Evidence tier Source Confirmed · 9 captures on record
What the publisher says
As described on Microsoft Marketplace.
FastDeploy is a high-performance inference deployment framework developed for efficient AI/ML model inference. It optimizes models for CPU, GPU, and edge devices, providing fast and reliable predictions. FastDeploy is designed to support a variety of machine learning tasks, making it suitable for both research and production environments.
Features of FastDeploy:
Show the rest of the publisher’s description (15 more lines)
- Optimized for multiple model formats including ONNX, TensorRT, Paddle, PyTorch, and TensorFlow.
- Supports computer vision tasks such as image classification, object detection, and segmentation.
- Enables NLP tasks like text classification, named entity recognition, and question answering.
- Provides Python and C++ APIs for easy integration into applications.
- Efficient CPU and GPU inference using backend optimizations like TensorRT and OpenVINO.
- Can be deployed on servers, cloud platforms, and edge devices for production-ready solutions.
- Supports model quantization and acceleration to reduce latency and memory usage.
- State-of-the-art performance on benchmarks and real-world applications.
To check the version of FastDeploy Python package:
# sudo su
# cd /opt
# source fastdeploy-py313/bin/activate
# source venv/bin/activate
# pip show fastdeploy-python
Disclaimer: FastDeploy is an open-source software provided by PaddlePaddle. It is provided "as is," without any warranty, express or implied. Users utilize this software at their own risk. The developers and contributors are not responsible for any damages, losses, or consequences resulting from the use of this software. Users are encouraged to review and comply with licensing terms and any applicable regulations when using FastDeploy.
Agent build and provenance
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The layer-by-layer build, the evidence behind each claim, the risk basis and the cross-marketplace links are open to any account. Some rows are disclosed, some the source leaves Unknown; a free account shows you which.
Compliance
- FedRAMPConfirmedNot listed90%, registry-checkedNo FedRAMP Marketplace entry matched this vendor's domain, checked 2026-08-27registry recordas observed 2026-08-27
Confirmed means matched to a public authoritative registry. Claimed means the vendor or its listing states it, not yet cross-checked. A framework not shown was not found in any source we hold, which is not evidence against it. Not listed means a scoped registry check found no match for this vendor's domain: a No is a scoped registry check, not a compliance judgment. Confidence bands: 95% domain-verified, 90% registry-checked, 80% self-attested, 70% weak signal. Self-attested items marked “vendor's site” are gathered from the vendor's own website and are not verified by us.
Vendor
External enrichment · as of 2026-08-29
Sources
Publisher resources
1 linkLinked repositories
Unknown means this listing does not publish a repository. It is not a statement that the code is closed, and a linked repository is not a claim that the publisher wrote it: the registry computes that relationship privately and does not publish it.
Evidence risk is the share of the build you cannot see before you deploy, not a security rating. Sign in to see the layer-by-layer basis for this band.