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AI Chatbot Hosting

Self-Host AI Chatbots & Conversational Agents on Dedicated GPU Servers — No Per-Token Fees

Deploy private AI chatbots powered by open source LLMs on dedicated UK GPU servers. Replace ChatGPT API, Claude API, or Gemini API with fixed monthly pricing, full data privacy and unlimited conversations.

What is AI Chatbot Hosting?

AI chatbot hosting means running your own conversational AI — customer support bots, internal knowledge assistants, sales agents, or any chat-based application — on a dedicated GPU server instead of paying per-token fees to API providers like OpenAI, Anthropic, or Google.

With a GigaGPU dedicated GPU server you get a full GPU card, NVMe-backed storage, and a UK-based bare metal environment. Deploy open source LLMs like Llama 3, Mistral, Qwen, or DeepSeek behind a chatbot frontend in minutes. No shared resources, no usage caps, no conversation data leaving your environment.

Open source LLMs have reached the quality level where self-hosted chatbots rival commercial APIs for most use cases — customer support, internal Q&A, document retrieval, lead qualification, and more. Combine them with RAG pipelines, tool calling, and custom system prompts for production-grade chatbot deployments at a fraction of the API cost.

11+
GPU Options
UK
Server Location
Private
Single-Tenant Hardware
RAG
Ready Infrastructure
1 Gbps
Network Port
Fixed
Monthly Pricing
Root
Full Admin Access
NVMe
Fast Local Storage

Built for private AI chatbot hosting, not shared-cloud API queues.

Models for AI Chatbot Hosting

Run the open source LLMs that power production chatbots — from lightweight 7B assistants to powerful 70B+ reasoning models. For the full model list, see Open Source LLM Hosting.

Llama 3.1 8B
Meta
ChatFastLightweight
Llama 3.1 70B
Meta
ChatReasoningTool Use
Mistral 7B Instruct
Mistral AI
ChatEfficient
Mixtral 8x7B
Mistral AI
MoEChatMultilingual
Qwen 2.5 72B
Alibaba
ChatMultilingualTool Use
DeepSeek-V3
DeepSeek
ChatReasoningMoE
Gemma 2 27B
Google
ChatInstruction
Phi-3 Mini
Microsoft
SmallChatEdge
Command R+
Cohere
RAGChatTool Use
Custom Fine-Tunes
Your Stack
Domain SpecificFine-Tuned

Any Hugging Face-compatible LLM can be deployed as a chatbot backend depending on GPU memory and framework. Popular routes include LLM Hosting via Ollama, vLLM, or text-generation-webui.

Best GPUs for AI Chatbot Hosting

Recommended configurations based on typical chatbot and conversational AI workloads.

RTX 4060 Ti
16 GB VRAM
Small Team / Internal Chatbot

16GB runs quantised 7B–13B models comfortably for internal Q&A bots, knowledge assistants, and low-concurrency customer chat. Great starting point for chatbot MVPs.

Llama 3.1 8B Mistral 7B Phi-3
Configure RTX 4060 Ti →
RTX 3090
24 GB VRAM
Best Value for Most Chatbots

24GB is the sweet spot for chatbot hosting. Run 13B models at full precision or quantised 30B+ models with headroom for RAG context, tool calling, and concurrent users.

Llama 3.1 8B/13B Mixtral 8x7B Q4 Gemma 2 27B Q4
Configure RTX 3090 →
RTX 5090
32 GB VRAM
Production Chatbot with Fast Responses

Blackwell 2.0 delivers the lowest latency for conversational AI. Run larger models with long context windows and multiple concurrent chat sessions at production speed.

Qwen 2.5 32B Mixtral 8x7B Command R+
Configure RTX 5090 →
RTX 6000 PRO
96 GB VRAM
Enterprise Chatbot / 70B Models

96GB runs 70B+ parameter models at full quality — ideal for enterprise chatbots that need the strongest reasoning, multi-turn conversation, and deep domain expertise.

Llama 3.1 70B Qwen 2.5 72B DeepSeek-V3
Configure RTX 6000 PRO →

AI Chatbot Hosting Pricing

Fixed monthly pricing for dedicated GPU servers. No per-token fees, no conversation limits, no surprise bills. Pick the GPU that fits your chatbot workload.

RTX 3050 · 6GBStarter
ArchitectureAmpere
VRAM6 GB GDDR6
FP326.77 TFLOPS
BusPCIe 4.0 x8
6GB
small chat modelsPhi-3, TinyLlama, small quantised
From £69.00/mo
Configure
RTX 4060 · 8GBPopular Pick
ArchitectureAda Lovelace
VRAM8 GB GDDR6
FP3215.11 TFLOPS
BusPCIe 4.0 x8
8GB
7B chat modelsLlama 3.1 8B Q4, Mistral 7B Q4
From £79.00/mo
Configure
RTX 5060 · 8GBBudget
ArchitectureBlackwell 2.0
VRAM8 GB GDDR7
FP3219.18 TFLOPS
BusPCIe 5.0 x8
8GB
fast 7B chat inferenceGDDR7 bandwidth for chat
From £89.00/mo
Configure
RX 9070 XT · 16GBAMD RDNA 4
ArchitectureRDNA 4.0
VRAM16 GB GDDR6
FP3248.66 TFLOPS
BusPCIe 5.0 x16
16GB
AMD chat inferenceROCm ready for chatbots
From £129.00/mo
Configure
Arc Pro B70 · 32GBNew
ArchitectureXe2
VRAM32 GB GDDR6
FP3222.9 TFLOPS
BusPCIe 5.0 x16
32GB
larger chat modelsFits Mixtral, Qwen 32B
From £179.00/mo
Configure
RTX 5080 · 16GBHigh Throughput
ArchitectureBlackwell 2.0
VRAM16 GB GDDR7
FP3256.28 TFLOPS
BusPCIe 5.0 x16
16GB
fast 7B–13B chatBlackwell speed for conversational AI
From £189.00/mo
Configure
Radeon AI Pro R9700 · 32GBAI Pro
ArchitectureRDNA 4
VRAM32 GB GDDR6
FP3247.84 TFLOPS
BusPCIe 5.0 x16
32GB
production chat inferenceRAG + tool calling headroom
From £199.00/mo
Configure
Ryzen AI MAX+ 395 · 96GBNew
ArchitectureStrix Halo
Unified RAM96 GB LPDDR5X
FP3214.8 TFLOPS
BusPCIe 4.0
96GB
shared memory pool70B+ chatbot models fit
From £209.00/mo
Configure
RTX 5090 · 32GBFor Production
ArchitectureBlackwell 2.0
VRAM32 GB GDDR7
FP32104.8 TFLOPS
BusPCIe 5.0 x16
32GB
fastest chat inferenceLow latency production chatbots
From £399.00/mo
Configure
RTX 6000 PRO · 96GBEnterprise
ArchitectureBlackwell 2.0
VRAM96 GB GDDR7
FP32126.0 TFLOPS
BusPCIe 5.0 x16
96GB
70B+ models at full qualityEnterprise chatbot, no compromises
From £899.00/mo
Configure

Chatbot model compatibility depends on VRAM, quantisation level, and context window requirements. Quantised models (Q4/Q5) significantly reduce VRAM needs. View all GPU plans →

Why Self-Host Your AI Chatbot Instead of Using APIs?

Per-token API pricing adds up fast once your chatbot is handling real traffic. Here's how a dedicated GPU compares.

Chatbot API Pricing

Pay per token — costs scale with every conversation
GPT-4o (OpenAI)~$2.50–$10 / 1M tokens
Claude 3.5 Sonnet~$3–$15 / 1M tokens
Gemini 1.5 Pro~$1.25–$5 / 1M tokens
10k conversations/month$150–$1,000+

Dedicated GPU Chatbot

Fixed monthly rate — unlimited conversations, no token fees
RTX 4060 Ti · Llama 3.1 8BFixed/mo
RTX 3090 · Mistral 7B + RAGFixed/mo
RTX 5090 · Qwen 2.5 32BFixed/mo
10k conversations/monthSame flat rate

Example: Customer Support Chatbot at 10,000 Conversations/Month

API route: At ~500 tokens per conversation (input + output), 10,000 conversations = ~5M tokens/month. Via GPT-4o that's roughly $25–$50/month at current rates — but costs scale linearly and longer conversations, RAG context, or higher-tier models push bills much higher.
Self-hosted route: A dedicated RTX 3090 running Llama 3.1 or Mistral via vLLM handles 10,000+ conversations per month at a fixed monthly rate — and handles 100,000 conversations just as affordably.
Privacy bonus: Conversation data never leaves your server. Critical for customer support, healthcare chatbots, legal assistants, and any application where data residency or GDPR compliance matters.

API cost estimates are based on publicly listed pricing at time of writing and are indicative only. Actual savings depend on conversation length, model choice, and usage patterns. GPU server prices retrieved live from the GigaGPU portal.

AI Chatbot Hosting Use Cases

From customer support to internal knowledge assistants — dedicated GPU servers handle every chatbot workload.

Customer Support Chatbots

Deploy AI-powered customer support that handles enquiries, troubleshooting, and FAQs 24/7. Connect to your knowledge base via RAG and serve unlimited conversations at a fixed monthly cost — no per-message API fees.

Internal Knowledge Assistants

Build a private ChatGPT-style assistant for your team that answers questions from internal docs, wikis, and databases. All data stays on your server — ideal for HR, IT helpdesk, and onboarding bots.

E-Commerce & Sales Chatbots

Guide shoppers through product recommendations, handle pre-sales questions, and qualify leads with an AI chatbot running on your own infrastructure. Integrate with your product catalogue and CRM via tool calling.

Education & Tutoring Bots

Create AI tutors that explain concepts, answer student questions, and provide personalised learning paths. Self-hosting ensures student data privacy and compliance with educational data regulations.

Healthcare & Triage Chatbots

Deploy private healthcare chatbots for symptom triage, appointment booking, and patient FAQ handling. Patient data stays on UK infrastructure — essential for NHS, GDPR, and data residency compliance.

Legal & Compliance Assistants

Build chatbots that answer contract questions, summarise legal documents, and assist with compliance queries. Confidential legal data never leaves your dedicated server — no third-party data processing.

Enterprise RAG Chatbots

Combine open source LLMs with vector databases and retrieval pipelines to build enterprise chatbots that answer questions grounded in your company's actual documents and data.

Voice-Enabled AI Agents

Combine your chatbot LLM with speech models to create voice agents — Whisper for ASR, your LLM for reasoning, and TTS for spoken responses, all on a single GPU.

Compatible Chatbot Frameworks & Tools

Every GigaGPU server ships with full root access — install any LLM framework or chatbot stack in minutes.

Deploy an AI Chatbot in 4 Steps

From order to live chatbot — typically under an hour.

01

Choose Your GPU & Configure

Pick the GPU that fits your chatbot model — 7B lightweight assistant or 70B enterprise reasoner. Select your OS (Ubuntu 22/24, Debian, Windows) and NVMe storage size.

02

Server Provisioned

Your dedicated GPU server is provisioned and you receive SSH or RDP credentials. Typical deployment time is under one hour.

03

Install Your Chatbot Stack

Install Ollama, vLLM, or your preferred framework. Pull your chosen model from Hugging Face or Ollama Hub. Set up your RAG pipeline with LangChain or LlamaIndex if needed.

04

Go Live

Add a frontend like Open WebUI, Chainlit, or your custom chat interface. Expose via Nginx with SSL. You're live — unlimited conversations, zero per-token fees, private infrastructure.

AI Chatbot Hosting — Frequently Asked Questions

Everything you need to know about self-hosting AI chatbots on dedicated GPU hardware.

AI chatbot hosting means running your own conversational AI on a dedicated GPU server instead of paying per-token fees to API providers like OpenAI, Anthropic, or Google. You deploy an open source LLM — such as Llama 3, Mistral, or Qwen — behind a chat interface, giving you unlimited conversations at a fixed monthly rate with full data privacy.
Any instruction-tuned or chat-finetuned LLM works. Popular choices include Llama 3.1 (8B/70B), Mistral 7B Instruct, Mixtral 8x7B, Qwen 2.5, Gemma 2, Command R+, and many more. You can also deploy custom fine-tuned models trained on your own data. See our Open Source LLM Hosting page for the full list.
It depends on the model size. For 7B models (fast, lightweight chatbots), 8–16GB VRAM is sufficient — the RTX 4060 Ti (16GB) is a great starting point. For 13B–30B models with RAG, 24GB is ideal — the RTX 3090 is the best value option. For 70B+ enterprise models, you need 96GB — the RTX 6000 PRO fits this perfectly.
At sustained usage, typically yes. API costs scale linearly with every token — longer conversations, more users, or RAG context all increase your bill. A dedicated GPU server processes unlimited tokens at a fixed monthly rate. The break-even point depends on your volume, but most teams processing thousands of conversations per month find self-hosting significantly cheaper.
Yes — this is one of the most popular use cases. Run your LLM alongside a vector database (ChromaDB, Qdrant, pgvector) on the same server. Use LangChain or LlamaIndex to build the retrieval pipeline. The GPU handles inference while the CPU and NVMe storage handle embedding and retrieval. A 24GB RTX 3090 fits a 13B model plus a full RAG stack comfortably.
Popular options include Open WebUI (a ChatGPT-style interface), Chainlit (embeddable chat widget), Streamlit, Gradio, or your own custom frontend. These connect to your LLM backend via API — typically an OpenAI-compatible endpoint served by Ollama or vLLM.
Yes. Modern open source LLMs support function calling and tool use — your chatbot can query databases, call REST APIs, look up product catalogues, create tickets, and more. Frameworks like LangChain make it straightforward to wire up tools. Models like Llama 3.1, Qwen 2.5, and Command R+ have native tool-calling capabilities.
Your GigaGPU server is a dedicated bare metal machine in a UK data centre — no shared resources, no multi-tenant environment. Conversation data, documents, and embeddings are processed entirely on your hardware and never sent to a third party. This makes it suitable for GDPR compliance, healthcare data, legal documents, and other sensitive applications.
Yes. Deploy your LLM behind an API endpoint, then embed a chat widget on your site using Chainlit, a custom JavaScript widget, or any frontend that calls your API. Most teams use Nginx as a reverse proxy with SSL and authentication. The chatbot appears as a live chat widget on your website, powered entirely by your own GPU server.
With vLLM's continuous batching, a single GPU can handle many concurrent users efficiently. A 7B model on an RTX 3090 can typically serve 10–50+ concurrent chat sessions depending on response length and latency requirements. For higher concurrency, larger GPUs or multiple servers can be used. vLLM's PagedAttention makes memory usage highly efficient for concurrent requests.
Yes — combine your chatbot LLM with speech models for a full voice agent. Run Whisper for speech-to-text, your LLM for reasoning, and Kokoro TTS or XTTS-v2 for text-to-speech — all on the same GPU. A 24GB RTX 3090 fits a 7B LLM plus a speech stack comfortably.
All servers are located in the UK. This ensures low latency for European users and compliance with UK/EU data protection requirements — important for chatbots handling customer data, support conversations, or any personal information.

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 AI chatbots, RAG pipelines, customer support bots, knowledge assistants, and any other conversational AI workload — with no shared resources and no per-token fees.

Get in Touch

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

Contact Sales →

Or browse the knowledgebase for setup guides on Ollama, vLLM, Open WebUI, and more.

Start Hosting Your AI Chatbot Today

Flat monthly pricing. Full GPU resources. UK data centre. Deploy Llama, Mistral, Qwen and more in under an hour.

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