語言

Flux 3 text-to-image workflow

從 ModelTrends 匯入

A basic Flux 3 text-to-image workflow: the Klein base in BF16 with a 9GB Text Upscaler, the Flux 2 VAE and a Qwen VL text encoder. 50 steps is recommended. On Graydient you can also run Distill, Base, BF16 Text Encoder and Upscaler presets for this family, the same ones listed on ModelTrends. A typical render takes about three minutes and wants around 28 GB of VRAM.

支援 Graydient 技術的應用程式

選項

選項映射至預設
(prompt positive)Text (Multiline) → value—
/guidanceKSampler → cfg3.5
/imagesEmpty Flux 2 Latent → batch_size1
/seedKSampler → seedrandom
/sizeEmpty Flux 2 Latent → width, height1024 × 1024
/stepsKSampler → steps50

使用的模型

Flux 3 (v11) 模型由 ModelTrends 透過短碼 /run:flux3 匯入 在 ModelTrends 查看

給開發者(可選)

API 範例程式碼。你可以用這個工作流程建立自己的應用程式供個人使用。準備好部署到全球時,請聯絡我們以取得高可用性伺服器。詳見完整渲染 API 文件。

curl https://cloud.graydient.ai/api/v3/render/ \
  -X POST \
  -H "Content-Type: application/vnd.api+json" \
  -H "Accept: application/vnd.api+json" \
  -H "Authorization: Bearer $GRAYDIENT_TOKEN" \
  -d '{
    "prompt": "/workflow /run:flux3 a lighthouse on a cliff at dusk",
    "callback_url": "https://example.com/webhook/render"
  }'

這是幕後運作方式。這已經為你設定好。上表中的參數會插入這些位置,讓你能改變運作方式及載入的模型。你不必理解或修改它——它已經能正常運作。

Load Diffusion Model MODEL to KSampler; Load CLIP CLIP to CLIP Text Encode (Prompt); Load CLIP (9GB Text Upscaler) CLIP to CLIP Text Encode (Prompt); Text (Multiline) STRING to CLIP Text Encode (Prompt); CLIP Text Encode (Prompt) CONDITIONING to KSampler; Empty Flux 2 Latent LATENT to KSampler; KSampler LATENT to VAE Decode; Load VAE VAE to VAE Decode; VAE Decode IMAGE to Save Image
Load Diffusion Model#28
MODEL
unet_nameflux3_image_klein_bas…
Load CLIP (9GB Text Upscaler)#25
CLIP
clip_nameqwen3.5_9b_flux3_prom…
Load CLIP#30
CLIP
clip_nameqwen3vl_4b_bf16
Load VAE#32
VAE
vae_nameflux2-vae
Text (Multiline)#24
STRING
valuea lighthouse on a cli…(prompt)
CLIP Text Encode (Prompt)#6
clipCONDITIONING
clip_upscale
text
Empty Flux 2 Latent#35
LATENT
width1024/size
height1024/size
batch_size1/images
KSampler#31
modelLATENT
positive
latent_image
seedrandom/seed
steps50/steps
cfg3.5/guidance
VAE Decode#8
samplesIMAGE
vae
Save Image#9
images
filename_prefixGraydient

唯讀視圖。高亮的選項是調用時可設定的。 Base BF16 with 9GB Text Upscaler; 50 steps recommended.

所有工作流程:強大的工作流程

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