---
base_model: Qwen/Qwen-Image
base_model_relation: quantized
license: apache-2.0
pipeline_tag: text-to-image
tags:
  - fni8
  - int8
  - w8a8
  - dp4a
  - volta
  - sm_70
  - quantized
  - diffusion
  - text-to-image
  - comfyui
  - 4-bit
---

# Qwen-Image — fni8 (int8/W4A8 dp4a, Volta sm_70)

Diffusion transformer (DiT), quantized from [`Qwen/Qwen-Image`](https://huggingface.co/Qwen/Qwen-Image). Repackaged to the **`.fni8`** resident format (~31.4 GB (int4 DiT)) for the [fni8](https://github.com/jajmangold/fni8) **W8A8/W4A8 DP4A** kernels on **NVIDIA Volta (sm_70)** — Tesla V100 / CMP 100-210.

## Status

**Validated:** end-to-end ComfyUI-fni8 sanity pass (a one-step output that is finite and non-constant — a sanity check, not a quality benchmark). **Performance is fleet-specific.** All fni8 speedups are measured on the CMP 100-210 mining-card fleet, where the fp16 tensor cores are firmware-gimped. These numbers do **not** transfer to a real Tesla V100 (whose fp16 tensor cores would beat dp4a).

## Format

- **Weights:** int4 per-group W4A8 (int8 activations), fp32 scales, resident dp4a VRAM layout.
- **Why dp4a:** sm_70 has no int8 tensor cores, so the matmul contraction runs on the `__dp4a` CUDA-core intrinsic. On the CMP 100-210 fleet (whose fp16 tensor cores are firmware-limited) dp4a is the fast path, not a compromise.

## How to run

[ComfyUI-fni8](https://github.com/jajmangold/ComfyUI-fni8) is the runtime (`UnetLoaderFNI8` runs the diffusion transformer through the dp4a kernels; the text encoder and VAE are unchanged). fni8-serve is for LLMs only and does not load this model.

## Limitations

- Quantization is lossy: int8 (and especially int4) outputs differ from the fp16/bf16 parent, and the difference varies by task.
- Capabilities, biases, and risks of the parent model carry over — see the parent card.
- This is a derivative quantization, not a relicense; the parent model's license and acceptable uses apply.

---

Part of the fni8 stack: [kernels](https://github.com/jajmangold/fni8) · [LLM serving](https://github.com/jajmangold/fni8-serve) · [ComfyUI DiTs](https://github.com/jajmangold/ComfyUI-fni8).