Will It Run AI

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A hub for hardware compatibility guides, VRAM requirements, GPU and Mac picks, and local AI explainers. Find the specific model or topic you need in the posts below.

flux

FLUX.2 Dev VRAM Requirements — FP16, FP8, NF4, GGUF Hardware Guide (2026)

FLUX.2 Dev VRAM requirements at every precision level. Full FP16 needs ~64 GB (32B + Mistral 24B text encoder). FP8 ~32–35 GB, NF4 ~18–20 GB. Best GPUs and setup tips for local image generation.

flux

FLUX.2 Klein 9B VRAM Requirements — FP16, FP8, GGUF Hardware Guide (2026)

FLUX.2 Klein 9B needs ~29 GB at FP16 and ~15 GB at FP8. Full VRAM table, GPU recommendations, and comparison with the 4B sibling and FLUX.2 Dev.

openai

GPT-OSS 20B VRAM Requirements — RTX 4060 Ti, RTX 4070, RTX 4090, Apple Silicon Guide

GPT-OSS 20B (21B MoE, 3.6B active) needs ~12 GB at Q4_K_M. Runs on RTX 4060 Ti 16GB, RTX 4070 12GB, and Apple Silicon. Full VRAM table and per-GPU verdicts.

video-generation

HunyuanVideo 1.5 VRAM Requirements — FP16, FP8, and Practical GPU Guide (2026)

HunyuanVideo 1.5 (8.3B T2V+I2V) is far more consumer-friendly than the 13B original. VRAM table at FP16/FP8/GGUF, recommended GPUs from 12 GB to 48 GB.

pony-diffusion

Pony Diffusion V6 XL VRAM Requirements — GPU Guide & Hardware Recommendations

Pony Diffusion V6 XL VRAM requirements: ~7.5 GB at FP16, runs on any 8GB GPU. Best GPUs, LoRA stacking tips, and how it compares to SDXL and Flux for anime and stylized art.

qwen

Qwen2.5-Coder 14B VRAM Requirements — Q4, Q5, Q8, FP16 Hardware Guide

Exact VRAM for Qwen2.5-Coder 14B at every quantization level. Q4_K_M needs ~8.7 GB, Q8 needs ~14.7 GB. Best GPUs and Macs for local coding inference.

stable-diffusion

SD 3.5 Medium VRAM Requirements — 8GB GPU Guide + SD 3.5 Medium vs SDXL

SD 3.5 Medium needs ~6 GB at FP16 and fits on any 8GB GPU. Full VRAM table (FP16/FP8/Q4), minimum GPU list, and SD 3.5 Medium vs SDXL comparison.

video-generation

Wan 2.1 / 2.2 VRAM Requirements — 1.3B, 5B, 14B Variant GPU Guide (2026)

Wan Video 2.2 VRAM: 1.3B needs 4–6 GB (GGUF), 5B TI2V 8–12 GB, 14B 6–24 GB (FP8). Recommended GPUs and T5 offloading guide for every tier.

deepseek

DeepSeek-V4 VRAM Requirements - Million-Token Local Inference Guide

DeepSeek-V4-Pro and DeepSeek-V4-Flash hardware guide: practical VRAM estimates, 1M context implications, Think Max memory planning, multi-GPU setups, and Mac guidance.

granite

Granite 4.1 VRAM Requirements - IBM 3B, 8B, and 30B Hardware Guide

Exact practical VRAM estimates for IBM Granite 4.1 3B, 8B, and 30B at Q4, Q5, Q8, FP8, and BF16. Includes RTX, Apple Silicon, long-context, and enterprise RAG guidance.

nemotron

Nemotron 3 Nano Omni VRAM Requirements - Document, Audio, Video, and OCR Guide

NVIDIA Nemotron 3 Nano Omni 30B-A3B hardware guide: VRAM estimates for NVFP4, FP8, BF16, multimodal KV cache, OCR/document analysis, ASR, and video workloads.

qwen

Qwen 3.6 27B VRAM & Hardware Requirements — Dense 27B GPU Guide (2026)

Qwen 3.6 27B: Q4_K_M ~16.8 GB fits RTX 4080 16GB. Flagship coding (77.2% SWE-bench) on a consumer GPU — GPU/Mac buyer guide and GGUF picks.

apple-silicon

Best Coding LLMs for Apple Silicon 24GB — Ranked 2026

Top local coding LLMs for 24GB Apple Silicon (M4 Pro, M3 Pro): Qwen3 Coder 30B, Qwen3.5-35B-A3B, DeepSeek Coder V2.5 ranked by SWE-bench and tok/s.

macbook

MacBook Air M4 vs MacBook Pro M4 for Local LLMs — Which to Buy (April 2026)

MacBook Air M4 vs Pro M4 for local LLMs: 24GB unified memory, tok/s benchmarks, thermal limits, and which one fits Qwen3.6-35B-A3B. Decision guide with exact specs.

qwen

Qwen 3.6 27B vs Gemma 4 27B — Dense Head-to-Head (April 2026)

Qwen3.6-27B dense vs Gemma 4 27B dense: SWE-bench 77.2 vs 78.5 but Qwen wins Terminal-Bench 59.3 and AIME 94.1. VRAM (16.8 vs 16 GB), coding, vision, 1M context.

qwen

Qwen3.6-35B-A3B Hardware Requirements — What GPU or Mac to Buy (2026)

Qwen3.6-35B-A3B hardware requirements: which GPU, Mac, or workstation to buy. Price vs VRAM vs tok/s for RTX 4090, RTX 5090, Mac M4 Pro/Max, H100. Q4/Q5/Q8 guidance.

qwen

Qwen3.6-35B-A3B Release Date — Open-Weight & GGUF Timeline (April 2026)

qwen3.6-35b-a3b release date status: API launched April 2, 2026; open-weight GGUF for the 35B-A3B MoE expected late April / early May 2026. Latest timeline and links.

vram

What Can You Run on 16GB, 24GB, 32GB VRAM? — Local LLM Guide (April 2026)

What local LLMs fit on 16GB, 24GB, or 32GB VRAM in 2026: top model per tier with Q4/Q8 numbers, tokens/sec on RTX 4080/4090/5090, coding picks, and when to upgrade.

mistral

Mistral VRAM Requirements (2026) — Will Your GPU Run 7B, Nemo 12B, Codestral 22B or Small 24B?

Mistral 7B needs ~4.3GB at Q4. Nemo 12B ~7.1GB. Codestral 22B ~12.8GB. Small 24B ~13.4GB. Full Q4/Q5/Q6/Q8 VRAM tables with 8GB/12GB/24GB GPU picks and Mac fit.

mlx

MLX vs Ollama on Apple Silicon (2026) — Real Benchmarks, Memory Usage & When to Use Each

MLX beats Ollama by 15-30% throughput on Apple Silicon and uses ~10% less memory. Full tok/s benchmarks for Qwen 3.5, Llama 4, Gemma 3 on M4 16GB → M3 Ultra 512GB.

quantization

Q4_K_M vs Q5_K_M vs Q8 — Which GGUF Quantization Should You Use? (2026 Guide)

Q4_K_M saves 72% VRAM with minor quality loss. Q5_K_M is the sweet spot. Q8 is near-lossless but 2x larger. Full comparison with VRAM, perplexity, and speed by model size.

qwen

Qwen 3.5 122B-A10B VRAM Requirements — MoE Workstation & Mac Studio Guide (Q4, Q5, Q6, Q8)

Qwen 3.5 122B-A10B needs ~74.4 GB at Q4_K_M. Fits on A100 80GB, H100, Mac Studio M4 Max 128GB, or M3 Ultra. Full VRAM table, benchmarks, and multi-GPU guidance.

qwen

Qwen 3.5 27B VRAM Requirements — Dense Model Hardware Guide (Q4/Q5/Q6/Q8)

Qwen 3.5 27B needs ~16.5 GB at Q4_K_M on RTX 4090. See also the newer Qwen3.6-27B (April 22, 2026) which needs 16.8 GB Q4 and beats it on coding benchmarks.

qwen

Qwen3.5-35B-A3B VRAM Requirements 2026 — 21.4 GB at Q4

Qwen3.5-35B-A3B needs ~21.4 GB at Q4_K_M. Fits RTX 4090/3090 and Mac M4 Max. Exact Q4/Q5/Q6/Q8 GGUF numbers, tok/s benchmarks, and GPU recommendations.

qwen

Qwen 3.5 9B VRAM Requirements — Best 8B-Class Dense Model (Q4, Q5, Q6, Q8)

Qwen 3.5 9B needs ~5.5 GB at Q4_K_M and ~9.6 GB at Q8_0. Runs well on 8 GB GPUs, comfortably on 12 GB. Full VRAM table, Mac fit, and tokens/second benchmarks.

qwen

Qwen 3.5 9B vs Llama 3.1 8B (2026) — VRAM, Speed, Quality & Which Should You Run?

Head-to-head: Qwen 3.5 9B vs Llama 3.1 8B for local inference. VRAM (5.5 vs 4.9 GB Q4), tokens/sec on RTX 4090, MMLU, context, multilingual, and which wins per use case.

qwen

Qwen 3.5 on Apple Silicon MLX (2026) — Memory Usage, Tokens/sec & Setup Guide

Qwen 3.5 35B-A3B MLX 4-bit uses ~19.5 GB on Mac. 9B fits 16 GB Macs at 25-35 tok/s. Full MLX memory + speed benchmarks per variant from M4 16GB to M3 Ultra 512GB.

qwen

Qwen 3.6 VRAM & Hardware Requirements — 35B-A3B MoE GPU Guide (2026)

Qwen 3.6 35B-A3B MoE: Q4_K_M ~21 GB, fits RTX 4090 24GB or Mac M4 Pro. Q8 ~37 GB needs 48 GB class. GPU and Mac buyer guide for 1M-context MoE.

qwen

Qwen 3 Coder 30B-A3B vs DeepSeek R1 Distill 14B for Local Coding (2026)

Head-to-head for local coding: Qwen 3 Coder 30B-A3B (MoE, 17GB Q4) vs DeepSeek R1 Distill Qwen 14B (dense, 8GB Q4). HumanEval, speed, reasoning, and which to run on 12GB/24GB GPUs.

vram

AI Model VRAM Requirements (2026) — Exact GPU Memory for 182+ LLMs, Flux, SDXL & Video

Will your GPU run it? Exact VRAM for 182+ AI models (Qwen 3.5, Gemma 4, Llama 4, DeepSeek R1, Flux, SDXL, video) at Q4/Q8/FP16, with 8GB/12GB/24GB/48GB GPU picks.

gemma

Gemma 3 12B VRAM Requirements - Q4, Q5, Q6, Q8 Hardware Guide

Exact VRAM for Gemma 3 12B at Q4_K_M, Q5_K_M, Q6_K, Q8_0, and FP16. Gemma 3 12B needs ~6.7GB at Q4 and ~12.6GB at Q8.

gemma

Gemma 3 VRAM Requirements — 1B, 4B, 12B, 27B GPU & Mac Guide (2026)

Exact VRAM for Gemma 3 1B, 4B, 12B, and 27B at Q4, Q8, and FP16. Gemma 3 12B needs ~6.7GB at Q4, 27B needs ~15.1GB. Full GPU and Mac recommendations for 2026.

minimax

MiniMax M2.7 VRAM Requirements - 230B MoE Agentic Model Hardware Guide

Exact VRAM for MiniMax M2.7 (230B total, 10B active MoE) at Dynamic 4-bit, Q2, Q3, Q4, Q5, Q8, and BF16. Includes Mac, multi-GPU, and partial offload scenarios.

mistral

Mistral Small 4 VRAM Requirements - 119B Hardware Guide

Exact VRAM for Mistral Small 4 119B at Q4_K_M, Q5_K_M, Q6_K, Q8_0, and FP16. See whether 80GB GPUs or high-memory Macs can run it locally.

qwen

Qwen 3 GPU Requirements — Original Family (0.6B–235B) VRAM Guide (2026)

VRAM tables for the original Qwen 3 family (0.6B to 235B-A22B), with GPU and Mac recommendations. For the newer Qwen 3.5 and Qwen 3.6 generations, see the dedicated pages linked below.

mac

Best LLM for 16GB Mac — What Actually Runs Well on Apple Silicon

The best local LLMs for a 16GB Mac in 2026. Which 4B, 8B, 9B, and 12B models fit well, when 14B becomes annoying, and whether to use MLX, Ollama, or LM Studio.

intel-arc

Intel Arc vs CUDA for Local AI — When Arc Makes Sense and When NVIDIA Is Safer

Should you buy Intel Arc for local AI, or stick with CUDA? A practical guide to Arc B580, Arc A770, RTX 3060, RTX 4060, and RTX 4070-class GPUs for local LLMs.

qwen

Qwen 3.5 on RTX 4090 — VRAM, Tokens/s, Best Runtime, and What Actually Fits

How well does Qwen 3.5 run on an RTX 4090 24GB? Practical guidance for Qwen 3.5 9B, 27B, and 35B A3B with VRAM requirements, tok/s estimates, and runtime tradeoffs.

hardware

Best Local AI Builds in 2026 - Budget, Inference, Training, and Multi-GPU Workstations

Recommended local AI PC builds by budget and use case. Practical guidance for single-GPU inference desktops, dual-GPU workstations, and multi-GPU servers, with CPU, RAM, ECC, motherboard, storage, and power advice.

software

Best Software for Running Local AI in 2026 - Ollama, llama.cpp, LM Studio, vLLM, ComfyUI & More

The practical software stack for local AI in 2026. When to use Ollama, llama.cpp, LM Studio, vLLM, ExLlamaV2, ComfyUI, and other tools for LLMs, image generation, video generation, and local serving.

glossary

Local AI Build Glossary in 2026 - PCIe, ECC, NVLink, Offload, Bifurcation & More

The practical glossary for local AI builders. Understand PCIe lanes, ECC RAM, bifurcation, RDIMM vs UDIMM, NVLink, offload, tensor parallelism, KV cache, VRAM headroom, and the hardware terms that matter when building an AI workstation.

hardware

How to Build a Local AI Workstation in 2026 - CPU, RAM, ECC, PCIe Lanes & Motherboards

A practical hardware guide for local AI builders. Learn how to choose the right CPU platform, RAM capacity, ECC memory, PCIe lane budget, motherboard, storage, and cooling for 1x, 2x, and 4x GPU systems.

pcie

PCIe Lanes for Local AI Explained - CPUs, Motherboards, Bifurcation & Multi-GPU Builds

PCIe lane math for local AI. Understand x16 vs x8, CPU-attached NVMe, chipset bottlenecks, bifurcation, PCIe switches, and how many lanes you really need for 1, 2, or 4 GPUs.

gpu

Best AI Models for 24GB VRAM — RTX 4090 & RTX 5090 (LLMs, Image & Video)

RTX 4090 (24GB) runs 30B models, Flux at FP8, and video generation. RTX 5090 (32GB) adds 70B MoE models. Complete guide with VRAM tables and speed estimates.

gpu

Best AI Models for 8GB VRAM — What Actually Runs on RTX 4060, RTX 3070, Arc B580

15 AI models that fit in 8GB VRAM: Qwen 3.5 4B, Phi-4 Mini, Gemma 3 4B for LLMs. SD 1.5, SDXL for images. Complete VRAM breakdown at Q4, Q5, Q8.

mac

Best AI Models for 16GB Mac — LLMs, Image, and Video That Actually Fit

The best AI models you can run on a 16GB Mac. Qwen 3 8B, Gemma 4 E4B, Phi-4 Mini, Stable Diffusion, and Flux — with practical memory guidance and setup advice for Ollama, LM Studio, and MLX.

reasoning

Best Reasoning Models to Run Locally in 2026 — VRAM Guide from 2GB to 40GB

Complete guide to reasoning models you can run locally: DeepSeek R1 distills, QwQ 32B, Phi-4 Reasoning, Gemma 4 MoE. VRAM requirements, GPU tiers, and thinking token speed tips.

gemma

Gemma 4 GPU & VRAM Requirements 2026 — 26B MoE Fits 15 GB

Gemma 4 VRAM: E2B ~3GB, E4B ~5GB, 26B MoE ~15GB, 31B dense ~18GB at Q4. RTX 4090/M4 Pro fit the 26B. Gemma 4 31B vs Qwen 3.6 27B — GPU picks included.

vram

Image Generation VRAM Requirements 2026 — Flux, SDXL, SD 3.5

Flux.1 needs 7 GB at GGUF Q4; SDXL fits on 8 GB. FP16/FP8/GGUF VRAM tables for Flux.1, Flux.2, SDXL, SD 3.5, Pony Diffusion — GPU picks by tier for 2026.

video-generation

Video Generation VRAM Requirements 2026: Every AI Video Model GPU Guide

Complete GPU and VRAM requirements for AI video generation in 2026. FP16 vs FP8 vs GGUF comparison for LTX Video, Wan Video, HunyuanVideo, CogVideoX, Mochi 1, and AnimateDiff. What you can actually run on 8GB, 12GB, 24GB, and 48GB GPUs.

mac

Best LLM for Mac 2026: Picks for M1/M2/M3/M4 by RAM Tier

The best local LLM for your exact Mac — by memory tier from M1 16GB to M3 Ultra. Model picks, quant levels, tok/s, and MLX vs llama.cpp, no guesswork.

deepseek

DeepSeek R1 VRAM Requirements — 7B to 671B Hardware Guide

Exact VRAM requirements for every DeepSeek R1 variant at Q4, Q8, and FP16 quantization. Covers the 7B, 14B, 32B, 70B distills and the full 671B MoE model with GPU recommendations for each size.

qwen

Qwen 3.5 VRAM Requirements — 9B, 27B, 35B-A3B, 122B-A10B

Exact VRAM for Qwen 3.5 9B, 27B, 35B-A3B, and 122B-A10B at Q4, Q5, Q6, Q8, and FP16. Includes RTX 4090, Apple Silicon, and MLX vs GGUF guidance.

apple-silicon

Apple Silicon for AI: M4 vs M3 vs M2 Comparison (2026)

Compare M4, M3, and M2 Apple Silicon chips for local AI inference. Unified memory advantages, performance benchmarks, and which Mac to buy for running LLMs and image models.

apple-silicon

Apple Silicon for AI: M4 vs M3 vs M2 Comparison

How do M2, M3, and M4 compare for running AI models locally? A practical breakdown of bandwidth, memory tiers, LLM performance, and which generation is worth buying for local AI workloads in 2026.

gpu

Best GPU for Running AI Models at Home (2026)

Complete GPU buyer's guide for home AI inference in 2026. RTX 4060 through RTX 5090 compared by VRAM, price, and performance. Find the right GPU for your budget.

vram

How Much VRAM Do You Need to Run LLMs Locally? (2026 Guide)

Practical VRAM requirements for running LLMs locally in 2026. From 7B to 405B models, quantization impact, and hardware recommendations for every budget.

quantization

Quantization Explained: Q4 vs Q8 vs FP16 — What You Actually Lose

Plain-English explanation of AI model quantization. What Q4, Q8, and FP16 mean, how much quality you lose at each level, and which to use for your hardware.

gpu

Best GPU for AI in 2026 — LLMs, Image Generation, and Video Generation

The ultimate GPU buying guide for all AI workloads in 2026. Budget to professional tier recommendations for running LLMs, Flux, SDXL, Wan Video, and more locally with VRAM requirements and use-case advice.

flux

Flux vs Midjourney — Local vs Cloud Image Generation in 2026

Flux 2 Dev vs Midjourney v6 compared head-to-head. Quality, cost, privacy, speed, customization, and hardware requirements. Find out which image generator is right for you.

flux-2

How to Run Flux 2 Locally — Hardware Requirements & Setup Guide

Complete guide to running Flux 2 Dev and Flux 2 Klein 4B on local hardware. VRAM requirements, ComfyUI workflows, diffusers code, FP8 optimization, and comparison with Flux 1.

apple-silicon

M4 Max for AI — Running Local Models on Apple Silicon

Complete guide to running AI models locally on the Apple M4 Max. Covers unified memory advantages, LLM performance, image and video generation, MLX vs llama.cpp, and how the M4 Max compares to NVIDIA GPUs and the M4 Pro.

qwen

Qwen Image — Running Alibaba's 20B Diffusion Model Locally

Guide to running Qwen Image locally. Hardware requirements for its 20.4B DiT transformer and 8.3B Qwen2.5-VL text encoder, diffusers setup, VRAM optimization, and comparison with Flux.

rtx-4060

RTX 4060 8GB for AI — The Budget AI GPU Guide

Complete guide to running AI models on the NVIDIA RTX 4060 with 8GB VRAM. Covers which LLMs, image generation, and video generation models fit, practical tips for maximizing 8GB, and when to upgrade.

rtx-5090

RTX 5090 for AI — What Can You Run? Complete Guide

Complete guide to running AI models on the NVIDIA RTX 5090 with 32GB VRAM. Covers LLMs, image generation, video generation, NVFP4/NVFP8 support, and whether upgrading from the RTX 4090 is worth it.

stable-diffusion

Stable Diffusion vs Flux in 2026 — Which Model Should You Use?

Complete comparison of SD 1.5, SDXL, SD 3.5, Flux 1, and Flux 2 for local image generation. VRAM requirements, quality, ecosystem maturity, and which model to choose based on your hardware budget.

image-generation

Best Local Image Generation Models in 2025 — Complete Guide

Compare the best AI image generation models for local hardware: Flux.1, SDXL, SD 3.5, SD 1.5, and top community fine-tunes. VRAM requirements, quality, and ecosystem for each.

flux

Flux vs SDXL vs SD 3.5 — Which Image Model Should You Choose?

Side-by-side comparison of Flux.1, Stable Diffusion XL, and SD 3.5 for local image generation. Quality, VRAM requirements, speed, ecosystem, licensing, and recommendations by use case.

flux

How to Run Flux Locally — Complete Hardware & Setup Guide

Step-by-step guide to running Flux.1 Dev and Schnell on local hardware. Hardware requirements, ComfyUI setup, diffusers code, GGUF quantization, ControlNet support, and performance optimization tips.

multi-gpu

2x RTX 4090 for LLMs: What You Can Run, Setup Guide & Real Performance (2026)

Can two RTX 4090s run Llama 70B or Qwen 72B? We break down the real performance of dual 4090 setups for local LLM inference — VRAM pooling, PCIe limitations, and what models you unlock.

multi-gpu

Multi-GPU LLM Inference Guide — NVLink vs PCIe, Tensor Parallelism (2026)

Multi-GPU LLM inference: real NVLink vs PCIe scaling numbers, tensor parallelism sizing, 2×/4×/8× GPU configs for Llama 3.3 70B and Qwen 3.5 122B, and exact tokens-per-second across consumer and datacenter hardware.

ollama

Ollama Multi-GPU Support: Official Behavior, Layer Split & Setup (2026)

How Ollama officially handles multiple GPUs: auto-detection, layer distribution, num_gpu parameter, CUDA_VISIBLE_DEVICES, and real 2× RTX 4090 / 2× RTX 3090 performance numbers for Llama 70B and Qwen 3.5.

vllm

vLLM Multi-GPU Setup: How Many GPUs You Actually Need (2026)

Stop guessing --tensor-parallel-size. Exact GPU counts + VRAM per model: Llama 70B = 2×RTX 4090 or 1×H100. Copy-paste configs and a full sizing table.

local-ai

What LLM Can I Run Locally on My GPU or Mac? (2026 Calculator + Guide)

Find the best local LLM for your exact VRAM: 4GB, 8GB, 12GB, 16GB, 24GB, 32GB, 48GB, 64GB+. Ranked picks for each tier with quant, tok/s, and one-click calculator.

gpu

Best GPU for Running LLMs Locally (2026) — RTX 4060 to H100 Buyer's Guide

RTX 4060 runs 8B models, RTX 4090 handles 30B, Mac M4 Max fits 70B. Compare every GPU for local AI with real VRAM data, speed benchmarks, and model counts.

getting-started

Getting Started with Local AI: Run LLMs on Your Own Hardware

Step-by-step guide to running AI models locally. Install Ollama, pick the right model for your hardware, and start generating in under 5 minutes.

deepseek

DeepSeek R1 VRAM Requirements — 7B to 671B Distills at Q4/Q8 (GPU Guide)

DeepSeek R1 14B needs ~8GB at Q4, 32B needs ~18GB, full 671B needs ~376GB. Complete VRAM tables for every distill with GPU and quantization recommendations.

llama

Llama 4 VRAM Requirements — Scout 109B & Maverick 400B (GPU & Mac Guide)

Llama 4 Scout needs ~61GB at Q4, Maverick needs ~224GB. Complete VRAM tables for every quantization level with GPU and Mac hardware recommendations.

video-generation

Best AI Video Generation Models for Local Hardware in 2025

Compare the best open-source AI video generation models for local use: Wan Video 2.1, LTX Video, HunyuanVideo, CogVideoX, Mochi 1, and AnimateDiff. Accurate VRAM requirements by configuration, quality, and setup for each.

gpu

Best GPU for AI Image Generation in 2025 — Local Flux, SDXL, SD 3.5

Complete GPU buying guide for local AI image generation. Budget to professional tier recommendations for Flux, SDXL, and SD 3.5 with VRAM requirements, performance benchmarks, and use-case advice.

comfyui

ComfyUI Beginner's Guide — Set Up Local AI Image Generation

Step-by-step ComfyUI installation and setup guide for local AI image generation. Learn text-to-image workflows, ControlNets, LoRAs, and VRAM optimization with SDXL, Flux, and SD 3.5.

sdxl

SDXL LoRA Guide — Styles, Characters & Quality LoRAs for Local AI Art

Complete guide to SDXL LoRAs for local AI image generation. How LoRAs work, where to find them, top recommended LoRAs by category, ComfyUI and A1111 usage, stacking tips, and VRAM impact.