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Voice Agent Hosting

Self-Host ASR + LLM + TTS Voice Agent Pipelines — Sub-Second Latency, No Per-Call Fees

Deploy fully self-hosted voice agents on dedicated UK GPU servers. Run Whisper, an open source LLM, and a TTS model in a single low-latency loop — replacing stacked API fees from Twilio, ElevenLabs and OpenAI with flat monthly pricing and complete data privacy.

What is Voice Agent Hosting?

Voice agent hosting means running an entire conversational AI pipeline — speech-to-text (ASR), a large language model (LLM) for reasoning, and text-to-speech (TTS) for spoken output — on your own dedicated GPU server instead of chaining together multiple cloud APIs.

With a GigaGPU dedicated GPU server you get a full GPU card, NVMe storage, and bare metal UK infrastructure. Deploy Whisper for transcription, an open source LLM like Llama 3 or Mistral for reasoning, and Kokoro TTS or Chatterbox TTS for natural speech output — all on a single GPU with sub-second end-to-end latency.

Voice agents built on open source models are now production-ready. Teams are replacing stacked per-minute API costs from providers like Twilio, Deepgram, ElevenLabs, and OpenAI with a single flat-rate server that handles the entire pipeline privately.

3-in-1
ASR + LLM + TTS Pipeline
<1s
End-to-End Latency
UK
Server Location
Private
Single-Tenant Hardware
Fixed
Monthly Pricing
Root
Full Admin Access
NVMe
Fast Local Storage
1 Gbps
Network Port

Built for private voice agent hosting — not shared-cloud API queues.

The Voice Agent Pipeline

A voice agent combines three models in a real-time loop. All three run on a single GPU server — no external API calls, no stacked latency.

1. ASR

Whisper / Faster-Whisper converts caller speech to text in real time

2. LLM

Llama 3, Mistral, or Qwen reasons over the transcript and generates a response

3. TTS

Kokoro TTS, Chatterbox, or XTTS-v2 speaks the response back to the caller

Loop

The cycle repeats — continuous conversation in real time

Models for Voice Agent Pipelines

Mix and match ASR, LLM, and TTS models to build the voice agent stack that fits your use case. All run on a single GigaGPU dedicated server.

Speech-to-Text (ASR)

Whisper Large v3
OpenAI (open-weight)
ASRMultilingual
Whisper Turbo
OpenAI (open-weight)
ASRLow Latency
Faster-Whisper
SYSTRAN
ASROptimisedStreaming
Distil-Whisper
Hugging Face
ASRFastLightweight

Large Language Models (LLM)

Llama 3.1 8B
Meta
LLMFastVersatile
Mistral 7B
Mistral AI
LLMEfficient
Qwen 2.5 7B
Alibaba
LLMMultilingual
Gemma 2 9B
Google
LLMCompact

Text-to-Speech (TTS)

Kokoro TTS
Open Source
TTSFastLightweight
Chatterbox TTS
Open Source
TTSVoice CloningRealtime
XTTS-v2
Coqui
TTSVoice CloningMultilingual
F5-TTS
Open Source
TTSNatural Speech

Any combination of ASR + LLM + TTS models can be deployed depending on GPU memory and latency targets. See Speech Model Hosting for the full speech model list, and Open Source LLM Hosting for all supported LLMs.

Best GPUs for Voice Agents

Voice agent stacks need enough VRAM to fit ASR + LLM + TTS simultaneously, and enough compute for sub-second latency. Here are our top picks.

RTX 3090
24 GB VRAM
Best Value Voice Agent

24GB Ampere fits Faster-Whisper (~3GB) + a 7B LLM at Q4 (~6GB) + Kokoro TTS (~1GB) comfortably. The go-to GPU for teams deploying their first production voice agent on a budget.

Whisper + 7B LLM + TTSVoice Agent Dev
Configure RTX 3090 →
RTX 5090
32 GB VRAM
Lowest Latency

Blackwell 2.0 delivers the fastest end-to-end voice agent loop. 32GB GDDR7 fits a 13B LLM alongside ASR and TTS with headroom for concurrent callers. The best choice for production telephony.

Sub-Second LatencyProduction Telephony
Configure RTX 5090 →
Ryzen AI MAX+ 395
96 GB Unified
Maximum Model Size

96GB unified memory lets you run a 70B LLM alongside Whisper and TTS — ideal for voice agents that need the most capable reasoning model available, such as complex customer support or advisory bots.

70B LLM + ASR + TTSComplex Reasoning
Configure Ryzen AI MAX+ →

Voice Agent Hosting Pricing

Fixed monthly pricing for the full GPU. No per-minute fees, no stacked API charges. Voice agent stacks typically need 24GB+ VRAM — but lighter pipelines can start on 16GB.

RTX 3050 · 6GBStarter
ArchitectureAmpere
VRAM6 GB GDDR6
FP326.77 TFLOPS
BusPCIe 4.0 x8
6GB
ASR-only or lightweight TTSNot recommended for full pipeline
From £69.00/mo
Configure
RTX 4060 · 8GBEntry
ArchitectureAda Lovelace
VRAM8 GB GDDR6
FP3215.11 TFLOPS
BusPCIe 4.0 x8
8GB
minimal agent stackWhisper + small LLM + Piper
From £79.00/mo
Configure
RTX 5060 · 8GBBudget
ArchitectureBlackwell 2.0
VRAM8 GB GDDR7
FP3219.18 TFLOPS
BusPCIe 5.0 x8
8GB
minimal agent stackGDDR7 bandwidth helps latency
From £89.00/mo
Configure
RTX 4060 Ti · 16GBDev Agent
ArchitectureAda Lovelace
VRAM16 GB GDDR6
FP3222.06 TFLOPS
BusPCIe 4.0 x8
16GB
development agent stackWhisper + 7B Q4 + Kokoro TTS
From £99.00/mo
Configure
RX 9070 XT · 16GBAMD RDNA 4
ArchitectureRDNA 4.0
VRAM16 GB GDDR6
FP3248.66 TFLOPS
BusPCIe 5.0 x16
16GB
AMD agent stackROCm ready for voice pipelines
From £129.00/mo
Configure
Arc Pro B70 · 32GBNew
ArchitectureXe2
VRAM32 GB GDDR6
FP3222.9 TFLOPS
BusPCIe 5.0 x16
32GB
VRAM headroom13B LLM + ASR + TTS pipeline
From £179.00/mo
Configure
RTX 5080 · 16GBHigh Speed
ArchitectureBlackwell 2.0
VRAM16 GB GDDR7
FP3256.28 TFLOPS
BusPCIe 5.0 x16
16GB
fast compact pipelineBlackwell speed for small stacks
From £189.00/mo
Configure
Radeon AI Pro R9700 · 32GBAI Pro
ArchitectureRDNA 4
VRAM32 GB GDDR6
FP3247.84 TFLOPS
BusPCIe 5.0 x16
32GB
full agent pipeline13B LLM + multi-model stack
From £199.00/mo
Configure
Ryzen AI MAX+ 395 · 96GBNew
ArchitectureStrix Halo
Unified RAM96 GB LPDDR5X
FP3214.8 TFLOPS
BusPCIe 4.0
96GB
70B LLM + full pipelineMaximum reasoning capability
From £209.00/mo
Configure
RTX 6000 PRO · 96GBEnterprise
ArchitectureBlackwell 2.0
VRAM96 GB GDDR7
FP32125.2 TFLOPS
BusPCIe 5.0 x16
96GB
enterprise voice agent70B LLM + multi-agent + ASR + TTS
From £749.00/mo
Configure

Voice Agent Costs: Stacked APIs vs Self-Hosted

Most voice agent providers charge per minute across every layer — ASR, LLM, and TTS fees stack up fast. A self-hosted GPU replaces all three with a single flat monthly rate.

Stacked API Pricing

Per-minute fees on every layer — costs multiply per call
Deepgram ASR~$0.0043 / min
OpenAI GPT-4o mini~$0.01–0.03 / call
ElevenLabs TTS~$0.30 / 1k chars
Twilio / SIP trunk~$0.01 / min
10,000 calls/month (3 min avg)$500–$2,000+

Self-Hosted GPU

Fixed monthly rate — unlimited calls, zero API fees
RTX 3090 · Full pipelineFixed/mo
RTX 5090 · Production agentFixed/mo
ASR + LLM + TTS included£0 extra
SIP trunk only (bring your own)~$0.005 / min
10,000 calls/month (3 min avg)Same flat rate

Example: 10,000 Voice Agent Calls/Month (3 min avg)

Stacked API route: 30,000 minutes across ASR + LLM + TTS layers. Depending on providers and models, this costs $500–$2,000+/month — and scales linearly with every additional call.
Self-hosted route: A dedicated RTX 3090 or RTX 5090 runs the entire pipeline at a fixed monthly rate. Handle 10,000 or 100,000 calls — the cost doesn’t change.
Privacy bonus: Call audio and transcripts never leave your server. Essential for healthcare, legal, financial, and customer service voice agents where data residency matters.

API cost estimates are based on publicly listed pricing at time of writing and are indicative only. Actual savings depend on call volume, model choices, and provider tiers. GPU server prices retrieved live from the GigaGPU portal.

Why Self-Host Voice Agents Instead of Using APIs?

Stacking third-party APIs for ASR, LLM, and TTS creates compounding costs, latency, and data exposure. Self-hosting the full pipeline on one GPU eliminates all three.

Eliminate Stacked Per-Minute Fees

Cloud voice agents charge per minute on every API layer — ASR, LLM, and TTS fees compound on every call. A dedicated GPU runs the entire pipeline for a flat monthly rate regardless of call volume.

Lower End-to-End Latency

Every external API hop adds 100–300ms of round-trip latency. Running ASR → LLM → TTS on the same GPU eliminates network hops entirely, achieving sub-second response times for natural conversation flow.

Complete Data Privacy

Call audio, transcripts, and conversation logs never leave your server. No third-party data processing agreements needed. Essential for healthcare, legal, financial services, and any industry with strict data residency requirements.

Full Pipeline Control

Choose your own ASR model, LLM, TTS voice, and orchestration framework. Swap components, fine-tune models, adjust prompts, and customise voices without vendor lock-in or API limitations.

Predictable Scaling

API costs scale linearly with every call — budgets become unpredictable. With a dedicated GPU, scaling means adding another server at a known monthly cost, not watching per-minute charges multiply.

No Vendor Dependency

If your ASR, LLM, or TTS provider changes pricing, rate limits, or discontinues a model, your voice agent breaks. Self-hosting gives you complete independence from third-party roadmaps and outages.

Voice Agent Use Cases

From customer support bots to healthcare triage — dedicated GPU servers power every type of voice agent deployment.

Customer Support Voice Bots

Handle enquiries, bookings, returns, and FAQs with a self-hosted voice agent that runs 24/7. Combine Whisper for ASR, an open source LLM for reasoning, and Kokoro TTS for natural-sounding responses — with no per-call API fees.

Telephony & IVR Automation

Replace rigid IVR phone trees with intelligent voice agents that understand natural language. Route calls, collect information, and resolve issues — all powered by your own GPU with sub-second latency.

Appointment Scheduling Agents

Automate appointment booking, rescheduling, and reminders by voice. The LLM checks availability, handles conversational back-and-forth, and confirms bookings — running entirely on private infrastructure.

Healthcare Triage & Patient Intake

Deploy privacy-focused voice agents that handle patient intake, symptom screening, and appointment triage. Call audio and health data stay on your server — never processed by a third-party API.

Real Estate & Property Enquiries

Let potential buyers and tenants call in, ask questions about listings, schedule viewings, and get property details — all handled by a voice agent connected to your property database.

Legal Intake & Client Screening

Automate initial client intake calls for law firms. Collect case details, screen for conflicts, and route qualified leads — with all call data and transcripts kept on private UK infrastructure.

Order Tracking & E-Commerce

Let customers check order status, process returns, and get product recommendations by voice. Integrate with your order management system via API for real-time responses at no per-call cost.

Multilingual Voice Agents

Serve customers in 50+ languages using multilingual ASR (Whisper) and TTS (XTTS-v2) models. Deploy a single voice agent that handles English, Spanish, French, German, and more from one GPU.

Deploy a Voice Agent in 4 Steps

From order to live voice agent in under an hour. Full root access means you control the entire stack.

01

Choose a GPU

Pick a server with enough VRAM for your pipeline. 24GB (RTX 3090) is the sweet spot for most voice agents; 32GB (RTX 5090) for production telephony.

02

Install Your Models

SSH in and install your ASR, LLM, and TTS models. Use pip install faster-whisper, ollama pull llama3, and your chosen TTS framework.

03

Wire the Pipeline

Connect ASR → LLM → TTS in a loop using a framework like LiveKit, Pipecat, or your own FastAPI orchestration. Expose a WebSocket or SIP endpoint.

04

Connect & Go Live

Point your SIP trunk, Twilio number, or web client at your server. Your voice agent is live — handling calls on your own private infrastructure.

Compatible Frameworks & Platforms

Every GigaGPU server ships with full root access — install any voice agent framework in minutes.

Voice Agent Hosting FAQ

Common questions about self-hosting voice agents on dedicated GPU servers.

A voice agent is an AI system that holds real-time spoken conversations. It combines three models in a loop: speech-to-text (ASR) to understand the caller, a large language model (LLM) to reason and generate a response, and text-to-speech (TTS) to speak the response back. Self-hosting means running all three on your own dedicated GPU server.
A typical voice agent pipeline uses: Faster-Whisper (~3–4GB), a 7B LLM at Q4 quantisation (~6–8GB), and Kokoro TTS or MeloTTS (~1–2GB). That totals ~10–14GB, making 24GB (RTX 3090) the minimum recommended for comfortable production use. For a 13B LLM or higher concurrency, 32GB (RTX 5090) gives more headroom. For 70B LLMs, the 96GB Ryzen AI MAX+ 395 or RTX 6000 PRO is needed.
Yes. Running all three models on the same GPU eliminates the 100–300ms network round-trip per API call that stacked cloud services add. On an RTX 5090, a well-optimised pipeline (Faster-Whisper + 7B LLM via vLLM + Kokoro TTS) can achieve ~500–800ms end-to-end response time — comparable to or faster than cloud voice agent platforms.
Popular open source voice agent frameworks include LiveKit Agents, Pipecat, and Vocode. These handle the orchestration loop (ASR → LLM → TTS), WebSocket/SIP connectivity, and turn-taking logic. You can also build a custom pipeline using FastAPI with Faster-Whisper, Ollama or vLLM, and your chosen TTS model.
You connect a SIP trunk (from providers like Twilio, Telnyx, or VoIP.ms) to your voice agent server. The SIP trunk routes incoming calls to your server’s IP address, where your voice agent pipeline picks up the audio stream. Frameworks like LiveKit and Pipecat have built-in SIP support. Twilio’s media streams can also forward audio via WebSocket.
Yes, but concurrency depends on VRAM and compute. A 24GB RTX 3090 can typically handle 2–5 concurrent calls with a 7B LLM pipeline. A 32GB RTX 5090 with its higher throughput can handle more. For high-volume call centres (50+ concurrent calls), you would deploy multiple GPU servers behind a load balancer.
Yes — self-hosting is often the preferred approach for regulated industries. Call audio, transcripts, and patient/client data never leave your server. There are no third-party data processing agreements to manage, no data leaving the UK, and no risk of audio being used to train external models. GigaGPU servers are single-tenant bare metal machines in UK data centres.
Managed voice agent platforms like Bland AI, Vapi, and Retell charge per minute and handle infrastructure for you. Self-hosting on a GigaGPU server gives you a flat monthly rate (no per-minute fees), complete data privacy, full model control, and the ability to customise every component. The trade-off is you manage the pipeline yourself — but frameworks like LiveKit and Pipecat make this straightforward.
For voice agents, inference speed matters more than raw capability — the LLM needs to generate responses in under ~500ms. Models like Llama 3.1 8B, Mistral 7B, and Qwen 2.5 7B at Q4 quantisation run fast on 24GB GPUs via vLLM or Ollama. For more complex reasoning, a 13B–33B model on 32GB+ VRAM is the next step up.
Yes. Models like XTTS-v2 and Chatterbox TTS support voice cloning from short reference audio clips. You can give your voice agent a custom brand voice or a specific speaker’s voice — all running privately on your own hardware with no voice data sent to a third party.

Available on all servers

  • 1Gbps Port
  • NVMe Storage
  • 128GB DDR4/DDR5
  • Any OS
  • 99.9% Uptime
  • Root/Admin Access

Our dedicated GPU servers provide full hardware resources and a dedicated GPU card, ensuring unmatched performance and privacy. Perfect for self-hosting voice agent pipelines, telephony AI, conversational bots, and any real-time speech AI workload — with no shared resources and no per-minute fees.

Get in Touch

Have questions about which GPU is right for your voice agent workload? Our team can help you choose the right configuration for your pipeline, concurrency needs, and budget.

Contact Sales →

Or browse the knowledgebase for setup guides on voice agent frameworks, speech models, and more.

Start Hosting Your Voice Agent Today

Flat monthly pricing. Full GPU resources. UK data centre. Deploy a complete ASR + LLM + TTS voice agent pipeline in under an hour.

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