Venice Image Generation

Two text-to-image endpoints:

POST /api/v1/image/generate
— Venice-native, full control (negative prompts, CFG, seed, up to 4 variants).
POST /api/v1/images/generations
— OpenAI-compatible, fewer knobs but drop-in for the OpenAI SDK.

Plus:

GET /api/v1/image/styles
— list of style preset names for
```
style_preset
```
.

For editing / upscaling / multi-image / background removal, see

venice-image-edit

Use when

You need to generate images from text prompts.
You need multiple variants in one call.
You're porting from OpenAI's
```
images.generate
```
and want a zero-change SDK swap.
You want to browse style presets before committing to one.

/image/generate

— Venice-native

Request

bash

curl https://api.venice.ai/api/v1/image/generate \
  -H "Authorization: Bearer $VENICE_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "z-image-turbo",
    "prompt": "A beautiful sunset over a mountain range",
    "width": 1024,
    "height": 1024,
    "cfg_scale": 7.5,
    "steps": 8,
    "seed": 123456789,
    "variants": 1,
    "format": "webp",
    "style_preset": "3D Model",
    "safe_mode": true
  }'

Fields

Field	Type	Default	Notes
`model`	string	—	Required. Image model ID. `GET /models?type=image` .
`prompt`	string	—	Required. Max `promptCharacterLimit` from the model's `model_spec.constraints` (typically 1500–7500).
`negative_prompt`	string	—	Describe what not to show. Same character cap as prompt.
`width` , `height`	int	1024, 1024	≤ 1280 each. Must be divisible by `constraints.widthHeightDivisor` on the model's `model_spec` .
`aspect_ratio`	string	—	`"1:1"` , `"16:9"` , `"9:16"` , … — used by models like Nano Banana instead of width/height.
`resolution`	string	—	`"1K"` , `"2K"` , `"4K"` — used by resolution-driven models.
`cfg_scale`	number	model default	0 < x ≤ 20. Higher = more prompt adherence.
`steps`	int	8	Inference steps. Some models ignore it (e.g. Turbo).
`seed`	int	0	`-999999999..999999999` . Use `0` /omit for random.
`variants`	int	1	1–4. Only if `return_binary: false` .
`lora_strength`	int	—	0–100 when model uses Loras.
`style_preset`	string	—	Value from `GET /image/styles` .
`format`	`"webp"` / `"png"` / `"jpeg"`	`webp`	Response image format.
`return_binary`	bool	`false`	`true` → binary `image/*` response; `false` → JSON with base64.
`embed_exif_metadata`	bool	`false`	Embed prompt info in EXIF.
`hide_watermark`	bool	`false`	Venice may still watermark certain content.
`safe_mode`	bool	`true`	Blurs adult content.
`enable_web_search`	bool	`false`	Only some models. Charges extra.
`inpaint`	—	—	Deprecated since May 19 2025. A new inpaint API is forthcoming.

Response (JSON,

return_binary: false

)

json

{
  "id": "...",
  "images": ["<base64>", "<base64>"],
  "timing": {...},
  "request": {...}
}

With

return_binary: true

, response is raw

image/webp

(or

png

jpeg

) with matching

Content-Type

/images/generations

— OpenAI-compatible

Use this if you're already on the OpenAI SDK. Field names match

openai.images.generate()

import OpenAI from 'openai'

const client = new OpenAI({
  apiKey: process.env.VENICE_API_KEY,
  baseURL: 'https://api.venice.ai/api/v1',
})

const res = await client.images.generate({
  model: 'z-image-turbo',
  prompt: 'A beautiful sunset over mountain ranges',
  size: '1024x1024',
  response_format: 'b64_json',
})

const b64 = res.data[0].b64_json

Mapped fields

Field	Values	Notes
`model`	string, default `"default"`	Unknown model IDs fall back to Venice's default.
`prompt`	string, ≤ 1500 chars	Required.
`size`	`auto` , `256x256` , `512x512` , `1024x1024` , `1536x1024` , `1024x1536` , `1792x1024` , `1024x1792`	—
`output_format`	`jpeg` / `png` / `webp`	Defaults to `png` .
`response_format`	`b64_json` / `url`	`url` returns a `data:` URL (not a hosted URL).
`moderation`	`auto` (safe mode on) / `low` (safe mode off)	—
`n`	`1`	Venice only supports a single image per call here.
`quality` , `style` ( `vivid` / `natural` ), `background` , `output_compression` , `user`	—	Accepted for OpenAI compat, not used by Venice.

If you need

variants

seed

negative_prompt

cfg_scale

, or

style_preset

, switch to

/image/generate

/image/styles

— list presets

bash

curl https://api.venice.ai/api/v1/image/styles \
  -H "Authorization: Bearer $VENICE_API_KEY"

Returns a list of

styles[]

, each with a

name

you can pass to

style_preset

. Cache this — it's small and stable.

Choosing a model

bash

curl "https://api.venice.ai/api/v1/models?type=image" \
  -H "Authorization: Bearer $VENICE_API_KEY"

Inspect per-model

model_spec

constraints.widthHeightDivisor

—

width

and

height

must both be divisible by this.

```
constraints.aspectRatios[]
```
+
```
defaultAspectRatio
```
— if present, the model supports aspect-ratio-driven sizing.

constraints.resolutions[]

defaultResolution

— if present, the model supports

resolution

(

1K

2K

4K

```
constraints.steps.{default,max}
```
— step bounds (some models ignore
```
steps
```
entirely).

constraints.promptCharacterLimit

— max prompt length (also applies to

negative_prompt

```
pricing.generation.usd
```
— flat USD per image, or
```
pricing.resolutions[].usd
```
for resolution-tiered models.

Pick a model that matches the feature + size combo you plan to use.

Common patterns

Fixed-seed A/B test

json

{"model": "z-image-turbo", "prompt": "...", "seed": 42, "variants": 4}

Aspect-ratio-driven model (Nano Banana family)

json

{"model": "nano-banana-2", "prompt": "...", "aspect_ratio": "16:9", "resolution": "2K"}

(Other nano-banana variants:

nano-banana-pro

. Always verify the current ID via

GET /models?type=image

Style preset + negative

json

{
  "model": "z-image-turbo",
  "prompt": "a red sports car in a parking lot",
  "negative_prompt": "blurry, people, clouds",
  "style_preset": "3D Model"
}

Stream binary to disk (Node)

const res = await fetch('https://api.venice.ai/api/v1/image/generate', {
  method: 'POST',
  headers: { Authorization: `Bearer ${process.env.VENICE_API_KEY}`, 'Content-Type': 'application/json' },
  body: JSON.stringify({ model: 'z-image-turbo', prompt: '...', return_binary: true }),
})
if (!res.ok) throw new Error(await res.text())
const buf = Buffer.from(await res.arrayBuffer())
await fs.writeFile('out.webp', buf)

Errors

Code	Meaning
`400`	Bad params (e.g. dimensions not divisible by `widthHeightDivisor` , prompt too long, `variants>1` with `return_binary` ).
`401`	Auth or Pro-only model.
`402`	Insufficient balance. Bearer: plain `{ "error": "Insufficient balance" }` ; x402: `PAYMENT_REQUIRED` body + `PAYMENT-REQUIRED` header.
`415`	Wrong `Content-Type` (send `application/json` for this endpoint).
`429`	Rate limited.
`500` / `503`	Inference or capacity issue — retry with jitter.

(Content-policy violations on

/image/generate

come back as

with an error string, not

— the

shape is specific to audio generation paths.)

Gotchas

Each model picks one sizing idiom: either
```
width
```
/
```
height
```
,
```
aspect_ratio
```
+
```
resolution
```
, or (OpenAI-compat)
```
size
```
. Match the model's
```
constraints
```
.
```
variants > 1
```
requires
```
return_binary: false
```
(JSON with base64 array).
```
steps
```
is ignored by fast/turbo models; they hardcode step count internally.
```
hide_watermark: true
```
is advisory — Venice may still watermark content flagged by safety classifiers.
Old
```
inpaint
```
field is deprecated; don't use it.
For OpenAI-compat,
```
response_format: "url"
```
returns a data URL, not a hosted URL — plan for that if you're saving to storage.

venice-image-generate

NPX Install

Tags

SKILL.md Content

Venice Image Generation

Use when

`/image/generate`
— Venice-native

Request

Fields

Response (JSON,
`return_binary: false`
)

`/images/generations`
— OpenAI-compatible

Mapped fields

`/image/styles`
— list presets

Choosing a model

Common patterns

Fixed-seed A/B test

Aspect-ratio-driven model (Nano Banana family)

Style preset + negative

Stream binary to disk (Node)

Errors

Gotchas

venice-image-generate

NPX Install

Tags

SKILL.md Content

Venice Image Generation

Use when

/image/generate — Venice-native

Request

Fields

Response (JSON, return_binary: false)

/images/generations — OpenAI-compatible

Mapped fields

/image/styles — list presets

Choosing a model

Common patterns

Fixed-seed A/B test

Aspect-ratio-driven model (Nano Banana family)

Style preset + negative

Stream binary to disk (Node)

Errors

Gotchas

`/image/generate`
— Venice-native

Response (JSON,
`return_binary: false`
)

`/images/generations`
— OpenAI-compatible

`/image/styles`
— list presets