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GPU Server for 5 Concurrent LLM chatbot Users: Sizing Guide

How to size a GPU server for 5 concurrent llm chatbot users. VRAM requirements, recommended GPUs, and scaling guidance for LLM inference.

GPU Server for 5 Concurrent LLM chatbot Users: Sizing Guide

Hardware recommendations for running LLM inference with 5 simultaneous users on dedicated GPU servers.

Quick Recommendation

For 5 concurrent llm chatbot users, we recommend the RTX 4060 Ti (from £69/month) as the starting configuration. Budget-friendly for small teams.

Recommended GPU Configurations

GPUVRAMMonthly CostRecommended ModelsNotes
RTX 4060 Ti 16 GB £69/mo Mistral 7B / LLaMA 3 8B Budget-friendly for small teams
RTX 3090 24 GB £89/mo LLaMA 3 8B / Qwen 7B Best value with 24 GB VRAM

VRAM & Throughput Requirements

A 7B-parameter model in FP16 consumes 7–8 GB of VRAM. INT4 quantisation can squeeze 13B models into 8 GB or 70B models into 40 GB. For 5 concurrent users running a 7B model, a single 16 GB GPU handles the load comfortably — especially with continuous batching through vLLM or TGI keeping GPU utilisation high.

Sizing Considerations

Five concurrent users is a common starting point for internal tools and small-scale customer bots. Here is what to consider when choosing hardware:

  • Real vs. peak concurrency: 5 concurrent users rarely means 5 simultaneous GPU operations. Request queuing and batching keep actual utilisation around 40–60% of theoretical peak.
  • Response length: Short 200-token replies serve more users per second than 2,000-token responses. Profile your average output length to size accurately.
  • Latency targets: For real-time chat, aim for sub-200ms time-to-first-token. Batch or async workloads can tolerate higher queue depths.
  • Growth plan: If you expect to double users within months, start with the RTX 3090 for its larger VRAM buffer.

Scaling Strategy

A single GPU comfortably handles 5 chatbot users. As you approach 10 concurrent sessions, consider adding a second node behind a reverse proxy for horizontal scaling.

GigaGPU supports seamless multi-server deployments. Start with the minimum configuration and scale out as your user base grows.

Cost Comparison

Serving 5 concurrent llm chatbot users via API providers typically costs £225-600/month depending on usage volume. A dedicated GPU server at £69/month gives you predictable costs with no per-request fees.

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