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/rigs · 3 reference builds · 100% independent

Reference builds
for AI rigs.

Three educational reference builds — GPU, VRAM, indicative build costs. What a good local AI rig looks like, with no commercial bias.

View configurations ↓Ask us for adviceWho is behind Localia
01 · Sovereignty

Sensitive data (legal, medical, HR, R&D) never leaves your walls. GDPR and AI Act compliant.

02 · Bounded cost

A Pro rig pays back in ~6 months versus €1500/month of API at scale. Marginal cost near zero afterwards.

03 · Updated models

How to keep up with new open-weight models, pick the right quantization and test a launch: our guides walk you through it step by step.

trust

What makes these builds reliable.

Localia is an independent resource: no stock, no fake benchmark. These builds are a reference to assemble the right rig yourself.

01

Justified components

Every GPU, VRAM and PSU choice is explained for a real local AI workload.

02

Transparent indicative costs

The amounts shown are estimated build costs at market price, not sale prices.

03

Documented performance

Which models run and their quantization are specified tier by tier.

04

Benchmarks to come

Real tokens/s measured on physical hardware will be published as soon as possible.

catalog

Three reference builds. Indicative costs.

estimated build costs · 2026 market price
// 01 · Solo dev · researcher · internal experiments

Starter

First solo AI rig

from
4 990 € HTex. VAT · parts
GPU · VRAM
1× RTX 509032 GB
Starter — Silent tower
Spec
  • ·AMD Ryzen 7 7700X (8C / 16T)
  • ·32 GB DDR5-6000
  • ·1 TB NVMe Gen 4
  • ·850 W 80+ Gold PSU
  • ·Component manufacturer warranties
Runs for example
  • ▸Llama 3.3 70B · Q3
  • ▸Qwen 2.5 32B · Q5
  • ▸Gemma 4 31B · Q5
  • ▸Mistral 7B · FP16
  • ▸DeepSeek R1 Distill 32B · Q5
Software
  • ·Ubuntu 24.04 LTS
  • ·NVIDIA drivers + CUDA
  • ·Ollama + Open WebUI (open-source, to install)
  • ·Optimised llama.cpp build
Open the calculator →
// 02 · Agency · SMB · firm · data team
popular

Pro

The team RAG rig

from
11 990 € HTex. VAT · parts
GPU · VRAM
2× RTX 509064 GB
Pro — 4U rack
Spec
  • ·AMD Ryzen 7 7700X (8C / 16T)
  • ·64 GB DDR5-4800 ECC UDIMM
  • ·1 TB NVMe Gen 4
  • ·1500 W 80+ Platinum PSU
  • ·Component manufacturer warranties
Runs for example
  • ▸Llama 3.3 70B · Q8
  • ▸DeepSeek R1 Distill 70B · Q8
  • ▸Qwen 2.5 72B · Q5
  • ▸Mixtral 8x7B · FP16
  • ▸Mistral Large 123B · Q4
Software
  • ·Everything in Starter +
  • ·vLLM with OpenAI-compatible server
  • ·RAG kit: LlamaIndex + Qdrant configured + README
  • ·CLI monitoring (nvidia-smi, htop, ollama logs)
Open the calculator →
// 03 · SME · law firm · medical · mid-market · public

Enterprise

AI sovereignty for SMEs

from
25 990 € HTex. VAT · parts
GPU · VRAM
2× RTX A6000 NVLink96 GB
Enterprise — 4U rack
Spec
  • ·AMD Threadripper Pro 7975WX (32C / 64T)
  • ·256 GB DDR5 ECC RDIMM
  • ·8 TB NVMe Gen 5 RAID 10
  • ·2000 W redundant PSU
  • ·Component manufacturer warranties
Runs for example
  • ▸Llama 3.3 70B · FP16
  • ▸Mistral Large 123B · Q5
  • ▸Qwen 2.5 72B · Q8
  • ▸Mixtral 8x22B · Q5
  • ▸Llama 4 Scout · Q5
Software
  • ·Everything in Pro +
  • ·Multi-GPU tensor parallel configured (NVLink)
  • ·Open WebUI multi-user · OIDC ready
  • ·GDPR / AI Act compliance docs included
Open the calculator →

indicative ex-VAT build costs (parts only, excl. assembly) · to be adapted to your use case · Localia does not sell, does not ship

◆ custom

Beyond the reference builds.

Everything beyond the standard builds: full RAG integration on your documents, Grafana dashboards, custom SSO (fine-grained RBAC, HDS-compliant audit), white-label UI, datacenter GPUs (H100 / H200 / B200 / MI300X), multi-rack, strict SLA, security audit, team training. Localia does not sell these services; we can point you to the right partners and help you scope the need.

H100 / H200MI300XMulti-rackStrict SLAEnterprise RAGSecurity auditTeam trainingMaintenance
Ask us for advice →
process

How to use these builds.

  1. 01
    Step 1

    Choose a build

    Find the reference build closest to your use case.

  2. 02
    Step 2

    Estimate the cost

    Open the calculator to estimate the build cost for your models.

  3. 03
    Step 3

    Source the components

    Buy the components yourself from the distributors of your choice.

  4. 04
    Step 4

    Install the stack

    Follow our guides to install Ollama, Open WebUI and the RAG stack.

faq

Frequently asked.

Does Localia sell these rigs?+
No. Localia is an independent resource: these builds are educational references to assemble your own rig. No stock, no sales, no shipping.
Which software stack should I use?+
Ubuntu 24.04 LTS · NVIDIA drivers · CUDA · Ollama · Open WebUI · llama.cpp · vLLM · RAG stack (LlamaIndex + Qdrant). All open-source, to install by following our guides.
Which models run on it?+
Depending on the build: Llama 3.3 70B, Mistral Large, Qwen 2.5 72B, DeepSeek R1, Gemma 4. The calculator tells you what fits in VRAM.
What about warranty?+
Each component keeps its own manufacturer warranty (GPU, motherboard, PSU, etc.). Localia is not a seller and therefore provides no warranty on the assembled whole.
What if I want to upgrade later?+
Every reference build is designed to accept +1 or +2 additional GPUs (free PCIe slots + sized PSU). Plan for it when buying the components.

Ready to run local?

A question about choosing a rig? Describe your case in two sentences: we'll point you to the right reference build — without selling you anything.

Ask us for advice →

Reply within 24 business hours · contact@getlocalia.com