Expired50% confidenceFactExact time
Full fine-tuning of an SD XL model requires more than 80 GB of VRAM, whereas LoRA training achieving equivalent results can be completed on a consumer-grade GPU with 24 GB of VRAM.
1
Sources
50%
Confidence
Medium-term (~90 days)
Relevance
7/6/2026
First Seen
This claim has expired. It is kept for the record and no longer describes the current state.
Valid until: 10/4/2026(expired)
Sources
AI Short Drama Practical Guide: A Three-Phase Learning Roadmap to Launch in Two Weeks
bilibiliSD-官方教程7/4/2026
Related Claims
UnverifiedFor small teams with a few professional-grade GPUs (such as A100 80GB or H100), a 270GB model has entered the range of operability.71% similarUnverifiedDeepSeek-V3完整模型需要数百GB显存，即便量化后的小模型也至少需要一块消费级以上的GPU71% similarUnverifiedLoRA fine-tuning reduces the required GPU memory from hundreds of GB to the GB level.71% similarUnverifiedThe VRAM consumption of the KV cache is proportional to context length, number of model layers, and number of attention heads; under an 8K context, a typical 27B model may consume an additional 2–4 GB of VRAM.70% similar
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