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[ Use case · Photoreal portraits ]

Best AI tools for photoreal portraits and characters

Photoreal portrait work has shifted hard toward Flux since 2024. Whether Flux beats SDXL for you depends on whether you have the VRAM, and whether you need consistent characters across frames.

VRAM FLOOR FOR THIS WORKFLOW
[ WORKFLOW PLAN ]

Decide in this order

  • Define the output: resolution, duration or context, batch/concurrency, and how often you will run it.
  • Set hard constraints: platform, privacy, license, VRAM/RAM, and whether slow CPU offload is acceptable.
  • Choose the workflow: eliminate tools that fail a hard constraint, then compare ecosystem, reproducibility, and switching cost.

The catalogue picks below are a shortlist, not proof that every default configuration fits. Open each datasheet and verify the exact model or extension you intend to use.

Evidence companion

ComfyUI VRAM planning

See the assumptions, official sources, and memory trade-offs behind this workflow.

Read the guide →

Our picks

06 MATCHED

ComfyUI

The nodal workflow engine for serious diffusion.

OPEN SOURCE6–16 GB VRAM
VRAM fit6–16 GB

Diffusers

Hugging Face's go-to library for every diffusion model.

OPEN SOURCE4–12 GB VRAM
VRAM fit4–12 GB

FLUX.1 [dev]

12B parameter open-weight diffusion model.

OPEN SOURCE8–24 GB VRAM
VRAM fit8–24 GB

✓ WHAT TO LOOK FOR

  • Flux.1 [dev] support at FP8 or NF4 (8 GB+)
  • IPAdapter / InstantID / PuLID for character consistency
  • Inpainting + face restoration in the same pipeline
  • Quantization options to dial VRAM use

! HONEST TRADE-OFFS

  • Check the exact model version and current license before commercial use
  • Aggressive quantization can improve fit, but quality and compatibility are workload-dependent
  • Truly consistent characters still need LoRA training in many cases

GOING DEEPER //

BUILD A FULL STACK →Image generation →12 GB VRAM stack →