Topic Hub

AI GPU Buying Guide

The GPU is the single most important component for AI workloads, and the market moves fast. New architectures, shifting prices, and evolving model requirements mean last year's advice is already outdated. This hub brings together our GPU comparisons, VRAM deep-dives, and benchmark roundups so you can make a confident buying decision — whether you're running inference on a budget, training models, or building a multi-GPU rig for production workloads.

Top Picks

NVIDIA GeForce RTX 5090

NVIDIA GeForce RTX 5090

$1,999 – $2,199

  • VRAM: 32GB GDDR7
  • CUDA Cores: 21,760
  • Memory Bandwidth: 1,792 GB/s
Check Price on Amazon
NVIDIA GeForce RTX 5080

NVIDIA GeForce RTX 5080

$999 – $1,099

  • VRAM: 16GB GDDR7
  • CUDA Cores: 10,752
  • Memory Bandwidth: 960 GB/s
Check Price on Amazon
NVIDIA GeForce RTX 4090

NVIDIA GeForce RTX 4090

$1,599 – $1,999

  • VRAM: 24GB GDDR6X
  • CUDA Cores: 16,384
  • Memory Bandwidth: 1,008 GB/s
Check Price on Amazon

Related Articles

Guide

NVIDIA Nemotron 3 Nano Omni — Local Hardware Guide (2026)

NVIDIA's first frontier-class multimodal open model runs on a single 16GB GPU. Here's the complete hardware buyer's guide: VRAM math, GPU picks, Apple Silicon options, tok/s estimates, and a decision tree for Nemotron 3 Nano Omni in 2026.

Read
Guide

Best Consumer GPU for Local LLM 2026 — Buyer's Guide (RTX 5090 / 4090 / 3090, B580, Apple Silicon)

The consumer-only buyer's guide to running 7B–70B models on your own desk in April 2026. Decisive single picks per budget tier — $500, $800, $1,500, $2,000 — with real street prices, tok/s ranges, and the used-3090 reality check the workstation-padded guides keep burying.

Read
Guide

Best AMD GPU for Local LLM Inference 2026 — A ROCm-First Buyer Guide (RX 7900 XTX, RX 9070 XT, Strix Halo, MI300X)

ROCm 7.2 finally fixed the AMD-for-AI software story. Here are the four AMD GPU buyer paths that matter in May 2026 — RX 7900 XTX at $899 for 24 GB, RX 9070 XT at $600 for the mid-range, Strix Halo unified memory at sub-$2,500, and MI300X / MI250X for self-hosted production — plus the explicit don't-buy cards.

Read
Guide

DeepSeek V4-Flash Local Hardware Guide 2026 — What It Actually Takes to Run a 284B MIT-Licensed MoE

DeepSeek V4-Flash dropped April 24 under MIT license: 284B total / 13B active, 1M context, Claude Haiku-tier API pricing. Here's what hardware actually runs it locally — five priced buyer paths from $5,999 Mac Studio to $11K RTX PRO 6000, the 90 GB don't-bother cutoff, and why the MoE active-parameter math reframes every decision.

Read
Guide

Qwen 3.6-35B-A3B Local Hardware Guide 2026: The $800 GPU That Now Runs a Frontier MoE

Alibaba's Qwen 3.6-35B-A3B (released 2026-04-16, Apache 2.0) is the first frontier-class open coding model that runs usefully on a single used RTX 3090 — because only ~3B of its 35B parameters are active per token. Full quantization table, five priced buyer paths from $249 to $2,000, Mac Studio unified-memory coverage, and the MoE math that explains why an $800 GPU now keeps up.

Read
Guide

Qwen3-Coder-Next Local Hardware Guide 2026 — VRAM, GPU & Memory You Actually Need

Qwen3-Coder-Next is the first frontier coding model that's realistically local. 80B total / 3B active MoE, 256K context, 58.7% SWE-bench Verified — and it runs on a single RTX 5090 with 64GB of system RAM. Full VRAM math by quantization, buyer-tier builds from $1,500 to $10,000, Mac Studio coverage, and the agent-loop reality check no one else is writing.

Read
Guide

Best Local LLM for Every RTX 50 Series GPU (2026 Model-GPU Matrix)

You already own (or are about to buy) an RTX 50 card — here's exactly which local LLM to run on it. Model-to-GPU matrix for the RTX 5090, 5080, 5070 Ti, 5060 Ti 16GB, 5060 and 5050, with Q4 VRAM math, multimodal overhead, MoE corrections, and real tok/s benchmarks.

Read
Guide

Qwen 3.5 Local Hardware Guide 2026: Every Model from 0.8B to 397B

Qwen 3.5 rewrites the local AI playbook with native multimodal, 262K context, and hybrid MoE. Here's exactly which GPU, Mac, or mini PC you need for every model size — with VRAM math, tok/s benchmarks, and price-tiered recommendations from $250 to enterprise.

Read
Guide

Running Google Gemma 4 Locally: Complete Hardware Guide (2026)

Gemma 4 just dropped with four model sizes under Apache 2.0. Here's exactly which GPU, Mac, or edge device you need to run every variant locally — from the 2B edge model to 31B Dense — with VRAM tables, benchmarks, budget tiers, and setup instructions.

Read

Guides