FLUX.1 Inference CLI

Supports MPS (Apple Silicon), CUDA and CPU

Features

• Multiple Models: Supports FLUX.1-schnell and FLUX.1-dev
• LoRA Support: Interactive LoRA picker for easy selection
• Cross-Platform: Supports MPS, CUDA and CPU
• Tested on macOS: Works well on Apple Silicon¹

Installation

Cloning the repository:

git clone https://github.com/SplittyDev/flux1-cli.git
cd flux1-cli

Using uv (recommended):

uv venv
source .venv/bin/activate
uv pip install -r requirements.txt
python3 src/main.py

Using pip:

python3 -m venv .venv
source .venv/bin/activate
python3 -m pip install -r requirements.txt
python3 src/main.py

Installing LoRAs

Simply put your .safetensors files in the lora directory.
They will be available immediately when typing /lora.

Prompting

Inference Modifiers

The CLI supports various modifiers, which can be added to the end of the prompt, like this:

• Photograph of a meadow in a forest /fast
• Photograph of a meadow in a forest /1024x768 /slow
• Photograph of a meadow in a forest /seed=1234 /8

List of Modifiers:

Modifier	Description
/f, /fast	Use a small number of inference steps for fast results
/s, /slow	Use a large number of inference steps for accurate results
/a, /again	Reuse the previous seed for the next inference
/r, /random	Use a random seed for the next inference
/<n> if n < 128	Use this number of inference steps for the next inference
/<n> if n >= 128	Set the resolution to nxn
/<w>x<h>	Set the resolution to wxh

Standalone Modifiers

The CLI also supports standalone modifiers, which only work on their own line.

List of Standalone Modifiers:

Modifier	Description
/quit	Quit the CLI
/lora	Show LoRA picker
/lora_scale=<scale>	Set the LoRA scale to scale
/seed=<seed>	Set the seed to seed

Tips and Tricks

• Leaving the prompt completely empty will repeat the last prompt
• You can combine modifiers, like this: Photograph of a meadow in a forest /fast /seed=1234
• You can apply new modifiers without repeating the prompt, like this: /slow /1024x768
• Images are saved in this format: output/<date>/<timestamp>_<seed>.png

Example workflows with modifiers

Annotated example, explaning the thought process

# Initial prompt. Generate images fast, to get a feeling for the prompt.
λ Prompt: Photograph of a meadow in a forest /fast
# Refine prompt. Fast mode is still active, no need to repeat it.
λ Prompt: High resolution photograph of a meadow in a forest
# This looks nice! Let's generate the same image again, but in slow mode.
λ Prompt: /again /slow
# Let's keep the same prompt, but randomize the seed again.
λ Prompt: /random
# Let's try it in landscape mode, but fast, to see if it looks better.
λ Prompt: /1920x1080 /fast
# Alright, let's call it a day
λ Prompt: /quit

Real-world example, using shortcuts and no comments

λ Prompt: Photograph of a moonlit meadow in a mythical forest/f
λ Prompt: 
λ Prompt: /a/s
λ Prompt: Stunning photograph of a moonlit meadow in a mythical forest, godrays/r/f
λ Prompt: /a/s
λ Prompt: /quit

Troubleshooting

I don't have enough VRAM:

You can pass the --offload-cpu flag to offload parts of the model to the CPU for lower VRAM usage with a small performance hit. Sadly this doesn't seem to work with MPS. If anyone knows why, please let me know!

I wanna use the CPU (for whatever reason):

You can pass the --force-cpu flag to force CPU inference. This is not recommended, as it's much slower than MPS or CUDA.

High resolution images are broken

FLUX.1 has a maximum resolution of 2MP. These are roughly the largest possible sizes²:

• 1:1 exact 1448 x 1448, rounded 1408 x 1408
• 3:2 exact 1773 x 1182, rounded 1728 x 1152
• 4:3 exact 1672 x 1254, rounded 1664 x 1216
• 16:9 exact 1936 x 1089, rounded 1920 x 1088
• 21:9 exact 2212 x 948, rounded 2176 x 960

You can use an upscaler (not included) to increase the resolution.

Footnotes

1. Tested on 2023 Mac Studio, 128GB Unified RAM, 24-Core Apple M2 Ultra ↩

2. See this post on Reddit. Thanks u/Aplakka! ↩