You're looking at a specific version of this model. Jump to the model overview.

usamaehsan /mage-flow-edit-turbo:a930c359

Input schema

The fields you can use to run this model with an API. If you don’t give a value for a field its default value will be used.

Field Type Default value Description
image
string
Image to edit.
prompt
string
An instruction describing the edit.
width
integer
1024

Max: 2048

Output width. Must be a multiple of 16. Set 0 to keep the input's own size (capped by max_size).
height
integer
1024

Max: 2048

Output height. Must be a multiple of 16. Set 0 to keep the input's own size (capped by max_size).
max_size
integer
1024

Min: 256

Max: 2048

Long-edge cap used only when width/height are 0.
steps
integer
4

Min: 1

Max: 50

Denoise steps. This is the 4-step Turbo checkpoint; above ~4 costs more without improving much.
cfg
number
1

Min: 1

Max: 10

Guidance. Turbo is distilled for 1.0 (no CFG); raising it doubles the work per step.
seed
integer
-1
Random seed. -1 for random.
debug_timing
boolean
False
Log a per-stage time breakdown. Adds GPU syncs, so it slightly inflates the total - use for profiling only.
vl_cond_long_edge
integer
384

Min: 128

Max: 768

Long edge the source image is resized to for the text encoder's conditioning pass. 384 matches training.
content_gate
boolean
True
Run the model's built-in content gate. It is a full Qwen3-VL generation on every edit (~1s of billed GPU), so turn it off only when the caller already moderates the prompt and the source image upstream.
gate_long_edge
integer
0

Max: 1024

Long edge the source image is resized to for the mandatory content gate. 0 = full resolution.
gate_max_tokens
integer
192

Min: 16

Max: 192

Token budget for the content gate's verdict. The gate is a greedy VL generation, so this caps its decode loop.
output_format
None
webp
Output image format.
output_quality
integer
90

Min: 1

Max: 100

Compression quality for WebP and JPEG.

Output schema

The shape of the response you’ll get when you run this model with an API.

Schema
{'format': 'uri', 'title': 'Output', 'type': 'string'}