GPU Server for 50 Concurrent Voice agent Users: Sizing Guide
Hardware recommendations for running real-time STT + TTS pipeline with 50 simultaneous users on dedicated GPU servers.
50 Simultaneous Conversations at £109/month
Fifty concurrent voice agents is where most startups hit their first major API billing shock. ElevenLabs, Whisper API, and an LLM provider combined easily reach £2,250-£6,000/month. A single RTX 5080 handles the same workload for £109/month because all three pipeline stages run locally on one card, eliminating per-minute charges entirely.
Server Configurations
| GPU | VRAM | Monthly Cost | Recommended Models | Notes |
|---|---|---|---|---|
| RTX 5080 | 16 GB | £109/mo | Whisper + XTTS concurrent | Low-latency voice pipeline |
| RTX 5090 | 32 GB | £179/mo | Full pipeline: STT + LLM + TTS | All-in-one voice agent |
Pipeline Memory at 50 Streams
The full voice stack needs 10-16 GB: Whisper Large (~3 GB), your LLM (4-8 GB), and a TTS model (2-4 GB). At 50 concurrent users, the maths works because voice conversations are bursty by nature. At any given second, perhaps 15-20 users are actively generating speech or waiting for a response. The rest are listening, thinking, or in mid-sentence. The GPU handles 15-20 active inference tasks efficiently.
Maintaining sub-500ms end-to-end latency at 50 users is achievable on a single GPU with smart scheduling. Priority goes to STT (because silence feels unresponsive), then TTS, then LLM generation.
Optimising for 50 Users
- Multi-GPU consideration: At 50 users, you are at the boundary where a second GPU adds meaningful headroom. Two RTX 5080 nodes at £218/month give you redundancy and halve peak load per card.
- Whisper batching: Batch short audio chunks from multiple users into a single Whisper forward pass. This is more efficient than processing streams individually.
- Response caching: If your voice agent handles FAQs, cache common LLM responses. A 20% cache hit rate significantly reduces GPU pressure during peak hours.
- Graceful degradation: Under extreme load, switch from Whisper Large to Whisper Medium. The accuracy difference is minimal, but inference speed nearly doubles.
Building Toward 100 Users
A multi-GPU setup is the recommended architecture at 50 users. Deploy two GPUs with session affinity — each user’s entire conversation stays on one node to maintain context efficiently. Use load balancing to distribute new connections to the node with fewer active sessions.
GigaGPU supports multi-server deployments natively. Scale your voice platform incrementally as call volume grows.
The API Savings at Scale
50 concurrent voice users on APIs costs £2,250-£6,000/month. A dedicated RTX 5080 at £109/month delivers the same capability. Annual savings: £25,692-£70,692. For many voice-first startups, this is the difference between burning runway and reaching profitability.
Scale Your Voice Infrastructure
50 concurrent voice agents on dedicated hardware. Flat £109/month with sub-500ms latency and no per-call charges.
