# FLUX.2 Setup in ComfyUI — Full Reproduction Recipe ## Hardware Context (This Session) - Proxmox CT 204, ROCm 6.2, PyTorch 2.6.0 (ROCm build) - AMD Ryzen AI 9 HX PRO 370 w/ Radeon 890M (gfx1150) - `HSA_OVERRIDE_GFX_VERSION=11.0.0` required for gfx1150 - 18GB "VRAM" reported; ~8.5 GB disk free after downloads ## Timeline | Step | Result | |------|--------| | FLUX.1-dev E2E | ✅ Works in 46s (512×512, 4 steps) | | FLUX.2 with FLUX.1 CLIP/T5 | ❌ `mat1 and mat2 shapes cannot be multiplied (512x4096 and 12288x4096)` | | FLUX.2 with Qwen3VL + ae.safetensors | ❌ `expected input[1, 128, 32, 32] to have 16 channels, but got 128 channels instead` | | FLUX.2 with Qwen3VL + taef2 | ✅ Success ~110s (1024×1024, 4 steps) | ## Required Models ### 1. UNet (GGUF) ```bash # ~5.4 GB wget https://huggingface.co/unsloth/FLUX.2-klein-9B-GGUF/resolve/main/flux-2-klein-9b-Q4_K_S.gguf # → models/unet/flux-2-klein-9b-Q4_K_S.gguf ``` ### 2. Text Encoder (Qwen3-VL-8B, GGUF) **CRITICAL:** FLUX.2 uses Qwen3-VL-8B, NOT CLIP-L + T5XXL. ```bash # ~4.7 GB — Q4_K_M quantization wget https://huggingface.co/Qwen/Qwen3-VL-8B-Instruct-GGUF/resolve/main/Qwen3VL-8B-Instruct-Q4_K_M.gguf # → models/clip/Qwen3VL-8B-Instruct-Q4_K_M.gguf ``` Alternative: `Qwen3-VL-8B-Instruct-Q8_0.gguf` (~8.3 GB) for higher quality. The GGUF detection logic in ComfyUI (`comfy/sd.py:detect_te_model`) identifies this model by: - `model.layers.0.self_attn.q_proj.weight` shape = `[4096, 4096]` - `num_hidden_layers = 36` → maps to `TEModel.QWEN3VL_8B` ### 3. VAE — TWO OPTIONS **Option A: TAEF2 (Tiny AutoEncoder, fast, lower quality)** ```bash # ~5 MB total, public, no auth needed cd models/vae_approx curl -LO https://github.com/madebyollin/taesd/raw/main/taef2_encoder.pth curl -LO https://github.com/madebyollin/taesd/raw/main/taef2_decoder.pth # Reference as vae_name: "taef2" in VAELoader node ``` **Option B: Full FLUX.2 VAE (`flux2_vae.safetensors`)** ```bash # ~160 MB, gated repo (BFL license acceptance required) # From: black-forest-labs/FLUX.2-klein-9B vae/diffusion_pytorch_model.safetensors # Save as: models/vae/flux2_vae.safetensors ``` The FLUX.1 VAE (`ae.safetensors`, 16 channels) is **incompatible** with FLUX.2 (128 channels). ## ComfyUI Workflow (API JSON) ```json { "1": { "inputs": {"unet_name": "flux-2-klein-9b-Q4_K_S.gguf"}, "class_type": "UnetLoaderGGUF" }, "2": { "inputs": { "clip_name": "Qwen3VL-8B-Instruct-Q4_K_M.gguf", "type": "flux2" }, "class_type": "CLIPLoaderGGUF" }, "3": { "inputs": {"vae_name": "taef2"}, "class_type": "VAELoader" }, "4": { "inputs": {"width": 1024, "height": 1024, "batch_size": 1}, "class_type": "EmptyFlux2LatentImage" }, "5": { "inputs": { "text": "A beautiful mountain lake at sunset, photorealistic, 4k", "clip": ["2", 0] }, "class_type": "CLIPTextEncode" }, "6": { "inputs": {"text": "", "clip": ["2", 0]}, "class_type": "CLIPTextEncode" }, "7": { "inputs": { "seed": 42, "steps": 4, "cfg": 1.0, "sampler_name": "euler", "scheduler": "simple", "denoise": 1.0, "model": ["1", 0], "positive": ["5", 0], "negative": ["6", 0], "latent_image": ["4", 0] }, "class_type": "KSampler" }, "8": { "inputs": {"samples": ["7", 0], "vae": ["3", 0]}, "class_type": "VAEDecode" }, "9": { "inputs": {"filename_prefix": "flux2_out", "images": ["8", 0]}, "class_type": "SaveImage" } } ``` ### Key node differences from FLUX.1 | Node | FLUX.1 | FLUX.2 | |------|--------|--------| | CLIP loader | `DualCLIPLoaderGGUF` (clip_l + t5xxl) | `CLIPLoaderGGUF` (single Qwen3VL) | | CLIP type | `"flux"` | `"flux2"` | | Empty latent | `EmptyLatentImage` (16 channels) | `EmptyFlux2LatentImage` (128 channels) | | VAE | `ae.safetensors` | `taef2` or `flux2_vae.safetensors` | ## ROCm gfx1150 Workaround gfx1150 (RDNA3.5, Radeon 890M) is not fully supported by ROCm 6.2. Set override before launch: ```bash export HSA_OVERRIDE_GFX_VERSION=11.0.0 python main.py --listen 0.0.0.0 --port 8188 ``` Without this, CLIP encoding fails with: ``` RuntimeError: HIP error: invalid device function ``` ## Performance (gfx1150, ROCm 6.2) | Pipeline | Resolution | Steps | Time | |----------|-----------|-------|------| | FLUX.1-dev Q4_K_S + CLIP/T5 + ae.safetensors | 512×512 | 4 | ~46s | | FLUX.2-klein Q4_K_S + Qwen3VL Q4_K_M + taef2 | 1024×1024 | 4 | ~110s | FLUX.2 is slower despite fewer parameters because Qwen3VL-8B text encoding is heavier than CLIP+T5, and the TAEF2 decode takes extra time. ## Disk Space Budget | Component | Size | |-----------|------| | FLUX.2 UNet Q4_K_S | 5.4 GB | | Qwen3VL-8B Q4_K_M | 4.7 GB | | taef2 encoder+decoder | 5 MB | | **Total** | **~10.1 GB** | Full FLUX.2 VAE adds ~160 MB. Q8_0 text encoder adds ~3.6 GB more. ## Common Errors ### `mat1 and mat2 shapes cannot be multiplied (512x4096 and 12288x4096)` **Cause:** Using CLIP-L + T5XXL (FLUX.1 encoders) with FLUX.2 UNet. **Fix:** Switch to `Qwen3VL-8B-Instruct-Q4_K_M.gguf` + `CLIPLoaderGGUF` with `"type": "flux2"`. ### `expected input[1, 128, 32, 32] to have 16 channels, but got 128 channels instead` **Cause:** Using FLUX.1 VAE (`ae.safetensors`) with FLUX.2 latents. **Fix:** Use `taef2` or download dedicated `flux2_vae.safetensors`. ### `HIP error: invalid device function` **Cause:** ROCm doesn't natively support gfx1150. **Fix:** `export HSA_OVERRIDE_GFX_VERSION=11.0.0` before starting ComfyUI. ### `RuntimeError: The expanded size of the tensor (512) must match ...` **Cause:** Using `EmptyLatentImage` (16-channel) instead of `EmptyFlux2LatentImage` (128-channel). **Fix:** Change node class to `EmptyFlux2LatentImage`. ## References - ComfyUI `comfy/model_base.py` lines 1057-1066: `class Flux2(Flux)` - ComfyUI `comfy/latent_formats.py` line 192: `class Flux2(LatentFormat)` with `latent_channels = 128` - ComfyUI `comfy/sd.py` lines 1631-1634: FLUX2 CLIPType routes to `klein_te` with Qwen3VL - TAEF2 source: https://github.com/madebyollin/taesd - Unsloth GGUF: https://huggingface.co/unsloth/FLUX.2-klein-9B-GGUF - Qwen GGUF: https://huggingface.co/Qwen/Qwen3-VL-8B-Instruct-GGUF