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RTP-LLM is an open-source large language model inference acceleration engine developed by Alibaba to provide high-performance serving infrastructure for modern LLM deployments. The system focuses on improving throughput, latency, and resource utilization when running large models in production environments. It achieves this by implementing optimized GPU kernels, batching strategies, and memory management techniques tailored for transformer inference workloads. The framework is designed for large-scale AI services and is already used internally across several Alibaba platforms such as Taobao, Amap, and other business systems that rely on conversational or search-related AI services. RTP-LLM supports a wide variety of modern model architectures, including Qwen, DeepSeek, and Llama-based models, making it a flexible engine for deploying many different open-source LLMs.
Features
- High-performance inference engine designed for large language model serving
- Optimized GPU kernels including FlashAttention and FlashDecoding
- Support for multiple LLM families such as Qwen, DeepSeek, and Llama
- Continuous batching scheduler for improving throughput and latency
- Quantization techniques including INT8 and weight-only INT4
- Production deployment across multiple large-scale Alibaba AI services
Project Samples
