Unlock Faster LLM Inference: Full Stack of Chips, Frameworks & Services

1. Chip Layer

Chip layer is the physical foundation of compute systems, influencing compute density, energy efficiency, and parallelism. Major vendors include NVIDIA, AMD, Groq, and Chinese companies such as Alibaba's Pingtouge, Huawei Ascend, Cambricon, Moore Threads, Suirui Technology, Muxi Integration, and Biren.

These chips now provide DeepSeek compatibility, easing supply pressure.

2. Chip‑Targeted Programming Languages & SDKs

Programming interfaces like NVIDIA CUDA, AMD ROCm, Pingtouge HGAI, Ascend C, Cambricon BangC, Moore Threads MUSA, Suirui Tops Riser, Muxi MXMACA, and Biren SUPA enable efficient resource scheduling and instruction mapping, though switching languages can be costly.

3. General Deep‑Learning Frameworks

Frameworks such as PyTorch, TensorFlow, JAX, MindSpore, PaddlePaddle, MXNet, and Caffe simplify model development, training, and deployment, each with its own strengths and ecosystem.

4. LLM Inference Acceleration Layer

This layer optimizes compute efficiency and resource utilization through compilation, quantization, batching, etc. Vendors and open‑source projects include vLLM, TensorRT‑LLM, ONNX Runtime, TGI, DeepPyTorch Inference, BladeLLM, SiliconLLM, among others.

5. Large Model Layer

International models: OpenAI GPT, Google Gemini, Meta LLaMA, Anthropic Claude, Mistral AI, X‑Grok. Domestic models: Alibaba Cloud Qwen, DeepSeek, Baidu Wenxin, ByteDance Doubao, Tencent Cloud Hunyuan, iFlytek Spark, Kimi, etc., with several open‑source releases.

6. Compute Platform Layer

Relies on GPU resources, primarily provided by public cloud providers like Alibaba Cloud PAI, Bailei, Serverless GPU functions, container services, and GPU servers. Overseas vendors also offer dedicated inference services such as Groq, together.io, and Fireworks.ai.

7. Application Orchestration Layer

Tools like LangChain, LlamaIndex, Spring AI Alibaba, Dify, and Alibaba Cloud Bailei enable integration of models, tools, data, and services to build complex AI workflows, with both code‑centric and low‑code options.

8. Traffic Management Layer

Manages traffic, service, security, and APIs for LLM services, addressing challenges like long‑lived connections, high latency, large bandwidth, and protection against abuse. New‑generation gateways such as Higress, Kong AI Gateway, and Alibaba Cloud Native API Gateway are emerging to meet these needs.

Overall, understanding the full stack—from silicon to traffic—helps evaluate and select optimal solutions for accelerating large‑model inference.