1:"$Sreact.fragment"
3:I[54118,["6693","static/chunks/fba4ba2d-460e04194f22506f.js?dpl=dpl_CPYCfxesaX7RKfJUQZpH2JDib41x","3009","static/chunks/6a7d804d-a5cc510ceffe206f.js?dpl=dpl_CPYCfxesaX7RKfJUQZpH2JDib41x","7505","static/chunks/c02d83f4-5637599209ef9447.js?dpl=dpl_CPYCfxesaX7RKfJUQZpH2JDib41x","1737","static/chunks/fe207bbb-c84ed91deca4f888.js?dpl=dpl_CPYCfxesaX7RKfJUQZpH2JDib41x","9509","static/chunks/9509-6125acd3006111c1.js?dpl=dpl_CPYCfxesaX7RKfJUQZpH2JDib41x","4378","static/chunks/4378-3f82908971052aa9.js?dpl=dpl_CPYCfxesaX7RKfJUQZpH2JDib41x","5289","static/chunks/5289-131715863bbab062.js?dpl=dpl_CPYCfxesaX7RKfJUQZpH2JDib41x","4094","static/chunks/4094-eaa6158623fe27ff.js?dpl=dpl_CPYCfxesaX7RKfJUQZpH2JDib41x","4982","static/chunks/4982-a4b2ee93ffd82ffd.js?dpl=dpl_CPYCfxesaX7RKfJUQZpH2JDib41x","1810","static/chunks/1810-cf4ca0391c1ddf2a.js?dpl=dpl_CPYCfxesaX7RKfJUQZpH2JDib41x","6397","static/chunks/6397-b7ccd1edf8aedf12.js?dpl=dpl_CPYCfxesaX7RKfJUQZpH2JDib41x","7979","static/chunks/7979-1799576a8e82a4f3.js?dpl=dpl_CPYCfxesaX7RKfJUQZpH2JDib41x","144","static/chunks/144-1a048554a0613a1b.js?dpl=dpl_CPYCfxesaX7RKfJUQZpH2JDib41x","2610","static/chunks/2610-c41f461a4ed7cf24.js?dpl=dpl_CPYCfxesaX7RKfJUQZpH2JDib41x","528","static/chunks/528-7ef2006e50a52549.js?dpl=dpl_CPYCfxesaX7RKfJUQZpH2JDib41x","1742","static/chunks/1742-0ea812562873537a.js?dpl=dpl_CPYCfxesaX7RKfJUQZpH2JDib41x","1172","static/chunks/1172-89020d82938322e4.js?dpl=dpl_CPYCfxesaX7RKfJUQZpH2JDib41x","9919","static/chunks/9919-b585857c6e10fb85.js?dpl=dpl_CPYCfxesaX7RKfJUQZpH2JDib41x","9326","static/chunks/9326-103822841b140d80.js?dpl=dpl_CPYCfxesaX7RKfJUQZpH2JDib41x","4077","static/chunks/4077-cba4e88bdb106467.js?dpl=dpl_CPYCfxesaX7RKfJUQZpH2JDib41x","1924","static/chunks/1924-8c4ee98e9b0dbf83.js?dpl=dpl_CPYCfxesaX7RKfJUQZpH2JDib41x","2530","static/chunks/2530-9eb218eca5ffc00b.js?dpl=dpl_CPYCfxesaX7RKfJUQZpH2JDib41x","7177","static/chunks/app/layout-75dbb92d3cda2f1c.js?dpl=dpl_CPYCfxesaX7RKfJUQZpH2JDib41x"],"Providers"]
4:I[98195,["6693","static/chunks/fba4ba2d-460e04194f22506f.js?dpl=dpl_CPYCfxesaX7RKfJUQZpH2JDib41x","3009","static/chunks/6a7d804d-a5cc510ceffe206f.js?dpl=dpl_CPYCfxesaX7RKfJUQZpH2JDib41x","7505","static/chunks/c02d83f4-5637599209ef9447.js?dpl=dpl_CPYCfxesaX7RKfJUQZpH2JDib41x","1737","static/chunks/fe207bbb-c84ed91deca4f888.js?dpl=dpl_CPYCfxesaX7RKfJUQZpH2JDib41x","9509","static/chunks/9509-6125acd3006111c1.js?dpl=dpl_CPYCfxesaX7RKfJUQZpH2JDib41x","4378","static/chunks/4378-3f82908971052aa9.js?dpl=dpl_CPYCfxesaX7RKfJUQZpH2JDib41x","5289","static/chunks/5289-131715863bbab062.js?dpl=dpl_CPYCfxesaX7RKfJUQZpH2JDib41x","4094","static/chunks/4094-eaa6158623fe27ff.js?dpl=dpl_CPYCfxesaX7RKfJUQZpH2JDib41x","4982","static/chunks/4982-a4b2ee93ffd82ffd.js?dpl=dpl_CPYCfxesaX7RKfJUQZpH2JDib41x","1810","static/chunks/1810-cf4ca0391c1ddf2a.js?dpl=dpl_CPYCfxesaX7RKfJUQZpH2JDib41x","6397","static/chunks/6397-b7ccd1edf8aedf12.js?dpl=dpl_CPYCfxesaX7RKfJUQZpH2JDib41x","7979","static/chunks/7979-1799576a8e82a4f3.js?dpl=dpl_CPYCfxesaX7RKfJUQZpH2JDib41x","144","static/chunks/144-1a048554a0613a1b.js?dpl=dpl_CPYCfxesaX7RKfJUQZpH2JDib41x","2610","static/chunks/2610-c41f461a4ed7cf24.js?dpl=dpl_CPYCfxesaX7RKfJUQZpH2JDib41x","528","static/chunks/528-7ef2006e50a52549.js?dpl=dpl_CPYCfxesaX7RKfJUQZpH2JDib41x","1742","static/chunks/1742-0ea812562873537a.js?dpl=dpl_CPYCfxesaX7RKfJUQZpH2JDib41x","1172","static/chunks/1172-89020d82938322e4.js?dpl=dpl_CPYCfxesaX7RKfJUQZpH2JDib41x","9919","static/chunks/9919-b585857c6e10fb85.js?dpl=dpl_CPYCfxesaX7RKfJUQZpH2JDib41x","9326","static/chunks/9326-103822841b140d80.js?dpl=dpl_CPYCfxesaX7RKfJUQZpH2JDib41x","4077","static/chunks/4077-cba4e88bdb106467.js?dpl=dpl_CPYCfxesaX7RKfJUQZpH2JDib41x","1924","static/chunks/1924-8c4ee98e9b0dbf83.js?dpl=dpl_CPYCfxesaX7RKfJUQZpH2JDib41x","2530","static/chunks/2530-9eb218eca5ffc00b.js?dpl=dpl_CPYCfxesaX7RKfJUQZpH2JDib41x","7177","static/chunks/app/layout-75dbb92d3cda2f1c.js?dpl=dpl_CPYCfxesaX7RKfJUQZpH2JDib41x"],"GoogleTagManager"]
5:I[4411,["6693","static/chunks/fba4ba2d-460e04194f22506f.js?dpl=dpl_CPYCfxesaX7RKfJUQZpH2JDib41x","3009","static/chunks/6a7d804d-a5cc510ceffe206f.js?dpl=dpl_CPYCfxesaX7RKfJUQZpH2JDib41x","7505","static/chunks/c02d83f4-5637599209ef9447.js?dpl=dpl_CPYCfxesaX7RKfJUQZpH2JDib41x","1737","static/chunks/fe207bbb-c84ed91deca4f888.js?dpl=dpl_CPYCfxesaX7RKfJUQZpH2JDib41x","9509","static/chunks/9509-6125acd3006111c1.js?dpl=dpl_CPYCfxesaX7RKfJUQZpH2JDib41x","4378","static/chunks/4378-3f82908971052aa9.js?dpl=dpl_CPYCfxesaX7RKfJUQZpH2JDib41x","5289","static/chunks/5289-131715863bbab062.js?dpl=dpl_CPYCfxesaX7RKfJUQZpH2JDib41x","4094","static/chunks/4094-eaa6158623fe27ff.js?dpl=dpl_CPYCfxesaX7RKfJUQZpH2JDib41x","4982","static/chunks/4982-a4b2ee93ffd82ffd.js?dpl=dpl_CPYCfxesaX7RKfJUQZpH2JDib41x","1810","static/chunks/1810-cf4ca0391c1ddf2a.js?dpl=dpl_CPYCfxesaX7RKfJUQZpH2JDib41x","6397","static/chunks/6397-b7ccd1edf8aedf12.js?dpl=dpl_CPYCfxesaX7RKfJUQZpH2JDib41x","7979","static/chunks/7979-1799576a8e82a4f3.js?dpl=dpl_CPYCfxesaX7RKfJUQZpH2JDib41x","144","static/chunks/144-1a048554a0613a1b.js?dpl=dpl_CPYCfxesaX7RKfJUQZpH2JDib41x","2610","static/chunks/2610-c41f461a4ed7cf24.js?dpl=dpl_CPYCfxesaX7RKfJUQZpH2JDib41x","528","static/chunks/528-7ef2006e50a52549.js?dpl=dpl_CPYCfxesaX7RKfJUQZpH2JDib41x","1742","static/chunks/1742-0ea812562873537a.js?dpl=dpl_CPYCfxesaX7RKfJUQZpH2JDib41x","1172","static/chunks/1172-89020d82938322e4.js?dpl=dpl_CPYCfxesaX7RKfJUQZpH2JDib41x","9919","static/chunks/9919-b585857c6e10fb85.js?dpl=dpl_CPYCfxesaX7RKfJUQZpH2JDib41x","9326","static/chunks/9326-103822841b140d80.js?dpl=dpl_CPYCfxesaX7RKfJUQZpH2JDib41x","4077","static/chunks/4077-cba4e88bdb106467.js?dpl=dpl_CPYCfxesaX7RKfJUQZpH2JDib41x","1924","static/chunks/1924-8c4ee98e9b0dbf83.js?dpl=dpl_CPYCfxesaX7RKfJUQZpH2JDib41x","2530","static/chunks/2530-9eb218eca5ffc00b.js?dpl=dpl_CPYCfxesaX7RKfJUQZpH2JDib41x","7177","static/chunks/app/layout-75dbb92d3cda2f1c.js?dpl=dpl_CPYCfxesaX7RKfJUQZpH2JDib41x"],"FilmAwardStrip"]
6:"$Sreact.suspense"
7:I[40459,["6693","static/chunks/fba4ba2d-460e04194f22506f.js?dpl=dpl_CPYCfxesaX7RKfJUQZpH2JDib41x","3009","static/chunks/6a7d804d-a5cc510ceffe206f.js?dpl=dpl_CPYCfxesaX7RKfJUQZpH2JDib41x","7505","static/chunks/c02d83f4-5637599209ef9447.js?dpl=dpl_CPYCfxesaX7RKfJUQZpH2JDib41x","1737","static/chunks/fe207bbb-c84ed91deca4f888.js?dpl=dpl_CPYCfxesaX7RKfJUQZpH2JDib41x","9509","static/chunks/9509-6125acd3006111c1.js?dpl=dpl_CPYCfxesaX7RKfJUQZpH2JDib41x","4378","static/chunks/4378-3f82908971052aa9.js?dpl=dpl_CPYCfxesaX7RKfJUQZpH2JDib41x","5289","static/chunks/5289-131715863bbab062.js?dpl=dpl_CPYCfxesaX7RKfJUQZpH2JDib41x","4094","static/chunks/4094-eaa6158623fe27ff.js?dpl=dpl_CPYCfxesaX7RKfJUQZpH2JDib41x","4982","static/chunks/4982-a4b2ee93ffd82ffd.js?dpl=dpl_CPYCfxesaX7RKfJUQZpH2JDib41x","1810","static/chunks/1810-cf4ca0391c1ddf2a.js?dpl=dpl_CPYCfxesaX7RKfJUQZpH2JDib41x","6397","static/chunks/6397-b7ccd1edf8aedf12.js?dpl=dpl_CPYCfxesaX7RKfJUQZpH2JDib41x","7979","static/chunks/7979-1799576a8e82a4f3.js?dpl=dpl_CPYCfxesaX7RKfJUQZpH2JDib41x","144","static/chunks/144-1a048554a0613a1b.js?dpl=dpl_CPYCfxesaX7RKfJUQZpH2JDib41x","2610","static/chunks/2610-c41f461a4ed7cf24.js?dpl=dpl_CPYCfxesaX7RKfJUQZpH2JDib41x","528","static/chunks/528-7ef2006e50a52549.js?dpl=dpl_CPYCfxesaX7RKfJUQZpH2JDib41x","1742","static/chunks/1742-0ea812562873537a.js?dpl=dpl_CPYCfxesaX7RKfJUQZpH2JDib41x","1172","static/chunks/1172-89020d82938322e4.js?dpl=dpl_CPYCfxesaX7RKfJUQZpH2JDib41x","9919","static/chunks/9919-b585857c6e10fb85.js?dpl=dpl_CPYCfxesaX7RKfJUQZpH2JDib41x","9326","static/chunks/9326-103822841b140d80.js?dpl=dpl_CPYCfxesaX7RKfJUQZpH2JDib41x","4077","static/chunks/4077-cba4e88bdb106467.js?dpl=dpl_CPYCfxesaX7RKfJUQZpH2JDib41x","1924","static/chunks/1924-8c4ee98e9b0dbf83.js?dpl=dpl_CPYCfxesaX7RKfJUQZpH2JDib41x","2530","static/chunks/2530-9eb218eca5ffc00b.js?dpl=dpl_CPYCfxesaX7RKfJUQZpH2JDib41x","7177","static/chunks/app/layout-75dbb92d3cda2f1c.js?dpl=dpl_CPYCfxesaX7RKfJUQZpH2JDib41x"],"Navbar"]
8:I[15848,[],""]
9:I[55256,["6693","static/chunks/fba4ba2d-460e04194f22506f.js?dpl=dpl_CPYCfxesaX7RKfJUQZpH2JDib41x","3009","static/chunks/6a7d804d-a5cc510ceffe206f.js?dpl=dpl_CPYCfxesaX7RKfJUQZpH2JDib41x","7505","static/chunks/c02d83f4-5637599209ef9447.js?dpl=dpl_CPYCfxesaX7RKfJUQZpH2JDib41x","9509","static/chunks/9509-6125acd3006111c1.js?dpl=dpl_CPYCfxesaX7RKfJUQZpH2JDib41x","4378","static/chunks/4378-3f82908971052aa9.js?dpl=dpl_CPYCfxesaX7RKfJUQZpH2JDib41x","1742","static/chunks/1742-0ea812562873537a.js?dpl=dpl_CPYCfxesaX7RKfJUQZpH2JDib41x","1172","static/chunks/1172-89020d82938322e4.js?dpl=dpl_CPYCfxesaX7RKfJUQZpH2JDib41x","8039","static/chunks/app/error-332e154bd557e323.js?dpl=dpl_CPYCfxesaX7RKfJUQZpH2JDib41x"],"default"]
a:I[62142,[],""]
19:I[79302,["4219","static/chunks/app/global-error-f07d85f704128170.js?dpl=dpl_CPYCfxesaX7RKfJUQZpH2JDib41x"],"default"]
:HL["/_next/static/media/7d4881bb7e1bf84d-s.p.woff2","font",{"crossOrigin":"","type":"font/woff2"}]
:HL["/_next/static/css/c91c557421edbcc1.css?dpl=dpl_CPYCfxesaX7RKfJUQZpH2JDib41x","style"]
:HL["/_next/static/css/9c4f0c3be44ead33.css?dpl=dpl_CPYCfxesaX7RKfJUQZpH2JDib41x","style"]
2:T412,
(function () {
  window.dataLayer = window.dataLayer || [];
  function gtag() { window.dataLayer.push(arguments); }

  gtag('consent', 'default', {
    ad_storage: 'denied',
    ad_user_data: 'denied',
    ad_personalization: 'denied',
    analytics_storage: 'denied',
    functionality_storage: 'denied',
    personalization_storage: 'denied',
    security_storage: 'granted'
  });

  try {
    var match = document.cookie.match(/(?:^|;\s*)gdpr_consent=([^;]*)/);
    if (!match) return;
    var saved = JSON.parse(decodeURIComponent(match[1]));
    if (!saved || typeof saved !== 'object') return;
    gtag('consent', 'update', {
      analytics_storage: saved.analytics ? 'granted' : 'denied',
      ad_storage: saved.marketing ? 'granted' : 'denied',
      ad_user_data: saved.marketing ? 'granted' : 'denied',
      ad_personalization: saved.marketing ? 'granted' : 'denied',
      functionality_storage: saved.functional ? 'granted' : 'denied'
    });
  } catch (e) {
    /* malformed cookie â€” the denied default stands */
  }
})();
0:{"P":null,"b":"vX-6P7rGIK5v7u82yfIum","p":"","c":["","models","z-image-turbo"],"i":false,"f":[[["",{"children":["models",{"children":[["route","z-image-turbo","d"],{"children":["__PAGE__",{}]}]}]},"$undefined","$undefined",true],["",["$","$1","c",{"children":[[["$","link","0",{"rel":"stylesheet","href":"/_next/static/css/c91c557421edbcc1.css?dpl=dpl_CPYCfxesaX7RKfJUQZpH2JDib41x","precedence":"next","crossOrigin":"$undefined","nonce":"$undefined"}],["$","link","1",{"rel":"stylesheet","href":"/_next/static/css/9c4f0c3be44ead33.css?dpl=dpl_CPYCfxesaX7RKfJUQZpH2JDib41x","precedence":"next","crossOrigin":"$undefined","nonce":"$undefined"}]],["$","html",null,{"lang":"en","suppressHydrationWarning":true,"className":"__variable_8c25df","children":[["$","head",null,{"children":[["$","script",null,{"id":"consent-mode-default","dangerouslySetInnerHTML":{"__html":"$2"}}],["$","script",null,{"id":"film-award-dismissed","dangerouslySetInnerHTML":{"__html":"try{if(document.cookie.split(';').some(function(c){return c.trim()===\"film_award_2027_dismissed=1\"}))document.documentElement.setAttribute(\"data-film-award-dismissed\",'')}catch(e){}"}}],["$","link",null,{"rel":"preconnect","href":"https://images.segmind.com"}],["$","link",null,{"rel":"preconnect","href":"https://segmind-resources.s3.amazonaws.com"}],["$","link",null,{"rel":"preconnect","href":"https://www.googletagmanager.com"}],["$","link",null,{"rel":"preload","href":"/fonts/Satoshi-Variable.woff2","as":"font","type":"font/woff2","crossOrigin":"anonymous"}]]}],["$","body",null,{"className":"antialiased bg-background text-foreground","children":["$","$L3",null,{"children":[["$","$L4",null,{"gtmId":"GTM-MHW23H4Z"}],["$","div",null,{"className":"min-h-screen flex flex-col","children":[["$","$L5",null,{}],["$","$6",null,{"fallback":["$","div",null,{"className":"h-16 bg-background/95 backdrop-blur border-b border-border"}],"children":["$","$L7",null,{}]}],["$","main",null,{"className":"flex-1","children":["$","$L8",null,{"parallelRouterKey":"children","error":"$9","errorStyles":[],"errorScripts":[],"template":["$","$La",null,{}],"templateStyles":"$undefined","templateScripts":"$undefined","notFound":[["$","div",null,{"className":"min-h-screen bg-background flex items-center justify-center px-4 sm:px-6 lg:px-8","children":["$","div",null,{"className":"max-w-lg w-full text-center","children":[["$","div",null,{"className":"mb-8","children":["$","div",null,{"className":"relative","children":[["$","h1",null,{"className":"text-9xl font-bold text-muted/20 dark:text-muted/10 select-none","children":"404"}],["$","div",null,{"className":"absolute inset-0 flex items-center justify-center","children":["$","div",null,{"className":"relative","children":[["$","div",null,{"className":"absolute -top-8 -left-8 w-16 h-16 bg-brand-100 dark:bg-brand-950 rounded-full flex items-center justify-center animate-bounce","children":["$","svg",null,{"ref":"$undefined","xmlns":"http://www.w3.org/2000/svg","width":24,"height":24,"viewBox":"0 0 24 24","fill":"none","stroke":"currentColor","strokeWidth":2,"strokeLinecap":"round","strokeLinejoin":"round","className":"lucide lucide-zap w-8 h-8 text-brand-500","children":["$Lb","$undefined"]}]}],"$Lc","$Ld"]}]}]]}]}],"$Le","$Lf","$L10","$L11"]}]}],[]],"forbidden":"$undefined","unauthorized":"$undefined"}]}],"$L12"]}],"$L13","$L14"]}]}]]}]]}],{"children":["models","$L15",{"children":[["route","z-image-turbo","d"],"$L16",{"children":["__PAGE__","$L17",{},null,false]},null,false]},null,false]},null,false],"$L18",false]],"m":"$undefined","G":["$19",[]],"s":false,"S":true}
1a:I[75289,["6693","static/chunks/fba4ba2d-460e04194f22506f.js?dpl=dpl_CPYCfxesaX7RKfJUQZpH2JDib41x","3009","static/chunks/6a7d804d-a5cc510ceffe206f.js?dpl=dpl_CPYCfxesaX7RKfJUQZpH2JDib41x","7505","static/chunks/c02d83f4-5637599209ef9447.js?dpl=dpl_CPYCfxesaX7RKfJUQZpH2JDib41x","6541","static/chunks/fb4e7fc9-e31ad622f5fde25d.js?dpl=dpl_CPYCfxesaX7RKfJUQZpH2JDib41x","9761","static/chunks/998e86a0-e112630ec4db17dc.js?dpl=dpl_CPYCfxesaX7RKfJUQZpH2JDib41x","9509","static/chunks/9509-6125acd3006111c1.js?dpl=dpl_CPYCfxesaX7RKfJUQZpH2JDib41x","4378","static/chunks/4378-3f82908971052aa9.js?dpl=dpl_CPYCfxesaX7RKfJUQZpH2JDib41x","5289","static/chunks/5289-131715863bbab062.js?dpl=dpl_CPYCfxesaX7RKfJUQZpH2JDib41x","4094","static/chunks/4094-eaa6158623fe27ff.js?dpl=dpl_CPYCfxesaX7RKfJUQZpH2JDib41x","4982","static/chunks/4982-a4b2ee93ffd82ffd.js?dpl=dpl_CPYCfxesaX7RKfJUQZpH2JDib41x","1810","static/chunks/1810-cf4ca0391c1ddf2a.js?dpl=dpl_CPYCfxesaX7RKfJUQZpH2JDib41x","6118","static/chunks/6118-7328b7d3f629a5ef.js?dpl=dpl_CPYCfxesaX7RKfJUQZpH2JDib41x","7979","static/chunks/7979-1799576a8e82a4f3.js?dpl=dpl_CPYCfxesaX7RKfJUQZpH2JDib41x","393","static/chunks/393-7cd2157fc3790475.js?dpl=dpl_CPYCfxesaX7RKfJUQZpH2JDib41x","3985","static/chunks/3985-1f9bcb95de313d61.js?dpl=dpl_CPYCfxesaX7RKfJUQZpH2JDib41x","2610","static/chunks/2610-c41f461a4ed7cf24.js?dpl=dpl_CPYCfxesaX7RKfJUQZpH2JDib41x","4844","static/chunks/4844-011fe3465334e7d0.js?dpl=dpl_CPYCfxesaX7RKfJUQZpH2JDib41x","9305","static/chunks/9305-0f5d0f2a661afddc.js?dpl=dpl_CPYCfxesaX7RKfJUQZpH2JDib41x","713","static/chunks/713-dcb3ca4f0233704d.js?dpl=dpl_CPYCfxesaX7RKfJUQZpH2JDib41x","3504","static/chunks/3504-ae9bc2dc93d2ef47.js?dpl=dpl_CPYCfxesaX7RKfJUQZpH2JDib41x","1742","static/chunks/1742-0ea812562873537a.js?dpl=dpl_CPYCfxesaX7RKfJUQZpH2JDib41x","1172","static/chunks/1172-89020d82938322e4.js?dpl=dpl_CPYCfxesaX7RKfJUQZpH2JDib41x","9919","static/chunks/9919-b585857c6e10fb85.js?dpl=dpl_CPYCfxesaX7RKfJUQZpH2JDib41x","9326","static/chunks/9326-103822841b140d80.js?dpl=dpl_CPYCfxesaX7RKfJUQZpH2JDib41x","1885","static/chunks/1885-f206f5873f09b3e2.js?dpl=dpl_CPYCfxesaX7RKfJUQZpH2JDib41x","4077","static/chunks/4077-cba4e88bdb106467.js?dpl=dpl_CPYCfxesaX7RKfJUQZpH2JDib41x","5126","static/chunks/5126-bdde68ce894e4935.js?dpl=dpl_CPYCfxesaX7RKfJUQZpH2JDib41x","5642","static/chunks/5642-c80cb7ee6e914a6a.js?dpl=dpl_CPYCfxesaX7RKfJUQZpH2JDib41x","1924","static/chunks/1924-8c4ee98e9b0dbf83.js?dpl=dpl_CPYCfxesaX7RKfJUQZpH2JDib41x","6372","static/chunks/6372-3e2880fc7d769d1f.js?dpl=dpl_CPYCfxesaX7RKfJUQZpH2JDib41x","1289","static/chunks/1289-4fdf72847f7ef615.js?dpl=dpl_CPYCfxesaX7RKfJUQZpH2JDib41x","8382","static/chunks/8382-004a14550e3769cc.js?dpl=dpl_CPYCfxesaX7RKfJUQZpH2JDib41x","1951","static/chunks/app/models/%5Broute%5D/page-c5fd4df0a8a5cab4.js?dpl=dpl_CPYCfxesaX7RKfJUQZpH2JDib41x"],""]
1b:I[4717,["6693","static/chunks/fba4ba2d-460e04194f22506f.js?dpl=dpl_CPYCfxesaX7RKfJUQZpH2JDib41x","3009","static/chunks/6a7d804d-a5cc510ceffe206f.js?dpl=dpl_CPYCfxesaX7RKfJUQZpH2JDib41x","7505","static/chunks/c02d83f4-5637599209ef9447.js?dpl=dpl_CPYCfxesaX7RKfJUQZpH2JDib41x","1737","static/chunks/fe207bbb-c84ed91deca4f888.js?dpl=dpl_CPYCfxesaX7RKfJUQZpH2JDib41x","9509","static/chunks/9509-6125acd3006111c1.js?dpl=dpl_CPYCfxesaX7RKfJUQZpH2JDib41x","4378","static/chunks/4378-3f82908971052aa9.js?dpl=dpl_CPYCfxesaX7RKfJUQZpH2JDib41x","5289","static/chunks/5289-131715863bbab062.js?dpl=dpl_CPYCfxesaX7RKfJUQZpH2JDib41x","4094","static/chunks/4094-eaa6158623fe27ff.js?dpl=dpl_CPYCfxesaX7RKfJUQZpH2JDib41x","4982","static/chunks/4982-a4b2ee93ffd82ffd.js?dpl=dpl_CPYCfxesaX7RKfJUQZpH2JDib41x","1810","static/chunks/1810-cf4ca0391c1ddf2a.js?dpl=dpl_CPYCfxesaX7RKfJUQZpH2JDib41x","6397","static/chunks/6397-b7ccd1edf8aedf12.js?dpl=dpl_CPYCfxesaX7RKfJUQZpH2JDib41x","7979","static/chunks/7979-1799576a8e82a4f3.js?dpl=dpl_CPYCfxesaX7RKfJUQZpH2JDib41x","144","static/chunks/144-1a048554a0613a1b.js?dpl=dpl_CPYCfxesaX7RKfJUQZpH2JDib41x","2610","static/chunks/2610-c41f461a4ed7cf24.js?dpl=dpl_CPYCfxesaX7RKfJUQZpH2JDib41x","528","static/chunks/528-7ef2006e50a52549.js?dpl=dpl_CPYCfxesaX7RKfJUQZpH2JDib41x","1742","static/chunks/1742-0ea812562873537a.js?dpl=dpl_CPYCfxesaX7RKfJUQZpH2JDib41x","1172","static/chunks/1172-89020d82938322e4.js?dpl=dpl_CPYCfxesaX7RKfJUQZpH2JDib41x","9919","static/chunks/9919-b585857c6e10fb85.js?dpl=dpl_CPYCfxesaX7RKfJUQZpH2JDib41x","9326","static/chunks/9326-103822841b140d80.js?dpl=dpl_CPYCfxesaX7RKfJUQZpH2JDib41x","4077","static/chunks/4077-cba4e88bdb106467.js?dpl=dpl_CPYCfxesaX7RKfJUQZpH2JDib41x","1924","static/chunks/1924-8c4ee98e9b0dbf83.js?dpl=dpl_CPYCfxesaX7RKfJUQZpH2JDib41x","2530","static/chunks/2530-9eb218eca5ffc00b.js?dpl=dpl_CPYCfxesaX7RKfJUQZpH2JDib41x","7177","static/chunks/app/layout-75dbb92d3cda2f1c.js?dpl=dpl_CPYCfxesaX7RKfJUQZpH2JDib41x"],"Footer"]
1c:I[35733,["6693","static/chunks/fba4ba2d-460e04194f22506f.js?dpl=dpl_CPYCfxesaX7RKfJUQZpH2JDib41x","3009","static/chunks/6a7d804d-a5cc510ceffe206f.js?dpl=dpl_CPYCfxesaX7RKfJUQZpH2JDib41x","7505","static/chunks/c02d83f4-5637599209ef9447.js?dpl=dpl_CPYCfxesaX7RKfJUQZpH2JDib41x","9509","static/chunks/9509-6125acd3006111c1.js?dpl=dpl_CPYCfxesaX7RKfJUQZpH2JDib41x","4378","static/chunks/4378-3f82908971052aa9.js?dpl=dpl_CPYCfxesaX7RKfJUQZpH2JDib41x","6397","static/chunks/6397-b7ccd1edf8aedf12.js?dpl=dpl_CPYCfxesaX7RKfJUQZpH2JDib41x","1742","static/chunks/1742-0ea812562873537a.js?dpl=dpl_CPYCfxesaX7RKfJUQZpH2JDib41x","341","static/chunks/app/models/(catalogue)/loading-03c2017343ab8539.js?dpl=dpl_CPYCfxesaX7RKfJUQZpH2JDib41x"],"Toaster"]
1d:I[20659,["6693","static/chunks/fba4ba2d-460e04194f22506f.js?dpl=dpl_CPYCfxesaX7RKfJUQZpH2JDib41x","3009","static/chunks/6a7d804d-a5cc510ceffe206f.js?dpl=dpl_CPYCfxesaX7RKfJUQZpH2JDib41x","7505","static/chunks/c02d83f4-5637599209ef9447.js?dpl=dpl_CPYCfxesaX7RKfJUQZpH2JDib41x","1737","static/chunks/fe207bbb-c84ed91deca4f888.js?dpl=dpl_CPYCfxesaX7RKfJUQZpH2JDib41x","9509","static/chunks/9509-6125acd3006111c1.js?dpl=dpl_CPYCfxesaX7RKfJUQZpH2JDib41x","4378","static/chunks/4378-3f82908971052aa9.js?dpl=dpl_CPYCfxesaX7RKfJUQZpH2JDib41x","5289","static/chunks/5289-131715863bbab062.js?dpl=dpl_CPYCfxesaX7RKfJUQZpH2JDib41x","4094","static/chunks/4094-eaa6158623fe27ff.js?dpl=dpl_CPYCfxesaX7RKfJUQZpH2JDib41x","4982","static/chunks/4982-a4b2ee93ffd82ffd.js?dpl=dpl_CPYCfxesaX7RKfJUQZpH2JDib41x","1810","static/chunks/1810-cf4ca0391c1ddf2a.js?dpl=dpl_CPYCfxesaX7RKfJUQZpH2JDib41x","6397","static/chunks/6397-b7ccd1edf8aedf12.js?dpl=dpl_CPYCfxesaX7RKfJUQZpH2JDib41x","7979","static/chunks/7979-1799576a8e82a4f3.js?dpl=dpl_CPYCfxesaX7RKfJUQZpH2JDib41x","144","static/chunks/144-1a048554a0613a1b.js?dpl=dpl_CPYCfxesaX7RKfJUQZpH2JDib41x","2610","static/chunks/2610-c41f461a4ed7cf24.js?dpl=dpl_CPYCfxesaX7RKfJUQZpH2JDib41x","528","static/chunks/528-7ef2006e50a52549.js?dpl=dpl_CPYCfxesaX7RKfJUQZpH2JDib41x","1742","static/chunks/1742-0ea812562873537a.js?dpl=dpl_CPYCfxesaX7RKfJUQZpH2JDib41x","1172","static/chunks/1172-89020d82938322e4.js?dpl=dpl_CPYCfxesaX7RKfJUQZpH2JDib41x","9919","static/chunks/9919-b585857c6e10fb85.js?dpl=dpl_CPYCfxesaX7RKfJUQZpH2JDib41x","9326","static/chunks/9326-103822841b140d80.js?dpl=dpl_CPYCfxesaX7RKfJUQZpH2JDib41x","4077","static/chunks/4077-cba4e88bdb106467.js?dpl=dpl_CPYCfxesaX7RKfJUQZpH2JDib41x","1924","static/chunks/1924-8c4ee98e9b0dbf83.js?dpl=dpl_CPYCfxesaX7RKfJUQZpH2JDib41x","2530","static/chunks/2530-9eb218eca5ffc00b.js?dpl=dpl_CPYCfxesaX7RKfJUQZpH2JDib41x","7177","static/chunks/app/layout-75dbb92d3cda2f1c.js?dpl=dpl_CPYCfxesaX7RKfJUQZpH2JDib41x"],"LazyLayoutExtras"]
20:I[30661,[],"OutletBoundary"]
22:I[72272,[],"AsyncMetadataOutlet"]
24:I[30661,[],"ViewportBoundary"]
26:I[30661,[],"MetadataBoundary"]
b:["$","path","1xq2db",{"d":"M4 14a1 1 0 0 1-.78-1.63l9.9-10.2a.5.5 0 0 1 .86.46l-1.92 6.02A1 1 0 0 0 13 10h7a1 1 0 0 1 .78 1.63l-9.9 10.2a.5.5 0 0 1-.86-.46l1.92-6.02A1 1 0 0 0 11 14z"}]
c:["$","div",null,{"className":"absolute -top-4 -right-12 w-12 h-12 bg-brand-secondary-100 dark:bg-brand-secondary-950 rounded-full flex items-center justify-center animate-pulse","children":["$","svg",null,{"ref":"$undefined","xmlns":"http://www.w3.org/2000/svg","width":24,"height":24,"viewBox":"0 0 24 24","fill":"none","stroke":"currentColor","strokeWidth":2,"strokeLinecap":"round","strokeLinejoin":"round","className":"lucide lucide-search w-6 h-6 text-brand-secondary-500","children":[["$","circle","4ej97u",{"cx":"11","cy":"11","r":"8"}],["$","path","1qie3q",{"d":"m21 21-4.3-4.3"}],"$undefined"]}]}]
d:["$","div",null,{"className":"absolute -bottom-6 left-4 w-10 h-10 bg-green-100 dark:bg-green-950 rounded-full flex items-center justify-center animate-bounce delay-200","children":["$","div",null,{"className":"w-3 h-3 bg-green-500 rounded-full"}]}]
e:["$","div",null,{"className":"mb-8","children":[["$","h2",null,{"className":"text-2xl font-semibold text-foreground mb-4","children":"Page Not Found"}],["$","p",null,{"className":"text-muted-foreground text-lg mb-2","children":"Oops! The page you're looking for doesn't exist."}],["$","p",null,{"className":"text-muted-foreground","children":"It might have been moved, deleted, or you entered the wrong URL."}]]}]
f:["$","div",null,{"className":"flex flex-col sm:flex-row gap-4 justify-center items-center mb-12","children":[["$","$L1a",null,{"href":"/","className":"inline-flex items-center justify-center gap-2 px-6 py-3 bg-brand-600 dark:bg-brand-500 text-white rounded-lg hover:bg-brand-700 dark:hover:bg-brand-600 transition-colors font-medium text-base w-full sm:w-auto","children":[["$","svg",null,{"ref":"$undefined","xmlns":"http://www.w3.org/2000/svg","width":24,"height":24,"viewBox":"0 0 24 24","fill":"none","stroke":"currentColor","strokeWidth":2,"strokeLinecap":"round","strokeLinejoin":"round","className":"lucide lucide-house w-5 h-5","children":[["$","path","5wwlr5",{"d":"M15 21v-8a1 1 0 0 0-1-1h-4a1 1 0 0 0-1 1v8"}],["$","path","1d0kgt",{"d":"M3 10a2 2 0 0 1 .709-1.528l7-5.999a2 2 0 0 1 2.582 0l7 5.999A2 2 0 0 1 21 10v9a2 2 0 0 1-2 2H5a2 2 0 0 1-2-2z"}],"$undefined"]}],"Go Home"]}],["$","$L1a",null,{"href":"/models","className":"inline-flex items-center justify-center gap-2 px-6 py-3 bg-surface border border-border text-foreground rounded-lg hover:bg-surface/80 transition-colors font-medium text-base w-full sm:w-auto","children":[["$","svg",null,{"ref":"$undefined","xmlns":"http://www.w3.org/2000/svg","width":24,"height":24,"viewBox":"0 0 24 24","fill":"none","stroke":"currentColor","strokeWidth":2,"strokeLinecap":"round","strokeLinejoin":"round","className":"lucide lucide-search w-5 h-5","children":[["$","circle","4ej97u",{"cx":"11","cy":"11","r":"8"}],["$","path","1qie3q",{"d":"m21 21-4.3-4.3"}],"$undefined"]}],"Browse Models"]}]]}]
10:["$","div",null,{"className":"border-t border-border pt-8","children":[["$","p",null,{"className":"text-sm text-muted-foreground mb-4","children":"Popular destinations:"}],["$","div",null,{"className":"flex flex-wrap justify-center gap-4 text-sm","children":[["$","$L1a",null,{"href":"/models/tags/image","className":"text-brand-600 dark:text-brand-400 hover:text-brand-700 dark:hover:text-brand-300 transition-colors","children":"Image Models"}],["$","span",null,{"className":"text-muted-foreground","children":"â€¢"}],["$","$L1a",null,{"href":"/models/tags/video","className":"text-brand-600 dark:text-brand-400 hover:text-brand-700 dark:hover:text-brand-300 transition-colors","children":"Video Models"}],["$","span",null,{"className":"text-muted-foreground","children":"â€¢"}],["$","$L1a",null,{"href":"/models/tags/llms","className":"text-brand-600 dark:text-brand-400 hover:text-brand-700 dark:hover:text-brand-300 transition-colors","children":"LLMs"}],["$","span",null,{"className":"text-muted-foreground","children":"â€¢"}],["$","$L1a",null,{"href":"/models","className":"text-brand-600 dark:text-brand-400 hover:text-brand-700 dark:hover:text-brand-300 transition-colors","children":"All Models"}]]}]]}]
11:["$","div",null,{"className":"mt-8","children":["$","$L1a",null,{"href":"/","className":"inline-flex items-center text-sm text-muted-foreground hover:text-foreground transition-colors","children":[["$","svg",null,{"ref":"$undefined","xmlns":"http://www.w3.org/2000/svg","width":24,"height":24,"viewBox":"0 0 24 24","fill":"none","stroke":"currentColor","strokeWidth":2,"strokeLinecap":"round","strokeLinejoin":"round","className":"lucide lucide-arrow-left w-4 h-4 mr-2","children":[["$","path","1l729n",{"d":"m12 19-7-7 7-7"}],["$","path","x3x0zl",{"d":"M19 12H5"}],"$undefined"]}],"Go back to homepage"]}]}]
12:["$","$L1b",null,{}]
13:["$","$L1c",null,{"closeButton":true,"toastOptions":{"duration":30000}}]
14:["$","$L1d",null,{}]
15:["$","$1","c",{"children":[null,["$","$L8",null,{"parallelRouterKey":"children","error":"$undefined","errorStyles":"$undefined","errorScripts":"$undefined","template":["$","$La",null,{}],"templateStyles":"$undefined","templateScripts":"$undefined","notFound":"$undefined","forbidden":"$undefined","unauthorized":"$undefined"}]]}]
16:["$","$1","c",{"children":[null,"$L1e"]}]
17:["$","$1","c",{"children":["$L1f",null,["$","$L20",null,{"children":["$L21",["$","$L22",null,{"promise":"$@23"}]]}]]}]
18:["$","$1","h",{"children":[null,[["$","$L24",null,{"children":"$L25"}],["$","meta",null,{"name":"next-size-adjust","content":""}]],["$","$L26",null,{"children":["$","div",null,{"hidden":true,"children":["$","$6",null,{"fallback":null,"children":"$L27"}]}]}]]}]
25:[["$","meta","0",{"charSet":"utf-8"}],["$","meta","1",{"name":"viewport","content":"width=device-width, initial-scale=1"}]]
21:null
28:I[53921,["6693","static/chunks/fba4ba2d-460e04194f22506f.js?dpl=dpl_CPYCfxesaX7RKfJUQZpH2JDib41x","3009","static/chunks/6a7d804d-a5cc510ceffe206f.js?dpl=dpl_CPYCfxesaX7RKfJUQZpH2JDib41x","7505","static/chunks/c02d83f4-5637599209ef9447.js?dpl=dpl_CPYCfxesaX7RKfJUQZpH2JDib41x","9509","static/chunks/9509-6125acd3006111c1.js?dpl=dpl_CPYCfxesaX7RKfJUQZpH2JDib41x","4378","static/chunks/4378-3f82908971052aa9.js?dpl=dpl_CPYCfxesaX7RKfJUQZpH2JDib41x","5289","static/chunks/5289-131715863bbab062.js?dpl=dpl_CPYCfxesaX7RKfJUQZpH2JDib41x","1742","static/chunks/1742-0ea812562873537a.js?dpl=dpl_CPYCfxesaX7RKfJUQZpH2JDib41x","1172","static/chunks/1172-89020d82938322e4.js?dpl=dpl_CPYCfxesaX7RKfJUQZpH2JDib41x","7213","static/chunks/7213-ed3acee0c865cd60.js?dpl=dpl_CPYCfxesaX7RKfJUQZpH2JDib41x","7256","static/chunks/app/models/%5Broute%5D/layout-23522cb6540a765c.js?dpl=dpl_CPYCfxesaX7RKfJUQZpH2JDib41x"],"default"]
2e:I[4704,[],"IconMark"]
29:T1320,# Z-Image-Turbo: Fast Text-to-Image Model with Bilingual Support

**Edited by Segmind Team on December 1, 2025.**

---

## What is Z-Image-Turbo?

**Z-Image-Turbo** is a high-speed text-to-image generation model from **Tongyi-MAI**; it is built on a 6â€‘billionâ€‘parameter single-stream diffusion transformer architecture. The model is a member of the Z-Image family, and this version delivers photorealistic results in under a second for rapid iterations. â€‹
**Z-Image-Turbo** is designed to run efficiently on consumer-grade GPUs, so developers and small teams can achieve professional-quality AI image generation without specialized hardware, setting it apart from many contemporary image models that require complex computational infrastructure or resources. It also provides native bilingual support for English and Chinese text in generated images, making it an invaluable asset for global applications and multilingual content workflows.


## Key Features of  Z-Image-Turbo

- **Sub-second generation speed** with as few as 10 inference steps for high-quality results 
- **Bilingual text rendering** that supports English and Chinese characters in generated images
- **6-billion parameter architecture** balancing model capability with resource efficiency
- **Consumer GPU compatibility** that enables local deployment without enterprise infrastructure
- **Advanced distillation techniques** and reinforcement learning optimization for enhanced output quality
- **Flexible resolution support** ranging from 256Ã—256 to 2048Ã—2048 pixels for desired image output quality
- **Multiple output formats**, including JPEG, PNG, and WebP, which offer flexibility with adjustable quality settings

## Best Use Cases

Z-Image-Turbo excels in rapid iteration and bilingual content generation, making it an asset for: 

- **Marketing teams** as they can quickly prototype visual concepts for campaigns targeting a global audience, especially the English and Chinese speakers. 
- **Game developers** benefit from fast asset generation during prototyping phases. 
- **E-commerce platforms** can design product mockups and lifestyle imagery at scale. 
- **Real-time applications** such as interactive design tools or chatbot-integrated image generation. 
- **Content creators** can produce multilingual social media content utilizing its accurate text rendering, eliminating the need for post-generation text overlays.

## Prompt Tips and Output Quality

- For optimal results, use descriptive prompts with clear subject, style, and composition details. 
- Utilise the **steps parameter**: 10 steps for quick previews and 40-50 steps for production-ready images. 
- Implement **guidance scale** to control prompt adherence: values around 5 provide creative freedom, and values of 8-10 enforce strict interpretation of the prompt.
- For images with text, specify the language and text placement clearly; for example - *"A Chinese restaurant sign saying 'ç¾Žé£Ÿå¤©å ‚' in glowing neon"*. 
- For consistent results across iterations, set a fixed **seed value**; use -1 for random variation. 
- Adjust the **height and width** in 64-pixel increments: 512Ã—512 for web use, while 1024Ã—1024 or higher suits print materials.

## FAQs

**Is Z-Image-Turbo open-source?**  
**Z-Image-Turbo** is part of the Z-Image family, which includes Z-Image-Base, designed specifically for community fine-tuning, offering robust support for open development and customization.

**How does it differ from other text-to-image models?**  
**Z-Image-Turbo** offers exceptional speed (sub-second generation), native bilingual text support (English and Chinese), and optimization for consumer GPUs. Therefore, Z-Image-Turbo distinguishes itself from most competing models that require more inference steps or enterprise-grade hardware for comparable quality.

**What parameters should I tweak for the best results?**  
Start with 10-20 steps and a guidance scale of 5; increase steps to 40-50 for final outputs. You can adjust the guidance scale higher (7-10) if the model isn't following your prompt closely, or lower the scale (3-5) for more creative interpretation.

**Can I generate images with Chinese text?**  
Yes, **Z-Image-Turbo** supports bilingual text rendering; you may specify Chinese characters directly in the prompt to accurately generate text elements in images.

**What resolution should I use for different applications?**  
Use '512Ã—512' for social media and web previews; '1024Ã—1024' for detailed digital content; and '2048Ã—2048' for print-quality materials. Furthermore, higher resolutions require more inference steps for the best quality.

**What image format should I choose?**  
Choose 'JPEG' for broad compatibility and smaller file sizes; go with 'PNG' for images that need transparency or lossless quality; and 'WebP' will render the best compression-to-quality ratio in modern web applications.2a:T99a,# Z-Image-Turbo: Effective Usage Guide

Z-Image-Turbo is a 6B-parameter diffusion transformer optimized for sub-second bilingual text-to-image generation on consumer GPUs. Use this guide to craft precise prompts, choose the right parameters and achieve consistent, high-quality outputs.

## 1. Prompt Design
- Be descriptive: include subject, style, lighting and mood.  
- Specify text elements clearly: e.g., â€œA neon sign reading â€˜ç¾Žé£Ÿå¤©å ‚â€™ above a street food stall.â€  
- Combine language tags when mixing English and Chinese: e.g., â€œ[EN] Futuristic cityscape at sunset; [CN] æœªæ¥åŸŽå¸‚ æ—¥è½.â€  

## 2. Key Parameters

| Parameter         | Quick Preview       | Detailed Draft       | Production-Ready    |
|-------------------|---------------------|----------------------|---------------------|
| steps             | 10                  | 20â€“30                | 40â€“50               |
| guidance_scale    | 4â€“6                 | 6â€“8                  | 8â€“10                |
| seed              | â€“1 (random)         | Fixed (e.g., 42)     | Fixed (custom seed) |
| resolution (WÃ—H)  | 512Ã—512             | 768Ã—768 or 1024Ã—768  | 1024Ã—1024 or 2048Ã—2048 |
| image_format      | jpeg                | png or webp          | png (transparency)  |
| quality           | 60â€“80               | 80â€“90                | 90â€“100              |

## 3. Use Case Recommendations
- **Marketing Mockups**:  
  â€¢ steps=20, guidance_scale=7, 1024Ã—1024, png, quality=85.  
- **Social Media Posts**:  
  â€¢ steps=10, guidance_scale=5, 512Ã—512, webp, quality=70.  
- **Print-Quality Art**:  
  â€¢ steps=50, guidance_scale=9, 2048Ã—2048, png, quality=100.  
- **Real-Time Tools**:  
  â€¢ steps=8â€“12, guidance_scale=4â€“6, 512Ã—512, jpeg, quality=75.  

## 4. Best Practices
- Lock a **seed** for reproducibility; use `-1` for varied outputs.  
- Adjust **guidance_scale** to trade creativity vs. prompt adherence.  
- Increment resolutions in 64-pixel steps to match model training specs.  
- For bilingual text, place language notation at prompt start.  
- Use `webp` for modern web delivery; choose `png` when transparency or sharp text edges matter.  

Experiment with these settings to balance speed, fidelity, and creative freedom. With Z-Image-Turboâ€™s efficient architecture and bilingual support, you can iterate rapidly and deliver professional-grade visuals in under a second.2b:T98e,Create a vibrant and modern magazine cover for Hindi Farmer, themed for April 2025.
The main background is a cool magenta to deep-pink gradient with airy soft shadows that mirror the vivid color of ripe dragon fruit (à¤¡à¥à¤°à¥ˆà¤—à¤¨ à¤«à¥à¤°à¥‚à¤Ÿ).

Centered is a Hindi farmer, a middle-aged man with sun-tanned skin, short textured black hair, and a confident stance. He stands beside a freshly harvested pile of bright red dragon fruit arranged on geometric crates painted in matte dark teal.
He wears a lightweight dark grey field jacket, a maroon undershirt, and rugged work pants.
His expression is sharp and determined, representing precision farming and market growth in India.

Use a new font direction featuring condensed sans-serif fonts for headlines and a bold serif for key title elements.
Balance white, dark magenta, and citrus orange text across the layout with clean editorial spacing.

Text Layout (all updated to Hindi)

â€¢ Top left:
â€œà¤ªà¥à¤°à¥€à¤®à¤¿à¤¯à¤® à¤¡à¥à¤°à¥ˆà¤—à¤¨ à¤«à¥à¤°à¥‚à¤Ÿâ€ in bright orange
Subtext in white: â€œà¤•à¥ˆà¤¸à¥‡ à¤­à¤¾à¤°à¤¤à¥€à¤¯ à¤•à¤¿à¤¸à¤¾à¤¨ à¤¨à¤¿à¤°à¥à¤¯à¤¾à¤¤ à¤¬à¤¾à¤œà¤¼à¤¾à¤° à¤®à¥‡à¤‚ à¤•à¤¦à¤® à¤¬à¤¢à¤¼à¤¾ à¤°à¤¹à¥‡ à¤¹à¥ˆà¤‚â€

â€¢ Top right:
â€œà¤¶à¥à¤·à¥à¤• à¤­à¥‚à¤®à¤¿ à¤¤à¤•à¤¨à¥€à¤•â€ in bold dark magenta
Subtext: â€œà¤²à¤‚à¤¬à¥‡ à¤®à¥Œà¤¸à¤® à¤®à¥‡à¤‚ à¤Šà¤°à¥à¤œà¤¾-à¤¸à¤•à¥à¤·à¤® à¤¸à¤¿à¤‚à¤šà¤¾à¤ˆ à¤•à¥‡ à¤¨à¤ à¤¤à¤°à¥€à¤•à¥‡â€

â€¢ Center right:
Large orange â€œ18â€
Text: â€œà¤…à¤§à¤¿à¤•à¤¤à¤® à¤ªà¥ˆà¤¦à¤¾à¤µà¤¾à¤° à¤•à¥‡ à¤²à¤¿à¤ 18 à¤›à¤‚à¤Ÿà¤¾à¤ˆ à¤°à¤£à¤¨à¥€à¤¤à¤¿à¤¯à¤¾à¤â€

â€¢ Bottom left:
â€œà¤®à¥‚à¤²à¥à¤¯ à¤¯à¥à¤¦à¥à¤§â€ in dark magenta
Pale pink subtext: â€œà¤¸à¤¾à¤²à¤­à¤° à¤¡à¥à¤°à¥ˆà¤—à¤¨ à¤«à¥à¤°à¥‚à¤Ÿ à¤¬à¤¾à¤œà¤¼à¤¾à¤° à¤•à¥€ à¤¬à¤¦à¤²à¤¤à¥€ à¤—à¤¤à¤¿à¤¶à¥€à¤²à¤¤à¤¾â€

â€¢ Bottom left corner (with an orange plus sign):
â€œà¤¤à¥‡à¤œà¤¼ à¤µà¥ƒà¤¦à¥à¤§à¤¿ à¤¦à¥‡à¤¨à¥‡ à¤µà¤¾à¤²à¤¾ à¤œà¥ˆà¤µà¤¿à¤• à¤‰à¤°à¥à¤µà¤°à¤•â€

â€¢ Bottom right (over the crates):
In elegant white serif: â€œà¤²à¤¾à¤² à¤•à¤¾ à¤²à¤¾à¤­â€
Orange subheading: â€œà¤µà¥‡ à¤•à¤¿à¤¸à¤¾à¤¨ à¤œà¥‹ à¤²à¤—à¤¾à¤¤à¤¾à¤° à¤¬à¤¡à¤¼à¥€ à¤ªà¥ˆà¤¦à¤¾à¤µà¤¾à¤° à¤²à¥‡ à¤°à¤¹à¥‡ à¤¹à¥ˆà¤‚â€

Art Direction

Design should look modern, clean, and forward-focused, emphasizing:

tropical & semi-tropical horticulture

premium produce

the rising value of dragon fruit cultivation in India

Lighting should be bright studio style with soft controlled shadows.2c:T98e,Create a vibrant and modern magazine cover for Hindi Farmer, themed for April 2025.
The main background is a cool magenta to deep-pink gradient with airy soft shadows that mirror the vivid color of ripe dragon fruit (à¤¡à¥à¤°à¥ˆà¤—à¤¨ à¤«à¥à¤°à¥‚à¤Ÿ).

Centered is a Hindi farmer, a middle-aged man with sun-tanned skin, short textured black hair, and a confident stance. He stands beside a freshly harvested pile of bright red dragon fruit arranged on geometric crates painted in matte dark teal.
He wears a lightweight dark grey field jacket, a maroon undershirt, and rugged work pants.
His expression is sharp and determined, representing precision farming and market growth in India.

Use a new font direction featuring condensed sans-serif fonts for headlines and a bold serif for key title elements.
Balance white, dark magenta, and citrus orange text across the layout with clean editorial spacing.

Text Layout (all updated to Hindi)

â€¢ Top left:
â€œà¤ªà¥à¤°à¥€à¤®à¤¿à¤¯à¤® à¤¡à¥à¤°à¥ˆà¤—à¤¨ à¤«à¥à¤°à¥‚à¤Ÿâ€ in bright orange
Subtext in white: â€œà¤•à¥ˆà¤¸à¥‡ à¤­à¤¾à¤°à¤¤à¥€à¤¯ à¤•à¤¿à¤¸à¤¾à¤¨ à¤¨à¤¿à¤°à¥à¤¯à¤¾à¤¤ à¤¬à¤¾à¤œà¤¼à¤¾à¤° à¤®à¥‡à¤‚ à¤•à¤¦à¤® à¤¬à¤¢à¤¼à¤¾ à¤°à¤¹à¥‡ à¤¹à¥ˆà¤‚â€

â€¢ Top right:
â€œà¤¶à¥à¤·à¥à¤• à¤­à¥‚à¤®à¤¿ à¤¤à¤•à¤¨à¥€à¤•â€ in bold dark magenta
Subtext: â€œà¤²à¤‚à¤¬à¥‡ à¤®à¥Œà¤¸à¤® à¤®à¥‡à¤‚ à¤Šà¤°à¥à¤œà¤¾-à¤¸à¤•à¥à¤·à¤® à¤¸à¤¿à¤‚à¤šà¤¾à¤ˆ à¤•à¥‡ à¤¨à¤ à¤¤à¤°à¥€à¤•à¥‡â€

â€¢ Center right:
Large orange â€œ18â€
Text: â€œà¤…à¤§à¤¿à¤•à¤¤à¤® à¤ªà¥ˆà¤¦à¤¾à¤µà¤¾à¤° à¤•à¥‡ à¤²à¤¿à¤ 18 à¤›à¤‚à¤Ÿà¤¾à¤ˆ à¤°à¤£à¤¨à¥€à¤¤à¤¿à¤¯à¤¾à¤â€

â€¢ Bottom left:
â€œà¤®à¥‚à¤²à¥à¤¯ à¤¯à¥à¤¦à¥à¤§â€ in dark magenta
Pale pink subtext: â€œà¤¸à¤¾à¤²à¤­à¤° à¤¡à¥à¤°à¥ˆà¤—à¤¨ à¤«à¥à¤°à¥‚à¤Ÿ à¤¬à¤¾à¤œà¤¼à¤¾à¤° à¤•à¥€ à¤¬à¤¦à¤²à¤¤à¥€ à¤—à¤¤à¤¿à¤¶à¥€à¤²à¤¤à¤¾â€

â€¢ Bottom left corner (with an orange plus sign):
â€œà¤¤à¥‡à¤œà¤¼ à¤µà¥ƒà¤¦à¥à¤§à¤¿ à¤¦à¥‡à¤¨à¥‡ à¤µà¤¾à¤²à¤¾ à¤œà¥ˆà¤µà¤¿à¤• à¤‰à¤°à¥à¤µà¤°à¤•â€

â€¢ Bottom right (over the crates):
In elegant white serif: â€œà¤²à¤¾à¤² à¤•à¤¾ à¤²à¤¾à¤­â€
Orange subheading: â€œà¤µà¥‡ à¤•à¤¿à¤¸à¤¾à¤¨ à¤œà¥‹ à¤²à¤—à¤¾à¤¤à¤¾à¤° à¤¬à¤¡à¤¼à¥€ à¤ªà¥ˆà¤¦à¤¾à¤µà¤¾à¤° à¤²à¥‡ à¤°à¤¹à¥‡ à¤¹à¥ˆà¤‚â€

Art Direction

Design should look modern, clean, and forward-focused, emphasizing:

tropical & semi-tropical horticulture

premium produce

the rising value of dragon fruit cultivation in India

Lighting should be bright studio style with soft controlled shadows.1e:["$","$L28",null,{"route":"z-image-turbo","modelDetails":{"title":"Z Image Turbo","thumbnail_image":"https://segmind-resources.s3.amazonaws.com/output/z-image-turbo-9606.png","type":"textToImage","model_type":"SS","is_depreciated":false,"meta_description":"Z-Image-Turbo generates photorealistic images in under one second with bilingual text support for global applications.","seo_description":"$29","guide":"$2a","pricing_guide":null,"artifacts":[],"default_image_output":"https://segmind-resources.s3.amazonaws.com/others/bdea434f-e787-470e-91c0-2911bf580c56-z-image-turbo-op.webp","default_response":null,"parameters":{"prompt":{"isRequired":true,"affectsPricing":false,"type":"str","description":"Text prompt describing the desired image","isEnum":false,"hidden":false,"isAdvanced":false,"displayOrder":0,"component":"textarea","displayValue":"$2b","label":"Prompt"},"steps":{"isRequired":false,"affectsPricing":false,"type":"int","description":"Number of inference steps","isEnum":false,"hidden":false,"isAdvanced":true,"displayOrder":1,"component":"slider","displayValue":8,"label":"Steps","range":[1,75],"step":1,"default":8},"guidance_scale":{"isRequired":false,"affectsPricing":false,"type":"float","description":"Classifier-free guidance scale","isEnum":false,"hidden":false,"isAdvanced":true,"displayOrder":2,"component":"slider","displayValue":1,"label":"Guidance Scale","range":[0,15],"step":0.1,"default":1},"seed":{"isRequired":false,"affectsPricing":false,"type":"int","description":"Random seed for reproducibility. Use -1 for random","isEnum":false,"hidden":false,"isAdvanced":false,"displayOrder":3,"component":"slider","displayValue":-1,"label":"Seed","range":[-1,92147483647],"step":1,"default":-1},"height":{"isRequired":false,"affectsPricing":false,"type":"int","description":"Output image height in pixels","isEnum":false,"hidden":false,"isAdvanced":true,"displayOrder":4,"component":"slider","displayValue":1024,"label":"Height","range":[256,2048],"step":64,"default":1024},"width":{"isRequired":false,"affectsPricing":false,"type":"int","description":"Output image width in pixels","isEnum":false,"hidden":false,"isAdvanced":true,"displayOrder":5,"component":"slider","displayValue":1024,"label":"Width","range":[256,2048],"step":64,"default":1024},"image_format":{"isRequired":false,"affectsPricing":false,"type":"str","description":"Output image format","isEnum":true,"hidden":false,"isAdvanced":true,"displayOrder":6,"component":"dropdown","displayValue":"webp","label":"Image Format","values":["jpeg","png","webp"],"default":"webp"},"quality":{"isRequired":false,"affectsPricing":false,"type":"int","description":"Output image quality (1-100)","isEnum":false,"hidden":false,"isAdvanced":true,"displayOrder":7,"component":"slider","displayValue":90,"label":"Image Quality","range":[1,100],"step":1,"default":90},"base_64":{"isRequired":false,"affectsPricing":false,"type":"bool","description":"Return image as base64 encoded string","isEnum":false,"hidden":true,"isAdvanced":true,"displayOrder":8,"component":"checkbox","displayValue":false,"label":"Base64 Output","default":false}},"endpoints":{"main":"/v1/z-image-turbo"},"api_notes":[],"model_outputs":null,"llm_capabilities":null,"license":"","github_link":null,"inference_provider":"SEGMIND_SERVERLESS","created_ts":"2025-11-27 17:57:58.087457+00:00","slug":"z-image-turbo","name":"Z Image Turbo","description":"Photorealistic images in under one second, bilingual text.","category":"textToImage","modality":"image","input":"text","output":"image","provider":"ALIBABA","thumbnail_url":"https://segmind-resources.s3.amazonaws.com/output/z-image-turbo-9606.png","is_new":false,"coming_soon":false,"popularity_score":62,"category_percentile":85,"average_cost":0.016715829198361613,"latency_seconds":4.27188,"created_at":"2025-11-27 17:57:58.087457+00:00","parameters_schema":{"$schema":"https://json-schema.org/draft/2020-12/schema","type":"object","properties":{"prompt":{"type":"string","title":"Prompt","description":"Text prompt describing the desired image","x-ui-metadata":{"order":0,"advanced":false,"hidden":false}},"steps":{"type":"integer","title":"Steps","description":"Number of inference steps","minimum":1,"maximum":75,"default":8,"x-ui-metadata":{"order":1,"advanced":true,"hidden":false}},"guidance_scale":{"type":"number","title":"Guidance Scale","description":"Classifier-free guidance scale","minimum":0,"maximum":15,"default":1,"x-ui-metadata":{"order":2,"advanced":true,"hidden":false,"step":0.1}},"seed":{"type":"integer","title":"Seed","description":"Random seed for reproducibility. Use -1 for random","minimum":-1,"maximum":92147483647,"default":-1,"x-ui-metadata":{"order":3,"advanced":false,"hidden":false}},"height":{"type":"integer","title":"Height","description":"Output image height in pixels","minimum":256,"maximum":2048,"default":1024,"x-ui-metadata":{"order":4,"advanced":true,"hidden":false}},"width":{"type":"integer","title":"Width","description":"Output image width in pixels","minimum":256,"maximum":2048,"default":1024,"x-ui-metadata":{"order":5,"advanced":true,"hidden":false}},"image_format":{"type":"string","title":"Image Format","description":"Output image format","oneOf":[{"const":"jpeg","title":"jpeg"},{"const":"png","title":"png"},{"const":"webp","title":"webp"}],"default":"webp","x-ui-metadata":{"order":6,"advanced":true,"hidden":false}},"quality":{"type":"integer","title":"Image Quality","description":"Output image quality (1-100)","minimum":1,"maximum":100,"default":90,"x-ui-metadata":{"order":7,"advanced":true,"hidden":false}},"base_64":{"type":"boolean","title":"Base64 Output","description":"Return image as base64 encoded string","default":false,"x-ui-metadata":{"order":8,"advanced":true,"hidden":true}}},"required":["prompt"],"examples":[{"prompt":"$2c","steps":8,"guidance_scale":1,"seed":-1,"height":1024,"width":1024,"image_format":"webp","quality":90,"base_64":false}]}},"metrics":{"total_requests":null,"latency":4.27188},"children":"$L2d"}]
23:{"metadata":[["$","title","0",{"children":"Z Image Turbo API | Segmind"}],["$","meta","1",{"name":"description","content":"Z-Image-Turbo generates photorealistic images in under one second with bilingual text support for global applications."}],["$","link","2",{"rel":"canonical","href":"https://www.segmind.com/models/z-image-turbo"}],["$","meta","3",{"property":"og:title","content":"Z Image Turbo API | Segmind"}],["$","meta","4",{"property":"og:description","content":"Z-Image-Turbo generates photorealistic images in under one second with bilingual text support for global applications."}],["$","meta","5",{"property":"og:image","content":"https://segmind-resources.s3.amazonaws.com/output/z-image-turbo-9606.png"}],["$","meta","6",{"name":"twitter:card","content":"summary_large_image"}],["$","meta","7",{"name":"twitter:title","content":"Z Image Turbo API | Segmind"}],["$","meta","8",{"name":"twitter:description","content":"Z-Image-Turbo generates photorealistic images in under one second with bilingual text support for global applications."}],["$","meta","9",{"name":"twitter:image","content":"https://www.segmind.com/og/home.jpg"}],["$","link","10",{"rel":"shortcut icon","href":"/favicon.ico"}],["$","link","11",{"rel":"icon","href":"/favicon.ico","sizes":"any"}],["$","link","12",{"rel":"icon","href":"/favicon-48x48.png","type":"image/png","sizes":"48x48"}],["$","link","13",{"rel":"icon","href":"/favicon-192x192.png","type":"image/png","sizes":"192x192"}],["$","link","14",{"rel":"icon","href":"/favicon.svg","type":"image/svg+xml"}],["$","link","15",{"rel":"apple-touch-icon","href":"/favicon-48x48.png"}],["$","$L2e","16",{}]],"error":null,"digest":"$undefined"}
27:"$23:metadata"
2d:["$","$L8",null,{"parallelRouterKey":"children","error":"$undefined","errorStyles":"$undefined","errorScripts":"$undefined","template":["$","$La",null,{}],"templateStyles":"$undefined","templateScripts":"$undefined","notFound":"$undefined","forbidden":"$undefined","unauthorized":"$undefined"}]
30:I[68382,["6693","static/chunks/fba4ba2d-460e04194f22506f.js?dpl=dpl_CPYCfxesaX7RKfJUQZpH2JDib41x","3009","static/chunks/6a7d804d-a5cc510ceffe206f.js?dpl=dpl_CPYCfxesaX7RKfJUQZpH2JDib41x","7505","static/chunks/c02d83f4-5637599209ef9447.js?dpl=dpl_CPYCfxesaX7RKfJUQZpH2JDib41x","6541","static/chunks/fb4e7fc9-e31ad622f5fde25d.js?dpl=dpl_CPYCfxesaX7RKfJUQZpH2JDib41x","9761","static/chunks/998e86a0-e112630ec4db17dc.js?dpl=dpl_CPYCfxesaX7RKfJUQZpH2JDib41x","9509","static/chunks/9509-6125acd3006111c1.js?dpl=dpl_CPYCfxesaX7RKfJUQZpH2JDib41x","4378","static/chunks/4378-3f82908971052aa9.js?dpl=dpl_CPYCfxesaX7RKfJUQZpH2JDib41x","5289","static/chunks/5289-131715863bbab062.js?dpl=dpl_CPYCfxesaX7RKfJUQZpH2JDib41x","4094","static/chunks/4094-eaa6158623fe27ff.js?dpl=dpl_CPYCfxesaX7RKfJUQZpH2JDib41x","4982","static/chunks/4982-a4b2ee93ffd82ffd.js?dpl=dpl_CPYCfxesaX7RKfJUQZpH2JDib41x","1810","static/chunks/1810-cf4ca0391c1ddf2a.js?dpl=dpl_CPYCfxesaX7RKfJUQZpH2JDib41x","6118","static/chunks/6118-7328b7d3f629a5ef.js?dpl=dpl_CPYCfxesaX7RKfJUQZpH2JDib41x","7979","static/chunks/7979-1799576a8e82a4f3.js?dpl=dpl_CPYCfxesaX7RKfJUQZpH2JDib41x","393","static/chunks/393-7cd2157fc3790475.js?dpl=dpl_CPYCfxesaX7RKfJUQZpH2JDib41x","3985","static/chunks/3985-1f9bcb95de313d61.js?dpl=dpl_CPYCfxesaX7RKfJUQZpH2JDib41x","2610","static/chunks/2610-c41f461a4ed7cf24.js?dpl=dpl_CPYCfxesaX7RKfJUQZpH2JDib41x","4844","static/chunks/4844-011fe3465334e7d0.js?dpl=dpl_CPYCfxesaX7RKfJUQZpH2JDib41x","9305","static/chunks/9305-0f5d0f2a661afddc.js?dpl=dpl_CPYCfxesaX7RKfJUQZpH2JDib41x","713","static/chunks/713-dcb3ca4f0233704d.js?dpl=dpl_CPYCfxesaX7RKfJUQZpH2JDib41x","3504","static/chunks/3504-ae9bc2dc93d2ef47.js?dpl=dpl_CPYCfxesaX7RKfJUQZpH2JDib41x","1742","static/chunks/1742-0ea812562873537a.js?dpl=dpl_CPYCfxesaX7RKfJUQZpH2JDib41x","1172","static/chunks/1172-89020d82938322e4.js?dpl=dpl_CPYCfxesaX7RKfJUQZpH2JDib41x","9919","static/chunks/9919-b585857c6e10fb85.js?dpl=dpl_CPYCfxesaX7RKfJUQZpH2JDib41x","9326","static/chunks/9326-103822841b140d80.js?dpl=dpl_CPYCfxesaX7RKfJUQZpH2JDib41x","1885","static/chunks/1885-f206f5873f09b3e2.js?dpl=dpl_CPYCfxesaX7RKfJUQZpH2JDib41x","4077","static/chunks/4077-cba4e88bdb106467.js?dpl=dpl_CPYCfxesaX7RKfJUQZpH2JDib41x","5126","static/chunks/5126-bdde68ce894e4935.js?dpl=dpl_CPYCfxesaX7RKfJUQZpH2JDib41x","5642","static/chunks/5642-c80cb7ee6e914a6a.js?dpl=dpl_CPYCfxesaX7RKfJUQZpH2JDib41x","1924","static/chunks/1924-8c4ee98e9b0dbf83.js?dpl=dpl_CPYCfxesaX7RKfJUQZpH2JDib41x","6372","static/chunks/6372-3e2880fc7d769d1f.js?dpl=dpl_CPYCfxesaX7RKfJUQZpH2JDib41x","1289","static/chunks/1289-4fdf72847f7ef615.js?dpl=dpl_CPYCfxesaX7RKfJUQZpH2JDib41x","8382","static/chunks/8382-004a14550e3769cc.js?dpl=dpl_CPYCfxesaX7RKfJUQZpH2JDib41x","1951","static/chunks/app/models/%5Broute%5D/page-c5fd4df0a8a5cab4.js?dpl=dpl_CPYCfxesaX7RKfJUQZpH2JDib41x"],"default",1]
2f:T891,{"@context":"https://schema.org","@type":"FAQPage","@id":"https://www.segmind.com/models/z-image-turbo#faq","mainEntity":[{"@type":"Question","name":"Is Z-Image-Turbo open-source?","acceptedAnswer":{"@type":"Answer","text":"Z-Image-Turbo is part of the Z-Image family, which includes Z-Image-Base, designed specifically for community fine-tuning, offering robust support for open development and customization."}},{"@type":"Question","name":"How does it differ from other text-to-image models?","acceptedAnswer":{"@type":"Answer","text":"Z-Image-Turbo offers exceptional speed (sub-second generation), native bilingual text support (English and Chinese), and optimization for consumer GPUs. Therefore, Z-Image-Turbo distinguishes itself from most competing models that require more inference steps or enterprise-grade hardware for comparable quality."}},{"@type":"Question","name":"What parameters should I tweak for the best results?","acceptedAnswer":{"@type":"Answer","text":"Start with 10-20 steps and a guidance scale of 5; increase steps to 40-50 for final outputs. You can adjust the guidance scale higher (7-10) if the model isn't following your prompt closely, or lower the scale (3-5) for more creative interpretation."}},{"@type":"Question","name":"Can I generate images with Chinese text?","acceptedAnswer":{"@type":"Answer","text":"Yes, Z-Image-Turbo supports bilingual text rendering; you may specify Chinese characters directly in the prompt to accurately generate text elements in images."}},{"@type":"Question","name":"What resolution should I use for different applications?","acceptedAnswer":{"@type":"Answer","text":"Use '512Ã—512' for social media and web previews; '1024Ã—1024' for detailed digital content; and '2048Ã—2048' for print-quality materials. Furthermore, higher resolutions require more inference steps for the best quality."}},{"@type":"Question","name":"What image format should I choose?","acceptedAnswer":{"@type":"Answer","text":"Choose 'JPEG' for broad compatibility and smaller file sizes; go with 'PNG' for images that need transparency or lossless quality; and 'WebP' will render the best compression-to-quality ratio in modern web applications."}}]}31:T1320,# Z-Image-Turbo: Fast Text-to-Image Model with Bilingual Support

**Edited by Segmind Team on December 1, 2025.**

---

## What is Z-Image-Turbo?

**Z-Image-Turbo** is a high-speed text-to-image generation model from **Tongyi-MAI**; it is built on a 6â€‘billionâ€‘parameter single-stream diffusion transformer architecture. The model is a member of the Z-Image family, and this version delivers photorealistic results in under a second for rapid iterations. â€‹
**Z-Image-Turbo** is designed to run efficiently on consumer-grade GPUs, so developers and small teams can achieve professional-quality AI image generation without specialized hardware, setting it apart from many contemporary image models that require complex computational infrastructure or resources. It also provides native bilingual support for English and Chinese text in generated images, making it an invaluable asset for global applications and multilingual content workflows.


## Key Features of  Z-Image-Turbo

- **Sub-second generation speed** with as few as 10 inference steps for high-quality results 
- **Bilingual text rendering** that supports English and Chinese characters in generated images
- **6-billion parameter architecture** balancing model capability with resource efficiency
- **Consumer GPU compatibility** that enables local deployment without enterprise infrastructure
- **Advanced distillation techniques** and reinforcement learning optimization for enhanced output quality
- **Flexible resolution support** ranging from 256Ã—256 to 2048Ã—2048 pixels for desired image output quality
- **Multiple output formats**, including JPEG, PNG, and WebP, which offer flexibility with adjustable quality settings

## Best Use Cases

Z-Image-Turbo excels in rapid iteration and bilingual content generation, making it an asset for: 

- **Marketing teams** as they can quickly prototype visual concepts for campaigns targeting a global audience, especially the English and Chinese speakers. 
- **Game developers** benefit from fast asset generation during prototyping phases. 
- **E-commerce platforms** can design product mockups and lifestyle imagery at scale. 
- **Real-time applications** such as interactive design tools or chatbot-integrated image generation. 
- **Content creators** can produce multilingual social media content utilizing its accurate text rendering, eliminating the need for post-generation text overlays.

## Prompt Tips and Output Quality

- For optimal results, use descriptive prompts with clear subject, style, and composition details. 
- Utilise the **steps parameter**: 10 steps for quick previews and 40-50 steps for production-ready images. 
- Implement **guidance scale** to control prompt adherence: values around 5 provide creative freedom, and values of 8-10 enforce strict interpretation of the prompt.
- For images with text, specify the language and text placement clearly; for example - *"A Chinese restaurant sign saying 'ç¾Žé£Ÿå¤©å ‚' in glowing neon"*. 
- For consistent results across iterations, set a fixed **seed value**; use -1 for random variation. 
- Adjust the **height and width** in 64-pixel increments: 512Ã—512 for web use, while 1024Ã—1024 or higher suits print materials.

## FAQs

**Is Z-Image-Turbo open-source?**  
**Z-Image-Turbo** is part of the Z-Image family, which includes Z-Image-Base, designed specifically for community fine-tuning, offering robust support for open development and customization.

**How does it differ from other text-to-image models?**  
**Z-Image-Turbo** offers exceptional speed (sub-second generation), native bilingual text support (English and Chinese), and optimization for consumer GPUs. Therefore, Z-Image-Turbo distinguishes itself from most competing models that require more inference steps or enterprise-grade hardware for comparable quality.

**What parameters should I tweak for the best results?**  
Start with 10-20 steps and a guidance scale of 5; increase steps to 40-50 for final outputs. You can adjust the guidance scale higher (7-10) if the model isn't following your prompt closely, or lower the scale (3-5) for more creative interpretation.

**Can I generate images with Chinese text?**  
Yes, **Z-Image-Turbo** supports bilingual text rendering; you may specify Chinese characters directly in the prompt to accurately generate text elements in images.

**What resolution should I use for different applications?**  
Use '512Ã—512' for social media and web previews; '1024Ã—1024' for detailed digital content; and '2048Ã—2048' for print-quality materials. Furthermore, higher resolutions require more inference steps for the best quality.

**What image format should I choose?**  
Choose 'JPEG' for broad compatibility and smaller file sizes; go with 'PNG' for images that need transparency or lossless quality; and 'WebP' will render the best compression-to-quality ratio in modern web applications.32:T99a,# Z-Image-Turbo: Effective Usage Guide

Z-Image-Turbo is a 6B-parameter diffusion transformer optimized for sub-second bilingual text-to-image generation on consumer GPUs. Use this guide to craft precise prompts, choose the right parameters and achieve consistent, high-quality outputs.

## 1. Prompt Design
- Be descriptive: include subject, style, lighting and mood.  
- Specify text elements clearly: e.g., â€œA neon sign reading â€˜ç¾Žé£Ÿå¤©å ‚â€™ above a street food stall.â€  
- Combine language tags when mixing English and Chinese: e.g., â€œ[EN] Futuristic cityscape at sunset; [CN] æœªæ¥åŸŽå¸‚ æ—¥è½.â€  

## 2. Key Parameters

| Parameter         | Quick Preview       | Detailed Draft       | Production-Ready    |
|-------------------|---------------------|----------------------|---------------------|
| steps             | 10                  | 20â€“30                | 40â€“50               |
| guidance_scale    | 4â€“6                 | 6â€“8                  | 8â€“10                |
| seed              | â€“1 (random)         | Fixed (e.g., 42)     | Fixed (custom seed) |
| resolution (WÃ—H)  | 512Ã—512             | 768Ã—768 or 1024Ã—768  | 1024Ã—1024 or 2048Ã—2048 |
| image_format      | jpeg                | png or webp          | png (transparency)  |
| quality           | 60â€“80               | 80â€“90                | 90â€“100              |

## 3. Use Case Recommendations
- **Marketing Mockups**:  
  â€¢ steps=20, guidance_scale=7, 1024Ã—1024, png, quality=85.  
- **Social Media Posts**:  
  â€¢ steps=10, guidance_scale=5, 512Ã—512, webp, quality=70.  
- **Print-Quality Art**:  
  â€¢ steps=50, guidance_scale=9, 2048Ã—2048, png, quality=100.  
- **Real-Time Tools**:  
  â€¢ steps=8â€“12, guidance_scale=4â€“6, 512Ã—512, jpeg, quality=75.  

## 4. Best Practices
- Lock a **seed** for reproducibility; use `-1` for varied outputs.  
- Adjust **guidance_scale** to trade creativity vs. prompt adherence.  
- Increment resolutions in 64-pixel steps to match model training specs.  
- For bilingual text, place language notation at prompt start.  
- Use `webp` for modern web delivery; choose `png` when transparency or sharp text edges matter.  

Experiment with these settings to balance speed, fidelity, and creative freedom. With Z-Image-Turboâ€™s efficient architecture and bilingual support, you can iterate rapidly and deliver professional-grade visuals in under a second.1f:[["$","script",null,{"type":"application/ld+json","dangerouslySetInnerHTML":{"__html":"{\"@context\":\"https://schema.org\",\"@type\":\"SoftwareApplication\",\"@id\":\"https://www.segmind.com/models/z-image-turbo\",\"name\":\"Z Image Turbo\",\"description\":\"Z-Image-Turbo generates photorealistic images in under one second with bilingual text support for global applications.\",\"url\":\"https://www.segmind.com/models/z-image-turbo\",\"applicationCategory\":\"AI Model\",\"applicationSubCategory\":\"textToImage\",\"operatingSystem\":\"Any\",\"image\":\"https://segmind-resources.s3.amazonaws.com/output/z-image-turbo-9606.png\",\"offers\":{\"@type\":\"Offer\",\"availability\":\"https://schema.org/InStock\",\"priceCurrency\":\"USD\",\"price\":\"0.016715829198361613\"},\"provider\":{\"@type\":\"Organization\",\"@id\":\"https://www.segmind.com/#organization\",\"name\":\"Segmind\",\"url\":\"https://www.segmind.com\",\"logo\":\"https://www.segmind.com/favicon.svg\"}}"}}],["$","script",null,{"type":"application/ld+json","dangerouslySetInnerHTML":{"__html":"$2f"}}],null,["$","$L30",null,{"route":"z-image-turbo","modelDetails":{"title":"Z Image Turbo","thumbnail_image":"https://segmind-resources.s3.amazonaws.com/output/z-image-turbo-9606.png","type":"textToImage","model_type":"SS","is_depreciated":false,"meta_description":"Z-Image-Turbo generates photorealistic images in under one second with bilingual text support for global applications.","seo_description":"$31","guide":"$32","pricing_guide":null,"artifacts":"$1e:props:modelDetails:artifacts","default_image_output":"https://segmind-resources.s3.amazonaws.com/others/bdea434f-e787-470e-91c0-2911bf580c56-z-image-turbo-op.webp","default_response":null,"parameters":"$1e:props:modelDetails:parameters","endpoints":"$1e:props:modelDetails:endpoints","api_notes":"$1e:props:modelDetails:api_notes","model_outputs":null,"llm_capabilities":null,"license":"","github_link":null,"inference_provider":"SEGMIND_SERVERLESS","created_ts":"2025-11-27 17:57:58.087457+00:00","slug":"z-image-turbo","name":"Z Image Turbo","description":"Photorealistic images in under one second, bilingual text.","category":"textToImage","modality":"image","input":"text","output":"image","provider":"ALIBABA","thumbnail_url":"https://segmind-resources.s3.amazonaws.com/output/z-image-turbo-9606.png","is_new":false,"coming_soon":false,"popularity_score":62,"category_percentile":85,"average_cost":0.016715829198361613,"latency_seconds":4.27188,"created_at":"2025-11-27 17:57:58.087457+00:00","parameters_schema":"$1e:props:modelDetails:parameters_schema"},"relatedTemplates":[],"popularModels":[{"slug":"qwen-image-2.1-turbo","title":"Qwen Image 2.1 Turbo","description":"Generate transparent PNGs; edit with up to 10 references.","type":"textToImage","partner":"ALIBABA","thumbnail_image":"https://segmind-resources.s3.amazonaws.com/output/qwen-image-2.1-turbo-6579.webp","default_image_output":"","is_new":true,"coming_soon":false,"is_visible":true,"segmind":true,"is_depreciated":false,"parameters":null,"latency":9.13358,"average_cost":0.016,"created_at":"2026-10-12 09:58:20.421947+00:00","popularity_score":41,"popularity_scale":"score","category_percentile":54},{"slug":"qwen-image-2.1-pro","title":"Qwen Image 2.1 Pro","description":"Generate transparent PNGs and edit with 10 reference images.","type":"textToImage","partner":"ALIBABA","thumbnail_image":"https://segmind-resources.s3.amazonaws.com/output/qwen-image-2.1-pro-1009.webp","default_image_output":"","is_new":true,"coming_soon":false,"is_visible":true,"segmind":true,"is_depreciated":false,"parameters":null,"latency":16.31398,"average_cost":0.05,"created_at":"2026-10-06 13:16:26.683335+00:00","popularity_score":44,"popularity_scale":"score","category_percentile":60},{"slug":"qwen-image-3","title":"Qwen Image 3.0","description":"Generate and edit legible in-image text, up to 2K.","type":"textToImage","partner":"ALIBABA","thumbnail_image":"https://segmind-resources.s3.amazonaws.com/output/qwen-image-3-7892.webp","default_image_output":"","is_new":false,"coming_soon":false,"is_visible":true,"segmind":true,"is_depreciated":false,"parameters":null,"latency":92.91656,"average_cost":0.049,"created_at":"2026-08-13 02:24:22.521553+00:00","popularity_score":56,"popularity_scale":"score","category_percentile":77},{"slug":"wan2.7-image","title":"Wan 2.7 Image Generation","description":"2K image generation with precise multilingual text rendering.","type":"textToImage","partner":"ALIBABA","thumbnail_image":"https://segmind-resources.s3.amazonaws.com/output/wan2.7-image-5506.webp","default_image_output":"","is_new":false,"coming_soon":false,"is_visible":true,"segmind":true,"is_depreciated":false,"parameters":null,"latency":21.70906,"average_cost":0.0429,"created_at":"2026-04-03 13:12:11.201178+00:00","popularity_score":56,"popularity_scale":"score","category_percentile":78}]}]]
