d · github_public_v1
OSV dependency advisories
No lockfile (source not queried)
As of 1mo · osv@v1
No lockfile (source not queried)
As of 1mo · 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

Tagline

accelerate
A tool for launching, training, and using PyTorch models with ease on various devices, configurations, including mixed precision support.
surogate
Training/Fine-tuning at the speed of light

Stars

accelerate
9.8k
surogate
813

Forks

accelerate
1.4k
surogate
8

Open issues

accelerate
105
surogate
7

Language

accelerate
Python
surogate
C++

Adopt for

accelerate
Tool: accelerate
surogate
surogate is a C++-based repository that accelerates training and fine-tuning for generative AI models using CUDA on NVIDIA GPUs

Persona

accelerate
-
surogate
-

Runtime

accelerate
-
surogate
-

License

accelerate
Apache-2.0
surogate
Apache-2.0

Last pushed

accelerate
Jul 30, 2026
surogate
Aug 23, 2026

Categories

accelerate
Inference & Serving, Model Training
surogate
Model Training

Trust and health

Days since push

accelerate
3d
surogate
1d

Open issues (now)

accelerate
105
surogate
7

Stars delta

accelerate
Unknown
surogate
+7 (30d)

Open issues delta

accelerate
Unknown
surogate
+1 (30d)

Full report

accelerate
Trust report
surogate
Trust report

Choose accelerate if…

  • accelerate is primarily Python; surogate is C++.
  • Tags unique to accelerate: deepspeed, fsdp, mixed precision, pytorch.
  • Also covers Inference & Serving.
  • Easy mixed-precision support for PyTorch models

When NOT to use accelerate

  • Non-PyTorch projects do not benefit from this tool
  • Doesnt offer advanced auto-tuning features for other frameworks like TensorFlow
  • Limited to Python environments compatible with PyTorch 1.10.0+

Choose surogate if…

  • surogate is primarily C++; accelerate is Python.
  • Tags unique to surogate: cuda, deep-learning, fine-tuning, generative-ai.
  • 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.

Explore

Sources

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

GitHub stars on cards: accelerate 9.8k · surogate 813 (synced Aug 3, 2026).

Common questions

What is the difference between accelerate and surogate?
accelerate: A tool for launching, training, and using PyTorch models with ease on various devices, configurations, including mixed precision support.. surogate: Training/Fine-tuning at the speed of light. See the comparison table for live GitHub stats and shared categories.
When should I choose accelerate over surogate?
Choose accelerate over surogate when accelerate is primarily Python; surogate is C++; Tags unique to accelerate: deepspeed, fsdp, mixed precision, pytorch; Also covers Inference & Serving; Easy mixed-precision support for PyTorch models.
When should I choose surogate over accelerate?
Choose surogate over accelerate when surogate is primarily C++; accelerate is Python; Tags unique to surogate: cuda, deep-learning, fine-tuning, generative-ai; 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 accelerate?
Non-PyTorch projects do not benefit from this tool Doesnt offer advanced auto-tuning features for other frameworks like TensorFlow Limited to Python environments compatible with PyTorch 1.10.0+
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 accelerate or surogate more popular on GitHub?
accelerate has more GitHub stars (9,803 vs 813). Stars measure visibility, not whether either tool fits your constraints.
Are accelerate and surogate open source?
Yes - both are open-source projects on GitHub (accelerate: Apache-2.0, surogate: Apache-2.0).
Where can I find alternatives to accelerate or surogate?
GraphCanon lists graph-backed alternatives at accelerate alternatives and surogate alternatives (accelerate 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, accelerate or surogate?
accelerate: 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 accelerate and surogate?
GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: accelerate trust report; surogate trust report.

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