🖥️ Local Deployment Guide
Hardware requirements and cost estimates for running LLMs on-premise.
Entry
Development / POC
€ 500,00
/month (hardware rental)
GPUs 1x
GPU Memory 24 GB
CPU Cores 8
RAM 32 GB
Storage 500 GB
Setup Time 1 days
Models Supported
7B-13B parameter models
Recommended
Standard
Production (Small)
€ 2.500,00
/month (hardware rental)
GPUs 2x
GPU Memory 48 GB
CPU Cores 32
RAM 128 GB
Storage 2000 GB
Setup Time 5 days
Models Supported
Up to 70B parameter models
Enterprise
Production (Enterprise)
€ 15.000,00
/month (hardware rental)
GPUs 8x
GPU Memory 640 GB
CPU Cores 128
RAM 512 GB
Storage 10000 GB
Setup Time 14 days
Models Supported
Any model including 405B
Tier Comparison
Development / POC
Small-scale testing and development
Pros
✓ Low cost
✓ Quick setup
✓ Good for testing
Cons
✗ Limited model size
✗ Low throughput
Production (Small)
Production workloads with moderate traffic
Pros
✓ Good balance of cost/performance
✓ Production-ready
Cons
✗ Limited redundancy
✗ Single point of failure
Production (Enterprise)
High-availability enterprise deployment
Pros
✓ High availability
✓ High throughput
✓ Multiple models
Cons
✗ High cost
✗ Complex setup
✗ Requires expertise
🎮 GPU Selection Guide
NVIDIA RTX 4090
24 GB VRAM
~€1,800
Best for: Development, 7B-13B models
NVIDIA A100
40-80 GB VRAM
~€10,000+ (or rent)
Best for: Production, up to 70B models
NVIDIA H100
80 GB VRAM
~€30,000+ (or rent)
Best for: Enterprise, 70B+ models, highest throughput
💰 Cost Comparison: Cloud vs Local
Break-even point: At ~100,000 API calls/month, local deployment often becomes more cost-effective than cloud APIs.
Example: GPT-4 at $0.03/1K tokens × 1M tokens = $30/month for basic usage. Heavy usage can reach $1,000+/month.
Local: After initial setup (~€500/month for Dev tier), marginal cost per query approaches €0.