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Apache SINGA

Free#17 of 35 in Deep Learning Software

Apache SINGA: A compact, free Python framework for neural networks and distributed training. Ranked #17 of 35 in Deep Learning Software by our editors (5.7/10); pricing: Free plan; best for teams seeking a compact Python neural-network framework.

5.7/10Editor score
Apache SINGA5.7 Visit Apache SINGA

At a glance

  • Editor score
    5.7 / 10
  • Pricing
    Free plan
  • Best for
    Teams seeking a compact Python neural-network framework
  • Free plan
    Yes
  • Paid from
    None
  • Training mode
    Local
  • Facts checked
    23 Sep 2026
  • Where it wins

    • Free, open-source framework with Python and C++ support
    • Automatic differentiation with SGD, Adam, RMSProp, and AdaGrad
    • Data-parallel training across multiple GPUs and nodes
  • Where it doesn't

    • Integration options center on ONNX and RDBMS
    • Deployment is self-hosted and focused on local or on-premises use
    • Verified integrations and workflow breadth are comparatively limited

Our verdict on Apache SINGA

Apache SINGA is an open-source deep-learning library for teams building, training, and running neural-network models. Its Python model and layer APIs support construction of neural networks, while C++ is also supported. The framework fits small, mid-market, and enterprise teams that want a compact, self-hosted tool for local or on-premises workloads across Linux, Windows, and macOS. CPU and CUDA-enabled GPU execution are supported, giving developers a choice of hardware for model development and operation.

SINGA is available as free open-source software rather than a tiered commercial product. The published installation options include pip, Docker, Conda, and source builds, so teams can align setup with their existing environment. Its ecosystem connections are focused: SINGA can load ONNX models for inference or retraining and export models created through its APIs to ONNX format; RDBMS is also listed as an integration. This makes it a practical fit for ONNX-centered workflows, while teams seeking a wider set of verified integrations may need to assess alternatives.

The standout capability is distributed training. SINGA supports data-parallel models across multiple GPUs and nodes, synchronizing distributed gradients with all-reduce. Automatic reverse-mode differentiation calculates gradients, and optimizers include SGD with momentum, Adam, RMSProp, and AdaGrad. Buffered-graph profiling exposes operator execution time for performance analysis. Documentation, examples, and community support are available for implementation and scaling. Choose SINGA when free licensing, Python APIs, GPU support, and distributed training are priorities; consider another framework if hosted deployment, broader workflow coverage, or a larger integration ecosystem matters more.

Apache SINGA pricing

Plans Free planFree Free to use — no paid tier required for the core job.
See plans on singa.apache.org

Apache SINGA fact sheet

Free planYes
Paid fromNone
Training modeLocal
Deployment targetsOn-prem
GPU accelerationYes
Distributed trainingYes
Supported languagesPython, C++
Model formatsONNX
DeploymentSelf-hosted
PlatformsLinux, Windows, macOS
SupportCommunity, Docs
Built forSmall business, Mid-market, Enterprise (editorial estimate)
Integrations2 integrations: ONNX, RDBMS
PricingFree plan
Websitesinga.apache.org
Facts checked23 Sep 2026

Apache SINGA integrations

Apache SINGA lists 2 integrations on its own site.

  • ONNX
  • RDBMS

Alternatives to Apache SINGA

See all Apache SINGA alternatives →

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Featured on iTechGuides

Featured on iTechGuides — Apache SINGA 5.7/10

Apache SINGA is listed in our Deep Learning Software directory. Add the badge to your site — it links back to this page.

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Reviewed by iTechGuides Editors · Editorial team · Updated Sep 2026

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