Can the RTX 2060 6 GB run HunyuanImage 2.1?
Not entirely. Even Q4_K_M is 8.6 GB over 6 GB, so ComfyUI keeps part of it in system RAM.
The smallest sensible file, Q4_K_M (11.3 GB), needs about 14.6 GB - 8.6 GB more than RTX 2060 6 GB has. ComfyUI can still run it by streaming part of the model from system RAM. How much slower that is depends on your ComfyUI version, the file format and the PCIe link - see the note below.
Also try the FP8 file (17.4 GB) on this GPU. It does not fit entirely, but a current ComfyUI streams the overflow from RAM and native 8-bit files often beat a small GGUF that does fit. Dynamic VRAM →
01With more VRAM
With 24 GB you could run HunyuanImage 2.1 at 8-bit or better (Q8_0, 19.8 GB) with no offloading: for example on the RTX 4090 24 GB, RTX 3090 24 GB, RX 7900 XTX 24 GB.
What changes from the RTX 2060 6 GB to the RTX 3060 12 GB → · What changes from the RTX 2060 6 GB to the RTX 5060 Ti 16 GB →
02Every HunyuanImage 2.1 file on 6 GB
| File | Size | Needed | On this card | Quality | Download |
|---|---|---|---|---|---|
| 16-bit SAFETENSORS · Comfy-Org | 34.9 GB | 38.2 GB | 32.2 GB too big | the original weights | Hugging Face → |
| Q8_0 GGUF · calcuis | 19.8 GB | 23.1 GB | 17.1 GB too big | practically identical to the original | Hugging Face → |
| FP8 SAFETENSORS · Comfy-Org | 17.4 GB | 20.7 GB | 14.7 GB too big | practically identical to the original | Hugging Face → |
| Q6_K GGUF · calcuis | 15.7 GB | 19.0 GB | 13.0 GB too big | very close to the original | Hugging Face → |
| Q5_K_M GGUF · calcuis | 13.4 GB | 16.7 GB | 10.7 GB too big | close; small differences in fine detail | Hugging Face → |
| Q4_K_M ← GGUF · calcuis | 11.3 GB | 14.6 GB | 8.6 GB too big | good; some loss in fine detail and text | Hugging Face → |
| Q3_K_M GGUF · calcuis | 9.8 GB | 13.1 GB | 7.1 GB too big | noticeable loss of detail | Hugging Face → |
| Q2_K GGUF · calcuis | 7.3 GB | 10.6 GB | 4.6 GB too big | heavy loss; a last resort | Hugging Face → |
“Needed” adds 2.5 GB of working memory for HunyuanImage 2.1 and a 0.8 GB reserve. Sizes 2026-10-01.
03What to download
| Part | File | Folder | Size | |
|---|---|---|---|---|
| Model | hunyuanimage2.1-q4_k_m.gguf Q4_K_M · calcuis/hunyuanimage-gguf | models/unet | 11.3 GB | Download → |
| Text encoder | qwen_2.5_vl_7b_fp8_scaled.safetensors Qwen2.5-VL 7B FP8 · Comfy-Org/HunyuanImage_2.1_ComfyUI | models/text_encoders | 9.4 GB | Download → |
| Text encoder | byt5_small_glyphxl_fp16.safetensors ByT5 small Glyph-XL · Comfy-Org/HunyuanImage_2.1_ComfyUI | models/text_encoders | 0.4 GB | Download → |
| VAE | hunyuan_image_2.1_vae_fp16.safetensors HunyuanImage 2.1 VAE · Comfy-Org/HunyuanImage_2.1_ComfyUI | models/vae | 0.8 GB | Download → |
| Total download · keep about the same free on disk | 21.9 GB | |||
Alternatives: Qwen2.5-VL 7B BF16 (16.6 GB). Sizes from Hugging Face, 2026-10-01.
04The text encoder
At 9.4 GB even the smallest Qwen2.5-VL 7B file is too big for 6 GB, so it runs from system RAM. That slows down reading the prompt, not the picture. Sizes: 16-bit 16.6 GB, FP8 9.4 GB. Why the encoder does not count against VRAM →
05Measured and reported results
Nobody has sent measured numbers for this pair yet. If you run HunyuanImage 2.1 on a RTX 2060 6 GB, send your time per image and peak VRAM and it will appear here, credited.
06About the RTX 2060 6 GB
The RTX 2060 6 GB (Turing) has no FP8 compute. FP8 files still load and save memory, but ComfyUI converts them back before the maths, so there is no speed gain - Q8_0 GGUF is the closer-to-original 8-bit choice. ComfyUI can compute INT8 files natively on NVIDIA, which is worth a try where a model offers one.
6 GB GDDR6 · 192-bit · 336 GB/s · Turing. Everything that runs on it →
07Questions
How much VRAM does HunyuanImage 2.1 need?
Around 10.6 GB with the smallest file (Q2_K) and 20.7 GB with an 8-bit file (FP8). The full 16-bit file needs about 38.2 GB.
Which HunyuanImage 2.1 file should I download for the RTX 2060 6 GB?
Q4_K_M (11.3 GB) from calcuis/hunyuanimage-gguf. Load it with Unet Loader (GGUF) from the ComfyUI-GGUF node pack.
FP8 or Q8_0 for HunyuanImage 2.1 on the RTX 2060 6 GB?
Q8_0 (19.8 GB). The RTX 2060 6 GB has no FP8 maths, so FP8 (17.4 GB) only saves memory and is a step further from the original.
How much do I need to download for HunyuanImage 2.1 on the RTX 2060 6 GB?
21.9 GB: hunyuanimage2.1-q4_k_m.gguf, qwen_2.5_vl_7b_fp8_scaled.safetensors, byt5_small_glyphxl_fp16.safetensors, hunyuan_image_2.1_vae_fp16.safetensors.