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Qwen3.5 models quantized for ComfyUI, run on 8GB VRAM

A user has released quantized versions of the Qwen3.5 models (2B, 4B, and 9B parameters) for use with ComfyUI. These INT8 models, utilizing ConvRot quantization, are designed to run efficiently on systems with as little as 8GB of VRAM. The user provides drop-in replacements for existing BF16 models and includes a workflow for image prompting, analysis, and captioning for LoRA training. AI

IMPACT Enables lower-spec hardware to run larger language models for image generation tasks.

RANK_REASON User-created quantized model release for a specific tool (ComfyUI).

Read on r/StableDiffusion →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

Qwen3.5 models quantized for ComfyUI, run on 8GB VRAM

COVERAGE [1]

  1. r/StableDiffusion TIER_2 English(EN) · /u/Winougan ·

    [Release] Qwen3.5 INT8 + ConvRot text encoders for ComfyUI (2B/4B/9B, runs on 8GB VRAM)

    <table> <tr><td> <a href="https://www.reddit.com/r/StableDiffusion/comments/1un547d/release_qwen35_int8_convrot_text_encoders_for/"> <img alt="[Release] Qwen3.5 INT8 + ConvRot text encoders for ComfyUI (2B/4B/9B, runs on 8GB VRAM)" src="https://preview.redd.it/figbmga8r6bh1.png?w…