FLUX.2 [dev] Turbo vs FLUX.2 [klein] 4B

Head-to-head across 1 challenge

FLUX.2 [dev] Turbo

0.0%

win rate

Ties

0.0%

FLUX.2 [klein] 4B

100.0%

win rate

0.0% 0.0% ties 100.0%

Challenge Results

The Halloween Invitation

Text-to-Image

“Vintage gothic Halloween party invitation. Dark parchment poster, spooky border with webs and thorns, central glowing jack-o-lantern, bats, twisted trees, moody night sky. Add elegant gothic title text saying "Halloween Party Invitation", a small scroll banner saying "You are invited to a night of frights", and event details at the bottom: Date: 30.10.2026 Time: 7pm Location: The Arches, NYC Spooky but polished, cinematic lighting, square format.”

FLUX.2 [dev] Turbo
FLUX.2 [klein] 4B
0% wins 0% ties 100% wins

AI Judge Analysis

FLUX.2 [dev] Turbo

  • + Perfect text rendering for all requested copy including complex details.
  • + Excellent gothic illustration style with consistent lighting.
  • + High fidelity in borders featuring both thorns and spider webs as requested.
  • The parchment texture is slightly less aged than Model B.

FLUX.2 [klein] 4B

  • + Effective moody atmosphere with a glowing moon in the background.
  • + Good use of the scroll banner for the secondary text.
  • Significant spelling errors in the title and details, such as 'Halllowon' and 'Imisation'.
  • The thorns and spider webs in the corner are less integrated into the 'parchment' border compared to the other model.

Verdict: FLUX.2 [dev] Turbo significantly outperforms the other model by accurately rendering every piece of requested text without spelling errors. While FLUX.2 [klein] 4B captures the requested atmosphere well, its failure to correctly spell common words like 'Invitation' or 'Location' makes it unusable as a party invitation.

FLUX.2 [dev] Turbo

Distilled version of Black Forest Labs' FLUX.2 [dev] outperforming it at a cheaper price. Developed by fal.ai.

FLUX.2 [klein] 4B

Black Forest Labs' compact, open-source image generation model with sub-second inference, optimized for production and near real-time applications with multi-reference support