--- title: "Offshore GPU Servers · RTX 4090, 5090 & H100, No KYC" description: "Dedicated NVIDIA GPUs from $61.99/mo: RTX 4090, 5090, A100 and H100 with CUDA preinstalled, for private LLMs. Ready in 1–24 h, no KYC, crypto." url: https://offshoreserv.com/offshore-gpu-servers lang: en updated: 2026-09-27 source: HTML page at the url above (canonical); this is its Markdown version --- NVIDIA · CUDA preinstalled · no KYC # Offshore GPU servers. Private AI, no KYC. Dedicated NVIDIA GPUs from RTX A4000 to 4 × H100 for LLM inference, fine-tuning, image generation and rendering. The driver and CUDA come preinstalled, and your prompts never leave the box. **From $61.99/mo, 30% under the cheapest offshore competitor.** - Ready in 1 to 24 hours - Dedicated GPUs, never shared - Prompts stay on your server - No KYC, email only ## 10 GPU servers, from RTX A4000 to 4 × H100. Every GPU is dedicated to you: no time-slicing, and no spot capacity that disappears in the middle of a job. | GPU | VRAM | CPU | RAM | Storage | Price | | --- | --- | --- | --- | --- | --- | | **RTX A4000** (Entry inference, 7-13B models) | 16 GB | 8 vCPU | 64 GB | 1 TB NVMe | **$61.99**/mo | | **RTX 4090** (Best price per token), popular | 24 GB | 8 vCPU | 64 GB | 1 TB NVMe | **$84.99**/mo | | **RTX 5090** (Fast inference, image and video) | 32 GB | 12 vCPU | 96 GB | 2 TB NVMe | **$134.99**/mo | | **RTX 6000 Ada** (48 GB, 32B at 8-bit) | 48 GB | EPYC 7302P · 16c | 128 GB | 2 × 1.92 TB NVMe | **$306.99**/mo | | **A100 80 GB** (Training and fine-tuning) | 80 GB | 16 vCPU | 128 GB | 3.84 TB NVMe | **$355.99**/mo | | **L40S** (Inference at scale) | 48 GB | EPYC 7443P · 24c | 256 GB | 2 × 1.92 TB NVMe | **$418.99**/mo | | **2 × RTX 5090** (64 GB of VRAM in one box) | 64 GB | EPYC 9354 · 32c | 256 GB | 2 × 1.92 TB NVMe | **$558.99**/mo | | **H100 80 GB** (Frontier training, SXM5) | 80 GB | 24 vCPU | 192 GB | 2 TB NVMe | **$581.99**/mo | | **2 × H100** (160 GB HBM3, NVLink) | 160 GB | 48 vCPU | 384 GB | 4 TB NVMe | **$1,096.99**/mo | | **4 × H100** (320 GB HBM3, NVLink), cluster | 320 GB | 96 vCPU | 768 GB | 30 TB NVMe | **$2,348.99**/mo | Planning a cluster or a model that needs more than 320 GB of VRAM? GPU and dedicated customers can ask for a custom build by ticket from the [client area](https://offshoreserv.com/account/support). ## Three kinds of GPU server. Consumer RTX cards for price per token, datacenter GPUs for memory and bandwidth, multi-GPU nodes for the largest models. - [RTX A4000 to 6000 Ada — 16 to 64 GB of VRAM. The most inference per dollar, for 7B to 70B models and image generation. — From **$61.99**/mo See the servers](https://offshoreserv.com/offshore-gpu-servers/rtx) - [A100, L40S & H100 — HBM or ECC memory and up to 3.35 TB/s of bandwidth, for training and serving at scale. — From **$355.99**/mo See the servers](https://offshoreserv.com/offshore-gpu-servers/datacenter) - [Multi-GPU nodes — Two or four GPUs in one server, up to 320 GB of VRAM with NVLink on H100. — From **$558.99**/mo See the servers](https://offshoreserv.com/offshore-gpu-servers/multi-gpu) - [Custom build — Already a GPU or dedicated customer? Ask by ticket for another GPU, more memory or storage, or a specific jurisdiction, and we reply with a price. — How support works](https://offshoreserv.com/contact) ## Rent a specific GPU. The four cards people ask for most, each with its specifications, what fits in its memory and its price per hour of use. - [RTX 4090, 24 GB — The value card for private chat assistants and image generation. — **$84.99**/mo RTX 4090 servers](https://offshoreserv.com/offshore-gpu-servers/rtx-4090) - [RTX 5090, 32 GB — Blackwell and GDDR7: faster tokens, longer contexts, or two cards for 70B. — **$134.99**/mo RTX 5090 servers](https://offshoreserv.com/offshore-gpu-servers/rtx-5090) - [A100, 80 GB — 80 GB of HBM2e on one card, for fine-tuning and large models. — **$355.99**/mo A100 servers](https://offshoreserv.com/offshore-gpu-servers/a100) - [H100, 80 GB — HBM3 at 3.35 TB/s and FP8, alone or up to four with NVLink. — **$581.99**/mo H100 servers](https://offshoreserv.com/offshore-gpu-servers/h100) ## Your models, your prompts, your server. Run open-weight models on hardware nobody else touches. No API provider sees your prompts, and we do not log or inspect your traffic. Llama, Qwen, Mistral, DeepSeek, Gemma and other open-weight models run on a single GPU once they are quantized, and the largest ones fit on our multi-GPU nodes. Serve them with **Ollama** for a quick start, **vLLM** for an OpenAI-compatible endpoint under load, or **llama.cpp** for the most compact setups. The table gives the memory a model needs at each precision with an 8K-token context for one user and 10% headroom. Longer contexts and more users need more. - Chat with a private assistant from your browser through an SSH tunnel. - Expose an API to your own apps, never to a third-party provider. - Fine-tune with LoRA on your own data, which never leaves the server. [Set up Ollama, vLLM or ComfyUI](https://offshoreserv.com/docs/gpu/images) · [How much VRAM do LLMs need?](https://offshoreserv.com/blog/how-much-vram-for-llms) | Model size | 4-bit | 8-bit | 16-bit | | --- | --- | --- | --- | | 7–8B | ~7 GB RTX A4000 | ~11 GB RTX A4000 | ~19 GB RTX 4090 | | 13–14B | ~11 GB RTX A4000 | ~18 GB RTX 4090 | ~32 GB RTX 6000 Ada, L40S | | 32B | ~24 GB RTX 5090 | ~40 GB RTX 6000 Ada, L40S | ~73 GB A100 or H100 | | 70B | ~50 GB A100, H100 or 2 × RTX 5090 | ~85 GB 2 × H100 | ~157 GB 4 × H100 | | 123B | ~86 GB 2 × H100 | ~147 GB 2 × H100 | ~274 GB 4 × H100 | ## Ready for CUDA on first login. Check the card, pull a model, start serving. - **Dedicated GPUs** — Each card is yours alone: no time-slicing, no shared memory. - **Driver & CUDA ready** — Ubuntu 24.04 with the NVIDIA driver and the CUDA toolkit installed. - **A guide for every stack** — Step by step for PyTorch, vLLM, Ollama, ComfyUI and Docker. - **NVMe storage** — 1 to 30 TB of NVMe for datasets, checkpoints and weights. - **1 Gbps, unmetered** — Pull models and datasets without a traffic meter. - **Nothing logged** — We never see or log your prompts, outputs or training data. - **DDoS mitigation** — Public endpoints stay online under attack. - **Full root** — Your drivers, your kernel modules, your stack. ## Every GPU, side by side. For inference, memory bandwidth sets the tokens per second; VRAM sets which models fit. | Specification | RTX A4000 | RTX 4090 (Popular) | RTX 5090 | RTX 6000 Ada | A100 80 GB | L40S | 2 × RTX 5090 | H100 80 GB | 2 × H100 | 4 × H100 (Cluster) | | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | | GPU | 1 × RTX A4000 | 1 × RTX 4090 | 1 × RTX 5090 | 1 × RTX 6000 Ada | 1 × A100 | 1 × L40S | 2 × RTX 5090 | 1 × H100 | 2 × H100 | 4 × H100 | | VRAM | 16 GB | 24 GB | 32 GB | 48 GB | 80 GB | 48 GB | 64 GB | 80 GB | 160 GB | 320 GB | | Memory type | GDDR6 ECC | GDDR6X | GDDR7 | GDDR6 ECC | HBM2e | GDDR6 ECC | GDDR7 | HBM3 | HBM3 | HBM3 | | Bandwidth per GPU | 448 GB/s | 1,008 GB/s | 1,792 GB/s | 960 GB/s | ~2.0 TB/s | 864 GB/s | 1,792 GB/s | 3.35 TB/s | 3.35 TB/s | 3.35 TB/s | | CPU | 8 vCPU | 8 vCPU | 12 vCPU | EPYC 7302P · 16c | 16 vCPU | EPYC 7443P · 24c | EPYC 9354 · 32c | 24 vCPU | 48 vCPU | 96 vCPU | | System memory | 64 GB | 64 GB | 96 GB | 128 GB | 128 GB | 256 GB | 256 GB | 192 GB | 384 GB | 768 GB | | Storage | 1 TB NVMe | 1 TB NVMe | 2 TB NVMe | 2 × 1.92 TB NVMe | 3.84 TB NVMe | 2 × 1.92 TB NVMe | 2 × 1.92 TB NVMe | 2 TB NVMe | 4 TB NVMe | 30 TB NVMe | | Monthly | **$61.99** | **$84.99** | **$134.99** | **$306.99** | **$355.99** | **$418.99** | **$558.99** | **$581.99** | **$1,096.99** | **$2,348.99** | | Quarterly, per month | $58.89 | $80.74 | $128.24 | $291.64 | $338.19 | $398.04 | $531.04 | $552.89 | $1,042.14 | $2,231.54 | | Yearly, per month | $54.55 | $74.79 | $118.79 | $270.15 | $313.27 | $368.71 | $491.91 | $512.15 | $965.35 | $2,067.11 | ## What people run on offshore GPUs. From a private chat assistant to fine-tuning on your own data, on cards nobody else uses. - **LLM inference** — Private chat and APIs on open-weight models, from 8B to 405B. — VRAM guide - **Fine-tuning** — LoRA and QLoRA on your own data, which never leaves the server. — [A100 & H100](https://offshoreserv.com/offshore-gpu-servers/datacenter) - **Image & video generation** — Stable Diffusion, Flux and video models with ComfyUI. — [RTX 5090](https://offshoreserv.com/offshore-gpu-servers/rtx) - **3D rendering** — Blender Cycles and other GPU renderers, without tying up your workstation. — [RTX servers](https://offshoreserv.com/offshore-gpu-servers/rtx) - **Speech & transcription** — Whisper and text-to-speech models on audio that must stay private. — [GPU images](https://offshoreserv.com/docs/gpu/images) - **Research & data science** — Jupyter, PyTorch and CUDA experiments on dedicated hardware. — Compare GPUs ## Four jurisdictions for GPUs. Availability depends on the card: the plan table shows where each one is in stock. - [Moldova Chișinău Best value — Outside the EU · no DSA — London **~33 ms** New York **~113 ms** Singapore **~129 ms**](https://offshoreserv.com/locations/moldova) - [Netherlands Amsterdam Network hub — EU member · DSA applies — London **~7 ms** New York **~87 ms** Singapore **~154 ms**](https://offshoreserv.com/locations/netherlands) - [Iceland Reykjavík Free-speech haven — EEA · outside the EU · no DSA — London **~29 ms** New York **~63 ms** Singapore **~169 ms**](https://offshoreserv.com/locations/iceland) - [Romania Bucharest Budget EU — EU member · DSA applies — London **~32 ms** New York **~113 ms** Singapore **~131 ms**](https://offshoreserv.com/locations/romania) Latency figures are estimates from distance, not measurements. Every jurisdiction has the same prices. [How we estimate latency](https://offshoreserv.com/network) ## The rules, before you pay. What we promise is written into our policies, not just our marketing. - US DMCA notices **Not actioned** — Answered with our policy, never enforced. Only a local court order, or a valid EU notice in EU locations, can require action. - Identity **Email only** — No name, address, phone or ID document, ever. A private or disposable address is fine. - Payment **5 cryptocurrencies** — Bitcoin, Ethereum, Monero, USDT and Solana, paid on-chain from any wallet to your balance. No card processor, no chargebacks. - Transparency **Signed canary** — A PGP-signed warrant canary every quarter and a public count of every request we receive. ## GPU servers, answered. **Another question?** The full FAQ answers what people ask before an order: payments, privacy, complaints and support. ### Are the GPUs shared or time-sliced? No. Every GPU in your plan is dedicated to your server for as long as you rent it. Nobody else runs jobs on it, and its memory is never shared. ### Which GPU do I need for my model? Start from the memory the weights need: see the table above or our guide on [VRAM for LLMs](https://offshoreserv.com/blog/how-much-vram-for-llms). As a rule, a 4-bit 70B model needs about 50 GB with an 8K context, so an 80 GB A100 or H100, or two RTX 5090s. ### Are the NVIDIA driver and CUDA installed? Yes. The Ubuntu images ship with the NVIDIA driver and the CUDA toolkit. PyTorch, vLLM, Ollama and ComfyUI install in a few commands, as shown in the [GPU images guide](https://offshoreserv.com/docs/gpu/images). ### Can I run a public AI service? Yes, as long as it is legal in your server’s jurisdiction and follows our [acceptable use policy](https://offshoreserv.com/acceptable-use-policy). You are responsible for what your service generates and serves. ### How fast is delivery? Between 1 and 24 hours after you order, depending on the card. If a GPU is temporarily out of stock in your jurisdiction, we tell you and either hold your order or return the payment to your balance. ### Can I mine cryptocurrency on a GPU server? Yes. Mining is allowed on GPU and dedicated servers, which are provisioned for you alone. ### Can I get a refund? GPU servers are not refundable once delivered, because the hardware is set aside for you. Check the specifications and the [GPU images guide](https://offshoreserv.com/docs/gpu/images) before ordering; your balance can always pay for other services. ### Do you log prompts, outputs or datasets? No. We do not log or inspect your server’s traffic, and we never look at what runs inside it. ## Guides and reading for GPU owners. Guides, policies and articles picked for this page, written by our team. - [AI-ready GPU images Drivers, CUDA and the tools preinstalled on GPU servers.](https://offshoreserv.com/docs/gpu/images) - [How much VRAM do LLMs need?Model sizes, quantization and the right GPU.](https://offshoreserv.com/blog/how-much-vram-for-llms) - [Self-host an LLM Ollama or vLLM, privately, on your own GPU.](https://offshoreserv.com/blog/self-host-llm-gpu-server) - [Dedicated vs cloud GPU Your break-even hours, and privacy.](https://offshoreserv.com/blog/dedicated-gpu-vs-cloud-gpu) - [RTX 4090 servers 24 GB of VRAM for $84.99/mo.](https://offshoreserv.com/offshore-gpu-servers/rtx-4090) - [H100 servers 80 GB of HBM3, up to 4 × H100.](https://offshoreserv.com/offshore-gpu-servers/h100) ## Your own GPU, away from the big clouds. 1. Pick a GPU and a jurisdiction 2. Pay in crypto, no ID asked 3. SSH in within 1 to 24 hours From $61.99/mo · dedicated cards · CUDA preinstalled --- OffshoreServ is an offshore hosting provider: VPS, dedicated servers, Windows RDP and GPU servers in seven jurisdictions (Iceland, Switzerland, Moldova, Romania, the Netherlands, Bulgaria and Malaysia), paid only in cryptocurrency (Bitcoin, Ethereum, Monero, Tether (USDT) and Solana), with no identity checks (no KYC). Prices and plans: https://offshoreserv.com/pricing · Answers: https://offshoreserv.com/faq · Every page: https://offshoreserv.com/llms.txt