Do we really need more 5B general-purpose image models?
The pattern I keep seeing: larger DiTs tend to produce more coherent images.
Proof1 community thread
Key points
- I’d rather have a larger model in INT4 than a smaller one at full precision.
- FLUX 2 Klein 9B is a perfect example: in my testing, it’s better than FLUX 3 Klein in practically every aspect of image quality—even with the updated FLUX 3 workflow.
- • Around 5B: too many compromises for a general-purpose model.
- Krea 2 with an INT4 DiT and INT4 text encoder runs well on an 8 GB GPU in my setup.
Sources (1)
- [1]Do we really need more 5B general-purpose image models?r/StableDiffusion (top, day) · Oct 17, 09:00 PM
The pattern I keep seeing: larger DiTs tend to produce more coherent images.
I’d rather have a larger model in INT4 than a smaller one at full precision.
Extractive summary: sentences quoted from the sources.
Before this
- Oct 17, 2026MOSS-Image LoRA training is now in AcademiaSD LoRAlab Trainer Studio (Base and SFT, under 6 GB VRAM)
- Oct 17, 2026Nemotron 3.5 Bolt, Muse Spark Open, and a Fast LFM2.5 24B
- Oct 16, 2026FLUX.3 Klein is disappointing for image generation, but AMAZING for consistent photo editing
- Oct 15, 2026Granite Switch 4.1: Chat, Decisions, and Speech from One Endpoint
- Oct 15, 2026REKI: Registering Knowledge in VLAs
- Oct 15, 2026NVIDIA Nemotron 3.5 Super VL Powers Specialized Agents with Multimodal Reasoning
