How Much VRAM Do You Need to Fine-Tune an LLM? (Full vs LoRA vs QLoRA)
Fine-tuning needs far more VRAM than inference — roughly 8x. QLoRA fits a 7B fine-tune on a 24GB card; full fine-tuning does not. Here is the real math.
GPU recommendations for running AI locally, ranked by VRAM, software fit, current pricing, and practical tradeoffs. From $250 budget picks to $2,000 flagship cards - find the right hardware for your workload.
Start with Best GPU for Local LLMs, use the VRAM and hardware tools, then narrow down with the guide that matches your budget or model size.
Fine-tuning needs far more VRAM than inference — roughly 8x. QLoRA fits a 7B fine-tune on a 24GB card; full fine-tuning does not. Here is the real math.
Strix Halo, DGX Spark, Framework Desktop, or Mac Studio? The number that decides which mini PC runs your local LLM is usable VRAM, not total RAM. Here is the honest breakdown, plus a tool that ranks the machines for the model you want to run.
The used RTX 3090 lost its value crown. At about $1,600 used vs about $1,400 new, the RX 7900 XTX is now the cheapest way to 24GB of VRAM — if you can live without CUDA. Here is the honest tradeoff.
A local AI workstation is a VRAM budget with a computer attached. Pick the model first, then the card, then everything else. Three builds for 32B, 70B, and headroom.
RTX 3090 vs 4090 vs 5090 for local AI: verified specs, VRAM, memory bandwidth, the real performance gap, and which 24GB-or-more card is actually worth buying in 2026.
The best GPUs for Stable Diffusion, SDXL, and FLUX in 2026 by VRAM tier — what runs SDXL, what you need for FLUX, and the value picks, with honest pricing.
The best GPUs for local AI under $1,000 in 2026: available 16GB options plus the conditions a private-market RTX 3090 must meet to qualify.
16GB vs 24GB VRAM for local LLMs: exactly which models each tier runs, where 16GB gets frustrating, and how to decide without overspending on a GPU.
NVIDIA vs AMD for local LLMs in 2026: CUDA vs ROCm maturity, real performance, the RX 7900 XTX value case, and who should actually choose AMD.
RTX 5090 vs RTX 4090 for local AI: verified specs, VRAM, FP4, real performance gap, and current pricing reality. Which flagship to actually buy in 2026.
A realistic parts list for a budget local AI PC. A used 12GB GPU plus value CPU, RAM, SSD, PSU, and case — what to buy, what it really costs, and the tradeoffs.
A clear cost breakdown of running AI locally versus paying for ChatGPT. Real subscription and electricity numbers, the break-even math, and who should switch.
How to evaluate an RTX 3090 for local LLMs: 24GB model fit, live price checks, inspection steps, dual-GPU sharding, and when to skip it.
What Q4_K_M, Q5_K_M, Q8, and FP16 actually mean, how much VRAM each saves, and which quantization to pick for local LLMs without wrecking quality.
The used GPU market is still the best way to buy 24GB of VRAM without paying flagship money. Here is the used card that actually makes sense, the risks to check, and who should skip the second-hand route.
The best cheap GPUs for local AI right now, by spend level: what to buy under $300, under $500, and when a used RTX 3090 still changes the math.
VRAM requirements for every popular LLM at every quantization level. Llama 4, DeepSeek R1, Qwen 3, Mistral, Stable Diffusion — the only table you need.
GPUs compared for local AI inference by VRAM, power, software support, and reviewed listing ranges — from entry-level cards to the RTX 5090.