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Caffe

Caffe: a fast open framework for deep learning.

Our verdict

Not reviewed yet

We have not reviewed Caffe yet

No one at Enterprise DNA has checked this listing against its sources. The description comes from public listings gathered automatically. Any fact below shows where it came from and when it was last checked.

How we review records

From the listing

About Caffe

Caffe is an open-source deep learning framework written in C++ that prioritizes speed and efficiency for training and deploying neural networks. It provides a modular architecture with support for CPU and GPU computation, commonly used for image classification, object detection, and computer vision tasks.

Best for

Teams building production computer vision systems who prioritize inference speed and have existing Caffe expertise

Use cases

  • Training convolutional neural networks for image recognition at scale
  • Deploying trained models in production with minimal latency
  • Prototyping deep learning architectures with pre-built layer definitions

Notes

34,585 stars on GitHub. Last updated 2024-07-31.

Pros

  • Fast inference and training performance, especially on GPUs
  • Lightweight and efficient for production deployment
  • Mature ecosystem with extensive pre-trained models available

Cons

  • Steeper learning curve compared to modern frameworks like PyTorch or TensorFlow
  • Less active development and community support than contemporary alternatives
  • Limited built-in support for dynamic computation graphs and recurrent architectures

Key facts

What we have checked

Latest version
1.0 (released 18 Apr 2017)
Checked GitHub
GitHub stars
34,552
Checked github api via nightly crawl, recovered from git history 20e874270887c1008f860ee0198e461a23c9e438

Each value shows when we last confirmed it and where it came from. Values we have not confirmed are left out, never guessed.

Stars and usage

How Caffe is growing

GitHub stars

34,585 to 34,552

stars. 12 July 2026 to 26 Sept 2026, 2 readings.

Source: github api via nightly crawl, recovered from git history 20e874270887c1008f860ee0198e461a23c9e438. Checked .

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PaddlePaddleAlternative to thisOpen sourceNamed in the listingNot dated
PyTorchAlternative to thisOpen sourceNamed in the listingNot dated
TensorFlowAlternative to thisOpen sourceNamed in the listingNot dated
VectorFlowAlternative to thisOpen sourceNamed in the listingNot dated
KerasThis is an alternative to itOpen sourceNamed in the listingNot dated

Compare

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Sources

Where this comes from

  • GitHubOfficial

    Checked · Latest version

  • github api via nightly crawl, recovered from git history 20e874270887c1008f860ee0198e461a23c9e438Registry

    Checked · GitHub stars

A source shows what was published when we checked it. It does not certify security, performance or a working installation. Read our method.

Changelog

What changed

  1. Released 1.0

    Source: GitHub

  2. Released rc5

    Source: GitHub

  3. Released rc4

    Source: GitHub

  4. Released rc3

    Source: GitHub

  5. Released rc2

    Source: GitHub

  6. Released rc

    Source: GitHub

  7. Released 0.9999

    Source: GitHub

  8. Released acm-mm-oss

    Source: GitHub

  9. Released 0.999

    Source: GitHub

  10. Released 0.99

    Source: GitHub

Open-source & AI alternatives

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Alternatives8 entries

Pairs with

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