User achieves 262k context & vision on 16GB VRAM with Qwen3.8 model

A Reddit user shared a method for running the Qwen3.8-27B-UD-IQ4_XS model with a 262k context window and vision capabilities on a 16GB VRAM graphics card. The user claims this is achievable using a modified version of llama.cpp-adaptive-kv-streaming, which allows for higher quantization and context lengths than typically thought possible on consumer hardware. This technique aims to help users with limited VRAM run more powerful models efficiently, achieving speeds of around 80 tokens/s for general use and 20 tokens/s at full context. AI

IMPACT Enables users with limited VRAM to run larger, more capable LLMs with extended context windows.

RANK_REASON User-shared optimization technique for running a specific LLM on consumer hardware.

Read on r/LocalLLaMA →

• llama.cpp-adaptive-kv-streaming
• Qwen3.8-27B-UD-IQ4_XS
• Unsloth

• infra
• model release

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