venice-image-generate

name venice-image-generate description Generate images with Venice. Covers POST /image/generate (Venice-native), POST /images/generations (OpenAI-compatible), GET /image/styles (style presets), request fields (prompt, dimensions, cfg_scale, seed, variants, style_preset, style_references, aspect_ratio, resolution, safe_mode, watermark), and response formats. 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. You want generated images to match the look of existing images ( style_references ). /image/generate — Venice-native Request 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 . style_references array — Reference images that guide the aesthetic of the output. Each item: { "image": <base64 or http(s) URL, <8MB>, "strength": 0.1–1 (default 0.5) } . Only on models with supportsStyleReferences: true ; per-model cap in constraints.maxStyleReferences . strength is ignored when constraints.supportsStyleReferenceStrength is false . quality "low" / "medium" / "high" — Output quality on models that support it (e.g. GPT Image 2). Higher values can raise the request charge. enhance_prompt bool false Rewrite the prompt to add clarifying visual detail before generating. Costs extra credits when a rewrite happens and adds up to ~30 s. The final prompt returns URL-encoded in the x-venice-enhanced-prompt response header. disable_prompt_optimization_thinking bool model default Skip the model's prompt-optimization thinking step for speed. Only honored by models with supportsOptimizePromptThinking . 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 ) { "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 , style_preset , or style_references , switch to /image/generate . /image/styles — list presets 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 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 ). supportsStyleReferences — whether the model accepts style_references on /image/generate . constraints.maxStyleReferences — max number of style reference images (only present on supporting models). constraints.supportsStyleReferenceStrength — whether per-reference strength is honored (only present on supporting models). 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 { "model" : "z-image-turbo" , "prompt" : "..." , "seed" : 42 , "variants" : 4 } Aspect-ratio-driven model (Nano Banana family) { "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 { "model" : "z-image-turbo" , "prompt" : "a red sports car in a parking lot" , "negative_prompt" : "blurry, people, clouds" , "style_preset" : "3D Model" } Style references (match the look of existing images) { "model" : "krea-v2-large" , "prompt" : "a lighthouse on a rocky coast at dusk" , "style_references" : [ { "image" : "https://example.com/ref-1.png" , "strength" : 0.8 } , { "image" : "data:image/png;base64,...." , "strength" : 0.4 } ] } Describe the subject in the prompt; the references carry the style . As of mid-2026 the supporting models are krea-v2-large / krea-v2-medium (up to 3 refs, strength honored) and luma-uni-1 / luma-uni-1-max (up to 3 refs, strength ignored) — all anonymized routing. Always re-verify via GET /models?type=image ( supportsStyleReferences ). 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 400 with an error string, not 422 — the 422 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. style_references is silently unsupported outside the models flagged supportsStyleReferences: true ; check the flag rather than trying and inspecting output. Each reference image must be < 8MB. For OpenAI-compat, response_format: "url" returns a data URL , not a hosted URL — plan for that if you're saving to storage.