Expired50% confidenceFactExact time
To run Stable Diffusion XL base version, an NVIDIA RTX 3060 (12GB VRAM) can perform inference smoothly; the full version of Flux.1-dev (FP16 precision) requires approximately 24GB of VRAM.
1
Sources
50%
Confidence
Medium-term (~90 days)
Relevance
7/12/2026
First Seen
This claim has expired. It is kept for the record and no longer describes the current state.
Valid until: 10/10/2026(expired)
Sources
In-Depth Comparison of AI Image Generation Tools: How to Choose Between Flux, Midjourney, and Gemini?
redditr/learnmachinelearning7/11/2026
Related Claims
UnverifiedNVIDIA graphics cards with 6 GB of VRAM or more (such as the GTX 1660 and RTX 3060) can run most Stable Diffusion models smoothly.81% similarUnverifiedFlux 基于扩散 Transformer(DiT)架构,与 SD 系列使用的 U-Net 架构不同,完整版需要约 24GB 显存,量化版可压至 8GB 左右73% similarUnverifiedA 35B model requires approximately 70GB of VRAM at FP16 precision, far exceeding the RTX 5090's 32GB capacity, so single-GPU deployment requires quantization.73% similarUnverifiedThe UD-Q8_K_XL quantized version of DeepSeek V4 Flash has a file size of 162 GB, uses MXFP4+BF16 mixed precision, and achieves completely lossless quality.72% similarUnverifiedLoRA fine-tuning based on Stable Diffusion can be completed on ordinary consumer-grade GPUs (such as RTX 3090/4090 with 16–24 GB VRAM), typically achieving satisfactory results within 1–4 hours.72% similar
Cite This Claim
Stable URI
https://kongchang.com/claim/494160API
curl https://kongchang.com/api/v1/knowledge/claims/494160MCP
get_claim(id=494160)