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- 🤝 **OpenAI API服务与vLLM兼容**：单命令部署，兼容[vLLM](https://github.com/vllm-project/vllm/)接口
- 🧮 **全量化格式支持**：W8A16、W8A8、W4A16、W4A8、W2A16、FP8等
- ⏩ **高级加速技术**：推测解码、多令牌预测（MTP）及分块预填充
- 🖥️ **多硬件支持**：NVIDIA GPU、昆仑芯XPU、海光DCU、昇腾NPU、天数智芯GPU、燧原GCU、沐曦GPU、英特尔Gaudi等
- 🖥️ **多硬件支持**：NVIDIA GPU、昆仑芯XPU、海光DCU、天数智芯GPU、燧原GCU、沐曦GPU、英特尔Gaudi等
## 要求
@@ -61,8 +61,6 @@ FastDeploy 支持在**英伟达（NVIDIA）GPU**、**昆仑芯（Kunlunxin）XPU
- [沐曦 GPU](./docs/zh/get_started/installation/metax_gpu.md)
- [英特尔 Gaudi](./docs/zh/get_started/installation/intel_gaudi.md)
**注意:** 我们正在积极拓展硬件支持范围。目前，包括昇腾（Ascend）NPU 等其他硬件平台正在开发测试中。敬请关注更新！
## 入门指南
通过我们的文档了解如何使用 FastDeploy：

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- 🤝 **OpenAI API Server and vLLM Compatible**: One-command deployment with [vLLM](https://github.com/vllm-project/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, Intel Gaudi etc.
- 🖥️ **Multi-Hardware Support**: NVIDIA GPU, Kunlunxin XPU, Hygon DCU, Iluvatar GPU, Enflame GCU, MetaX GPU, Intel Gaudi etc.
## Requirements
@@ -59,8 +59,6 @@ FastDeploy supports inference deployment on **NVIDIA GPUs**, **Kunlunxin XPUs**,
- [MetaX GPU](./docs/get_started/installation/metax_gpu.md)
- [Intel Gaudi](./docs/get_started/installation/intel_gaudi.md)
**Note:** We are actively working on expanding hardware support. Additional hardware platforms including Ascend NPU are currently under development and testing. Stay tuned for updates!
## Get Started
Learn how to use FastDeploy through our documentation: