Fibo 2.0 uses a Fibo diffusion transformer, the standard FLUX.2 VAE, and Qwen3-VL 4B as the LLM text encoder. The Qwen tokenizer is built in.
- Download Fibo 2.0 Dev
- Download Fibo 2.0 Edit Turbo
- Download vae
- Download Qwen3-VL 4B
The original Diffusers weights from briaai/Fibo-2.0-dev and briaai/Fibo-2.0-edit-turbo are also supported. Pass the transformer's diffusion_pytorch_model.safetensors.index.json to --diffusion-model and keep its shards alongside it.
INT8 convrot weights load directly; see INT8 convrot for backend requirements.
Dev supports both text-to-image generation and reference-image editing.
.\bin\Release\sd-cli.exe --diffusion-model ..\models\diffusion_models\fibo2_dev_int8_convrot.safetensors --llm ..\models\text_encoders\Qwen3-VL-4B-Instruct-Q4_K_M.gguf --llm_vision ..\models\text_encoders\Qwen3-VL-4B-Instruct-mmproj-BF16.gguf --vae ..\models\vae\flux2_ae.safetensors -p "a lovely cat holding a sign says 'fibo2.cpp'" --cfg-scale 5.0 --sampling-method euler -v --offload-to-cpu
.\bin\Release\sd-cli.exe --diffusion-model ..\models\diffusion_models\fibo2_dev_int8_convrot.safetensors --llm ..\models\text_encoders\Qwen3-VL-4B-Instruct-Q4_K_M.gguf --llm_vision ..\models\text_encoders\Qwen3-VL-4B-Instruct-mmproj-BF16.gguf --vae ..\models\vae\flux2_ae.safetensors -r ..\assets\flux\flux1-dev-q8_0.png -p "change 'flux.cpp' to 'fibo2.cpp'" --cfg-scale 5.0 --sampling-method euler -v --offload-to-cpu
Edit Turbo is distilled for reference-image editing in 4 steps with CFG 1.
.\bin\Release\sd-cli.exe --diffusion-model ..\models\diffusion_models\fibo2_edit_turbo_int8_convrot.safetensors --llm ..\models\text_encoders\Qwen3-VL-4B-Instruct-Q4_K_M.gguf --llm_vision ..\models\text_encoders\Qwen3-VL-4B-Instruct-mmproj-BF16.gguf --vae ..\models\vae\flux2_ae.safetensors -r ..\assets\flux\flux1-dev-q8_0.png -p "change 'flux.cpp' to 'fibo2.cpp'" --cfg-scale 1 --steps 4 --sampling-method euler -v --offload-to-cpu
The BF16 files accept the same options. Use dimensions divisible by 16. Repeat -r to use multiple reference images; instructions can refer to <image_1>, <image_2>, etc. See Image Editing for reference-image preprocessing options. Separate GGUF text encoders need their vision projector passed with --llm_vision for editing.
The automatic fibo2 reference preset combines resize_single_ref_to_target=true, vae_size_buckets=true, vae_center_crop=true, and vlm_use_vae_input=true. A single reference is scaled to cover the output dimensions and center-cropped. Multiple references use dimensions divisible by 16, chosen within ±10% of one megapixel to minimize cropping for each image's aspect ratio; vae_input_max_pixels overrides that target area. The VAE and vision encoder receive the same crops, with smaller copies used by the vision encoder. These are generic reference-image options and can be overridden individually: for example, --ref-image-args vae_center_crop=false uses direct resizing, while resize_before_vae=false skips this automatic crop and resize step entirely.
The vision encoder defaults to vlm_resize_mode=longest_side,vlm_max_size=768. Override these with --ref-image-args, for example vlm_max_size=512, or use vlm_resize_mode=none to skip size-based scaling. Vision inputs are still aligned to the encoder's patch grid.
Plain prompts and structured JSON captions are accepted. This integration uses the caption-only text-rendering path (render_text_images=False); it does not generate auxiliary glyph images or expand prompts with Bria VGL. Native Fibo mask preprocessing is not connected to --mask.