Mismatched LoRA and base model causes 280x slowdown and RAM flooding, user finds
Spoonman915 · reddit · 2026-10-02
A Reddit user discovered that using a LoRA trained on one H3 base model (fl2va) with a different workflow (ref2va) floods 20GB into system RAM and errors out after 7 hours—while the same LoRA paired with its matching model finishes in about 90 seconds. A quick check worth making before blaming your hardware.
More from Multimodal
- Tavus' Griffin passes video Turing test: 48% of live viewers mistook it for a human — EXM7777 · 2026-10-02
- Color shift test: Qwen Image 2.1 drifts far less than Qwen Image Edit 2511 in continuous editing — scatter299792458 · 2026-10-02
- Same 3D prompt test: GPT-6.1 SOL beats GPT-6.0 SOL, gap widest at Very High reasoning — bursinru · 2026-10-02
- AI filmmaking debate shifts from best model to who owns the production pipeline — lmoroney · 2026-10-02
- Gradium claims fastest TTS yet with ~50ms time-to-first-audio, tops sub-100ms naturalness — mattturck · 2026-10-02
- Fizgig 6.8.1 ships Krea 2 slider LoRAs, Ultra mode, and Qwen Image 2.1 full fine-tuning — shootthesound · 2026-10-02