Builder Workflows
How much hardware do you actually need? It depends on your workflow. Pick the setup that matches how you build with AI.
Basic Coding Assistant
Run a single local coding model for code completion and chat. The entry-level builder setup: replace API-dependent code completion with a local 7-8B model.
VRAM
5.8 GB
Models
1
API savings
$30/mo
Break-even
25 mo
Recommended build
Budget AI Desktop
$684
Power Coding Workflow
Run a dedicated 32B coding model with embeddings for local RAG. The sweet spot for developers who want serious local AI coding without API dependency.
VRAM
18.9 GB
Models
2
API savings
$80/mo
Break-even
12 mo
Recommended build
AI Builder Workstation
$2,773
Full AI Builder
The complete local AI development stack: concurrent coding model + reasoning model + embeddings. Switch between QwQ for architecture decisions and Qwen Coder for implementation, with local RAG always available.
VRAM
18.9 GB
Models
4
API savings
$150/mo
Break-even
8 mo
Recommended build
AI Builder Workstation
$2,773
Mac AI Builder
The silent, unified-memory approach: Apple Silicon with enough memory to run coding + reasoning + embeddings concurrently. No fan noise, no separate GPU. The premium option for builders who value silence and simplicity.
VRAM
27.3 GB
Models
3
API savings
$100/mo
Break-even
35 mo
Recommended build
Mac Studio AI Builder
$3,999
Home AI Server
Always-on local AI server for a household or small team. Runs Ollama + Open WebUI accessible from any device on the network. Serves chat, coding assistance, document Q&A, and transcription to multiple simultaneous users, with zero API costs and complete data privacy.
VRAM
7 GB
Models
3
API savings
$80/mo
Break-even
10 mo
Recommended build
Budget Home AI Server
$1,063
Model Fine-Tuning & Training
Fine-tune language models locally with QLoRA, LoRA, and full fine-tuning. Train custom adapters for domain-specific tasks without sending proprietary data to third-party APIs. VRAM requirements scale with model size and method: QLoRA fine-tuning a 7B model fits in 16GB, while full fine-tuning of 32B models needs 48GB+. System RAM matters: gradient checkpointing and dataset loading use 2-4x the model's VRAM in system memory.
VRAM
10 GB
Models
3
API savings
$200/mo
Break-even
10 mo
Recommended build
Mid-Range AI Workstation
$1,119
AI Image & Video Generation
Local image and video generation with FLUX.1, SDXL, and Stable Diffusion 3. Run ComfyUI workflows with LoRAs, ControlNet, and upscaling: no cloud credits, no content filters, no rate limits. VRAM is the bottleneck: FLUX.1 at full quality needs 24GB, but Q4 quantization brings it to 8GB GPUs.
VRAM
13 GB
Models
3
API savings
$60/mo
Break-even
15 mo
Recommended build
Mid-Range AI Workstation
$1,119