Installation
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Quick Start
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Supported Models
[2025-07] 《FastDeploy2.0推理部署实测》专题活动已上线! 完成文心4.5系列开源模型的推理部署等任务，即可获得骨瓷马克杯等FastDeploy2.0官方周边及丰富奖金！?? 欢迎大家体验反馈～ ??报名地址 ??活动详情
[2025-07] The FastDeploy 2.0 Inference Deployment Challenge is now live! Complete the inference deployment task for the ERNIE 4.5 series open-source models to win official FastDeploy 2.0 merch and generous prizes! ?? You're welcome to try it out and share your feedback! ??Sign up here ??Event details
[2025-06] ?? Released FastDeploy v2.0: Supports inference and deployment for ERNIE 4.5. Furthermore, we open-source an industrial-grade PD disaggregation with context caching, dynamic role switching for effective resource utilization to further enhance inference performance for MoE models.
FastDeploy is an inference and deployment toolkit for large language models and visual language models based on PaddlePaddle. It delivers production-ready, out-of-the-box deployment solutions with core acceleration technologies:
- ?? Load-Balanced PD Disaggregation: Industrial-grade solution featuring context caching and dynamic instance role switching. Optimizes resource utilization while balancing SLO compliance and throughput.
- ?? Unified KV Cache Transmission: Lightweight high-performance transport library with intelligent NVLink/RDMA selection.
- ?? OpenAI API Server and vLLM Compatible: One-command deployment with vLLM interface compatibility.
- ?? Comprehensive Quantization Format Support: W8A16, W8A8, W4A16, W4A8, W2A16, FP8, and more.
- ? Advanced Acceleration Techniques: Speculative decoding, Multi-Token Prediction (MTP) and Chunked Prefill.
- ??? Multi-Hardware Support: NVIDIA GPU, Kunlunxin XPU, Hygon DCU, Ascend NPU, Iluvatar GPU, Enflame GCU, MetaX GPU etc.
- OS: Linux
- Python: 3.10 ~ 3.12
FastDeploy supports inference deployment on NVIDIA GPUs, Kunlunxin XPUs, Iluvatar GPUs, Enflame GCUs, and other hardware. For detailed installation instructions:
Note: We are actively working on expanding hardware support. Additional hardware platforms including Ascend NPU, Hygon DCU, and MetaX GPU are currently under development and testing. Stay tuned for updates!
Learn how to use FastDeploy through our documentation:
- 10-Minutes Quick Deployment
- ERNIE-4.5 Large Language Model Deployment
- ERNIE-4.5-VL Multimodal Model Deployment
- Offline Inference Development
- Online Service Deployment
- Full Supported Models List
- Optimal Deployment
| Model | Data Type | PD Disaggregation | Chunked Prefill | Prefix Caching | MTP | CUDA Graph | Maximum Context Length |
|---|---|---|---|---|---|---|---|
| ERNIE-4.5-300B-A47B | BF16/WINT4/WINT8/W4A8C8/WINT2/FP8 | ? | ? | ? | ?(WINT4) | WIP | 128K |
| ERNIE-4.5-300B-A47B-Base | BF16/WINT4/WINT8 | ? | ? | ? | ?(WINT4) | WIP | 128K |
| ERNIE-4.5-VL-424B-A47B | BF16/WINT4/WINT8 | WIP | ? | WIP | ? | WIP | 128K |
| ERNIE-4.5-VL-28B-A3B | BF16/WINT4/WINT8 | ? | ? | WIP | ? | WIP | 128K |
| ERNIE-4.5-21B-A3B | BF16/WINT4/WINT8/FP8 | ? | ? | ? | WIP | ? | 128K |
| ERNIE-4.5-21B-A3B-Base | BF16/WINT4/WINT8/FP8 | ? | ? | ? | WIP | ? | 128K |
| ERNIE-4.5-0.3B | BF16/WINT8/FP8 | ? | ? | ? | ? | ? | 128K |
FastDeploy is licensed under the Apache-2.0 open-source license. During development, portions of vLLM code were referenced and incorporated to maintain interface compatibility, for which we express our gratitude.