--- title: "Private LLM Hosting | Managed AI on Dedicated Hardware | Bit Refinery" url: "https://bitrefinery.com/services/private-llm-hosting" description: "Run open-source AI models privately on dedicated GPU-accelerated hardware. Zero egress fees, your data never leaves, fully managed deployment. Deploy Qwen, Llama, Mistral, and more in Denver & Seattle data centers." lastmod: "2026-05-31" source: "auto-generated from SSG HTML" --- PRIVATE LLM HOSTING # Run AI Models on Your Own Infrastructure Deploy open-source language models on your own dedicated server in our data centers. Full root access. Your data never leaves. Zero egress fees. No per-token API costs. 99.99% Uptime SLA $0 Egress Fees Data Never Leaves Denver & Seattle DCs PRIVATE LLM INFERENCE SECURE MODEL: QWEN3-8B127 tok/s RESPONSE STREAM Hello GPU87% VRAM5.2GB LATENCY12ms EGRESS$0 ## What is Private LLM Hosting? Private LLM hosting means running open-source AI language models — like Llama, Qwen, Mistral, and Gemma — on dedicated hardware that you control. Instead of sending every prompt to a cloud API and paying per token, your model runs on infrastructure in our data center with dedicated compute, memory, and GPU resources. Your data never touches a third-party API. There are no per-token charges, no rate limits, and no surprise bills. ### Data Privacy Every prompt sent to OpenAI, Anthropic, or Google touches external servers. For companies handling sensitive data, that's a compliance risk. ### Cost Predictability Per-token pricing scales unpredictably. A single busy chatbot can generate thousands of dollars in monthly API costs. ### No Vendor Lock-in Open-source models run on standard hardware. Switch models anytime without changing providers. ### Zero Egress Fees Inference responses are data transfer. On AWS or GCP, that's metered egress. On Bit Refinery, it's $0. 72% of enterprises cite data privacy as the top barrier to LLM adoption Kong 2025 $0 per-token cost — fixed monthly pricing regardless of usage $0 egress fees on all inference traffic ## How It Works 1 ### Tell Us What You Need Share your use case — which models you want to run, how many users, what compliance requirements. We'll design a deployment tailored to your workload and budget. 2 ### Choose Your Model Select from any open-source or custom model — Qwen, Llama, Mistral, Gemma, DeepSeek, Phi, and hundreds more, or bring your own fine-tuned model. We deploy it using production-grade inference engines like vLLM, Ollama, or llama.cpp. 3 ### Get Your Dedicated Server Your dedicated server is custom-built for your workload — with or without GPU. Full root access, a managed firewall, your choice of inference engine, and an OpenAI-compatible API endpoint ready to go. 4 ### Scale When You Need To Add models. Increase capacity. Move to multi-model deployments. Scale down if your needs change. Month-to-month, no long-term contracts. ## Choose the Right Model for Your Workload You don't need a 400-billion-parameter frontier model for most business tasks. Modern small language models in the 7B–30B range deliver 80–90% of frontier model quality on focused tasks — at a fraction of the cost. GENERAL-PURPOSE REASONING & CHAT ### Qwen3-8B 8B parameters The current best all-around small model. Dual-mode architecture supports both fast dialogue and deep reasoning within a single model. 131K token context window. Ideal for internal copilots, customer support, and general Q&A. ~6 GB (Q4) · 50–150 tokens/sec (GPU) CODE GENERATION & REVIEW ### DeepSeek-R1-Distill-Qwen-7B 7B parameters Distilled from DeepSeek-R1 with exceptional reasoning capabilities. 92.8% accuracy on MATH-500 and strong code generation benchmarks. Purpose-built for development workflows, code review automation, and technical documentation. ~5 GB (Q4) · 50–150 tokens/sec (GPU) FINE-TUNING & CUSTOM MODELS ### Mistral 7B 7B parameters The most fine-tuning-friendly open architecture. Widely used as a base model for domain-specific SLMs in legal, medical, financial, and security applications. Large ecosystem of adapters and tooling. ~5 GB (Q4) · 50–150 tokens/sec (GPU) DOCUMENT PROCESSING & SUMMARIZATION ### Gemma 4 27B 27B parameters (Google) Google's latest open model (Apache 2.0). Per-layer embedding architecture delivers frontier-class summarization, document analysis, and structured extraction while fitting on a single consumer GPU. Strong multilingual support. ~20 GB (Q4) · 20–60 tokens/sec (GPU) MULTIMODAL (VISION + TEXT) ### Qwen2.5-VL-7B-Instruct 7B parameters Processes images and video alongside text. Useful for document OCR, image classification, visual inspection, and any workflow where the model needs to "see" input. ~6 GB (Q4) · 30–80 tokens/sec (GPU) ENTERPRISE-SCALE REASONING ### Qwen3 32B 32B parameters The strongest open model in the 30B class. Deeper reasoning, more nuanced output, larger context handling. For workloads where 8B models aren't quite enough. ~20 GB (Q4) · 20–60 tokens/sec (GPU) CUSTOM & FINE-TUNED MODELS ### Bring Your Own Model Any size Deploy models you've fine-tuned in-house or trained from scratch. We support GGUF, GPTQ, AWQ, and SafeTensors formats from Hugging Face or your own registry. Your weights stay on your hardware. Varies by model · We handle deployment & optimization MULTILINGUAL APPLICATIONS ### Qwen 2.5 (7B / 14B / 32B) Best non-English language support across major open models. Strong for multilingual customer support, translation workflows, and global enterprise deployments. SECURITY & VULNERABILITY ANALYSIS ### Custom SLMs / Fine-tuned Models Task-specific small language models for cybersecurity — vulnerability discovery, code auditing, threat intelligence. Bring your own model, we provide the infrastructure. ## Custom-Built for Your Workload Every deployment is different. We build a private LLM setup tailored to your models, your users, and your budget — with on a dedicated server with full root access, $0 egress fees, and GPU acceleration available based on your workload. ### Every deployment includes: Dedicated server — your hardware, your workload only Full root and SSH access Managed firewall included GPU acceleration available (50–150+ tokens/sec on 7B–14B models) OpenAI-compatible API endpoint Managed deployment, monitoring, and updates $0 egress fees — unlimited bandwidth included 99.99% uptime SLA Month-to-month — no long-term contracts Hosted in Denver or Seattle data centers Configuration Models Use Case Single Model 1 model (7B–14B) Small team copilot, internal chatbot, dev/test Multi-Model 2–5 models (7B–30B) Production apps, multiple departments, A/B testing Enterprise 5+ models (7B–70B) Organization-wide AI, RAG pipelines, compliance workloads Full Stack Unlimited + managed services LLM + ClickHouse + MinIO + GCP Interconnect All configurations are custom. Contact us for a quote based on your specific requirements. ## Bit Refinery vs. RunPod RunPod is a popular cloud GPU platform. Here's how private LLM hosting on Bit Refinery compares for teams running persistent AI inference workloads. Feature Bit Refinery RunPod Pricing model Fixed monthly — custom quote Per-second / per-hour GPU rental Cost at scale (24/7) Predictable flat rate RTX 4090 ~$0.44/hr = ~$317/mo; H100 ~$3.35/hr = ~$2,412/mo Egress fees $0 — unlimited bandwidth $0 on network storage; standard egress elsewhere Hardware Dedicated server — full root access, your workload only Shared cloud GPUs Uptime SLA 99.99% 99.9% Data residency Denver, CO and Seattle, WA 31 regions — varies by availability Management Fully managed — we deploy, monitor, update Self-service — you manage containers Compliance SOC 2, HIPAA, PCI DSS, ISO 27001, FedRAMP SOC 2 Type II GCP Interconnect Free private peering (Denver) Not available Best for Managed, private, predictable-cost AI inference Self-service elastic cloud GPU compute **The key difference:** RunPod is a self-service cloud GPU platform — great for developers who want to manage their own infrastructure. Bit Refinery is a fully managed private AI hosting service — we handle the deployment, monitoring, and operations so you just use the API. If you need compliance certifications, dedicated hardware, and predictable costs without managing infrastructure, Bit Refinery is built for that. RunPod pricing based on published rates at runpod.io/pricing as of April 2026. Bit Refinery pricing is custom — contact us for a quote. ## Cost Comparison Three ways to run AI inference. Here's how they compare at real-world token volumes. ### vs. Cloud LLM APIs (per-token pricing) Daily Tokens GPT-4o/mo GPT-4o Mini/mo Bit Refinery/mo 500K ~$2,250 ~$225 Fixed monthly rate 2M ~$9,000 ~$900 Fixed monthly rate 10M ~$45,000 ~$4,500 Fixed monthly rate 50M ~$225,000 ~$22,500 Fixed monthly rate Cloud API pricing based on published per-token rates as of April 2026. Bit Refinery pricing is fixed regardless of token volume. ### vs. RunPod Cloud GPU (24/7 inference) GPU RunPod Hourly RunPod 24/7 Monthly Bit Refinery RTX 4090 (24 GB) ~$0.44/hr ~$317/mo Custom quote — dedicated, fully managed L4 (24 GB) ~$0.24/hr ~$173/mo Custom quote — dedicated, fully managed A100 80 GB ~$1.64/hr ~$1,181/mo Custom quote — dedicated, fully managed H100 SXM ~$3.35/hr ~$2,412/mo Custom quote — dedicated, fully managed RunPod pricing from runpod.io/pricing (Community Cloud, April 2026). Does not include storage costs ($0.07–$0.20/GB/mo). Bit Refinery includes storage, management, monitoring, and $0 egress. **RunPod charges per hour. Cloud APIs charge per token. Bit Refinery charges a flat monthly rate.** At low or bursty usage, per-hour pricing can be cheaper. At sustained 24/7 inference — which is what most production AI workloads look like — fixed monthly pricing eliminates billing surprises and typically costs less when you factor in management overhead, egress, and storage. ### Feature Comparison at a Glance Cloud APIs Cloud GPUs Bit Refinery Pricing Per token Per hour/second Fixed monthly Data privacy Data sent to provider Shared infrastructure Dedicated server, full access Management None needed (API) Self-service Fully managed Model choice Provider's models only Any (you deploy) Any (we deploy) Egress fees N/A Varies $0 Compliance Varies SOC 2 SOC 2, HIPAA, PCI, ISO Uptime SLA Varies 99.9% 99.99% Best for Low volume, elastic Dev/test, experimentation Production, compliance ## Built for Real Workloads ### Internal AI Copilot Deploy a private ChatGPT alternative for your team. Employees ask questions, generate content, and get coding assistance — without sending proprietary data to external APIs. ### Customer Support Automation Power chatbots and support ticket triage with a fine-tuned SLM. Process thousands of customer interactions daily with consistent, fast responses. Zero per-token cost. ### Document Processing Pipeline Extract, classify, and summarize documents at scale. Medical records, legal contracts, financial reports — process sensitive documents without sending them to external services. ### Code Review & Security Scanning Run specialized code analysis models that scan repositories for vulnerabilities, generate code reviews, and flag security issues. Source code never leaves your infrastructure. ### RAG (Retrieval-Augmented Generation) Combine a private LLM with your own knowledge base. Connect to ClickHouse or Trino for data retrieval, MinIO for document storage — all on Bit Refinery with zero egress between services. ### Agentic Workflows & Automation Multi-step AI tasks like report generation, data entry automation, and tool orchestration. Agents generate 10–100x more tokens — fixed pricing removes the ceiling. ### Regulated Industry Compliance Healthcare (HIPAA), finance (SOC 2, PCI DSS), legal, and government workloads where data residency and access controls are non-negotiable. Private LLM hosting on dedicated hardware in SOC 2 compliant data centers with private networking and encryption at rest. ## Production-Grade Inference Stack We deploy your models using battle-tested open-source inference engines — not experimental tooling. ### vLLM Production-grade serving with continuous batching and PagedAttention for high-concurrency workloads. Best for multi-user API endpoints. ### Ollama Simple deployment with automatic hardware detection and an OpenAI-compatible REST API. Best for development, internal tools, and single-tenant deployments. ### llama.cpp Lightweight C++ runtime optimized for efficient inference. Best for air-gapped environments and maximum hardware efficiency. ### Model Formats - GGUF — Universal format for CPU and hybrid CPU/GPU inference with quantization support. - GPTQ / AWQ — GPU-optimized quantization formats for maximum throughput on dedicated GPUs. ### Quantization & API All models deployed with **Q4\_K\_M quantization** by default — retaining ~95% of full-precision quality while reducing memory by 75%. Higher precision available on request. Every deployment exposes an **OpenAI-compatible API endpoint**. If your application works with the OpenAI SDK, it works with your private Bit Refinery endpoint — just change the base URL. ## Why Bit Refinery for Private AI ### $0 Egress Fees Every inference response is data transfer. On AWS, that's $0.09/GB. On GCP, $0.12/GB. On Bit Refinery, it's $0 — unlimited 1 Gbps bandwidth included. ### Your Server, Your Rules You get a dedicated server with full root access — not a shared VM where another tenant's workload degrades your inference latency. Install what you need, configure it how you want. ### GPU-Accelerated Inference GPU acceleration available on every deployment. 50–150+ tokens/sec on 7B–14B models — fast enough for real-time chat, streaming responses, and production applications. CPU-only configurations also available for lighter workloads. ### Data Never Leaves Your prompts, documents, and outputs stay on your hardware in our Tier 3 data centers in Denver or Seattle. No third-party data processing agreements. ### Predictable Monthly Pricing Fixed monthly rate. No per-token charges, no bandwidth overages, no compute-hour surprises. Budget AI infrastructure the same way you budget rent. ### Google Cloud Interconnect (Denver) Every Denver deployment includes free private peering to Google Cloud. Run your LLM on Bit Refinery and connect to BigQuery, Vertex AI, or Cloud Storage over a sub-millisecond private link. ### Full Stack Integration Combine private LLM hosting with Bit Refinery's other managed services for a complete AI infrastructure stack: Included with every deployment Foundryby Bit Refinery Your control plane for private AI. Browse models, manage API keys, secure access. foundry.bitrefinery.com Foundry Models API keys IP whitelist Usage Playground Settings ## Models Qwen3-8BLive 8B params · Q4\_K\_M · General reasoning Running · 5.8 GB · 142 t/s · 3 active users DeepSeek-R1-Distill-7BLive 7B params · Q4\_K\_M · Code generation Running · 4.9 GB · 156 t/s · 1 active user Mistral-7B-v0.3 7B params · Q4\_K\_M · Fine-tuned (custom) Stopped · 4.6 GB API endpoint`https://acme-corp.foundry.bitrefinery.com/v1` API key `sk-br-••••••••••••••a4f8` IP whitelist10.0.1.0/24203.0.113.42 ### Model library Browse, deploy, or upload your own models ### API & keys OpenAI-compatible endpoint. Generate and rotate keys. ### IP whitelist Restrict API access to only your approved IPs Chat playgroundUsage metricsServer monitoringAudit logging No CLI required. No DevOps. Just log in and manage your AI. ## Frequently Asked Questions ## Ready to Run AI on Your Own Infrastructure? Get a private LLM deployment — no per-token costs, your data stays yours. Custom-built for your workload. Trusted since 2008 · 99.99% SLA · Denver & Seattle data centers · $0 egress fees