Best local LLMs for Japanese light novel translation with 24GB VRAM

A user in the r/LocalLLaMA community inquired about the best open-source language models for translating Japanese light novels, specifically tailored for setup with 24GB of VRAM. Japanese literary translation is notoriously challenging for AI due to heavy context reliance, nuanced honorifics, and cultural idioms. Finding optimal local models for 24GB VRAM allows enthusiasts to translate novel-length texts privately and cost-effectively on consumer flagship GPUs like the RTX 3090 or 4090. A 24GB VRAM budget typically allows running 14B to 32B parameter models at high precision (8-bit) or larger 70B models using lower quantization (2.5-bit to 3.5-bit). Open models frequently evaluated for Japanese translation include fine-tunes of Qwen2.5, Command R, and specialized Japanese models such as Sakana AI tools or Swallow.