Node.js and vLLM achieve 50ms LLM inference latency on RTX 4090

A developer shares a simplified approach to LLM inference using Node.js and vLLM, aiming for high throughput and low latency. This method bypasses complex serving stacks, leveraging Node.js for API gateway functions and vLLM for optimized inference on GPUs. The author reports achieving 50ms P95 latency with 100 concurrent requests on an RTX 4090 using a Llama-2-7B model, and notes a 25% cost saving compared to Hugging Face's Text Generation Inference due to vLLM's efficient GPU utilization. AI

IMPACT Simplifies LLM deployment for developers, potentially reducing costs and improving user experience through lower latency.

RANK_REASON Developer shares a practical implementation of LLM inference using specific technologies.

Read on dev.to — LLM tag →

• Claude
• FarahGPT
• Hugging Face
• Llama-2-7B-chat-hf
• LLM
• Node.js
• OpenAI
• RTX 4090
• Text Generation Inference
• vLLM

• infra
• product

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