Nodes/civitai-comfy-nodes/mageflow / 4b-turbo / createImage
ComfyUI Node

mageflow / 4b-turbo / createImage

The cheapest legit image generation on Civitai's fleet

By civitai·Created 3 months ago·Updated 2 days ago· 44
mageflow / 4b-turbo / createImage
  • loras
  • diffusion_model
  • api_config
  • images
  • errors
  • workflow_id
  • raw_json
prompt
steps4
cfg_scale1.00
quantity1
output_format
image_metadata
negative_prompt
sampler
scheduler
seed0
width1024
height1024

Take Microsoft's small 4B MageFlow model, distill it down to 4 steps at CFG 1.0, and you get the node that's basically the value end of the Civitai orchestration catalogue: fast, cheap-per-job text-to-image in the cloud. This is the 4B-turbo createImage variant - prompt in, IMAGE out, nothing runs locally.

It's the node to reach for when you need bulk image generation on the cheap, or a fast draft stage before a fancier local or hosted model does the final pass. MageFlow's own claim to fame is that a 4B model can do this at all, and the turbo variant leans into the speed. Just don't expect the detail ceiling of a 12B or 20B model.

How it works

The standard civitai-comfy-nodes flow: the node submits your prompt to the Civitai Orchestration API, runs MageFlow 4B-turbo on Civitai's Comfy engine, long-polls, and returns a native IMAGE tensor. Turbo = guidance-distilled, so 4 steps at CFG 1.0 are the defaults and you should generally leave them there. The "turbo" in the name is doing all the work.

The inputs that matter

  • prompt - required, and it's the only thing you need to fill to get an image.
  • diffusion_model (CIVITAI_AIR) and loras (CIVITAI_LORAS) - optional typed sockets; wire Civitai Model Selector / LoRA Selector nodes to swap models or stack LoRAs on the cloud job.
  • quantity - up to 12 images per job, which makes this node genuinely useful for batch work.
  • steps / cfg_scale - 4 / 1.0 defaults. Distilled model: don't crank CFG.
  • sampler / scheduler / seed / width / height - standard, plus a negative prompt slot.

Outputs

images → Preview/Save. errors, workflow_id, and raw_json are diagnostics; raw_json carries the full workflow result.

Installing and authenticating

Pack-wide install:

cd ComfyUI/custom_nodes
git clone https://github.com/civitai/civitai-comfy-nodes.git
pip install -r civitai-comfy-nodes/requirements.txt

or ComfyUI Manager → "Civitai Comfy Nodes" → Install → restart. Dependencies: requests, python-socketio[client].

Auth: Civitai Auth node → CIVITAI_API_TOKEN → stored key/OAuth → browser login. Headless:

export CIVITAI_API_TOKEN=your_token

Where people get burned

  • 4 steps is the whole point - and the ceiling. You're trading detail for speed and cost. If your use case needs fidelity, the non-turbo MageFlow create node (20 steps) or a bigger engine is the move.
  • CFG 1.0 is not a bug. Setting CFG to 7 "because that's normal" will actively hurt output on a guidance-distilled model.
  • Billing is per job, and quantity multiplies it. Yes, quantity up to 12 is tempting. Yes, you pay per image. Batch responsibly.
  • Your prompts go to Civitai's servers with hosted moderation. Standard API-node trade.
CategoryCivitai/Image/mageflow

Inputs (15)

NameTypeDefaultDescription
promptSTRING
stepsINT41–150
cfg_scaleFLOAT1.000–30
quantityINT11–12
output_formatoptCOMBO4 options: , jpeg, png, webP
image_metadataoptSTRINGExternal metadata that will be stored with the image
negative_promptoptSTRING
sampleroptCOMBO32 options: , euler, euler_ancestral, euler_cfg_pp, euler_ancestral_cfg_pp, heun, +26
scheduleroptCOMBO8 options: , normal, karras, exponential, sgm_uniform, simple, +2
seedoptINT00–4294967295
lorasoptCIVITAI_LORAS
diffusion_modeloptCIVITAI_AIR
widthoptINT1024512–2048
heightoptINT1024512–2048
api_configoptCIVITAI_CONFIGOptional Civitai Auth connection; defaults to CIVITAI_API_TOKEN or stored OAuth login.

Outputs (4)

NameTypeDescription
imagesIMAGE
errorsSTRING
workflow_idSTRING
raw_jsonSTRING