Image Generation Settings
Search for our available models here to learn more about them.
Please use our default settings for optimal results if you're a beginner.
Image generation engines can often generate disproportionate body parts, extra limbs or fingers, strange textures etc. Use negative prompting to avoid disfiguration or for creative outputs like avoiding certain colour schemes, elements or styles.
By default, each run produces one output per Model.
An increase in output quality is comparable to a gradual progression in any drawing process that begins with a draft version and ends with a finished product.
At lower values the image will effectively be random. The standard value is between 6-8. Values that are too high can also distort the image.
Object Repositioning Settings
How big should the object look?
Where would you like to place the object in the scene?
![](data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAIAAAACACAIAAABMXPacAAAYVklEQVR4Ae3Be4yU1dkA8Oe8t7nP7GVmYVkuW9F639rUNI+pNobGWOMftGnVmNZYk1MTaytCVRBqxFaqAi5CoRZ6YlLTaCmhsRpjtaI1Ij4JUlOwCIhsWZbdnZ3duc+87zvv5XzJJCQ2/aDbr7ucf77fj4FSnHMhBKhDRIgI6jBQinMuhAB1iAgRQR0GSnHOhRCgDhEhIqjDQCnOuRAC1CEiRAR1GCjFORdCgDpEhIigDgOlOOdCCFCHiBAR1GGgFOdcCAHqEBEigjoMlOKcCyFAHSJCRFCHgVKccyEEqENEiAjqMFCKcy6EAHWICBFBHQZKcc6FEKAOESEiqMNAKc65EALUISJEBHUYKMU5F0KAOkSEiKAOA6U450IIUIeIEBHUYaAU51wIAeoQESKCOgyU4pwLIUAdIkJEUIeBUpxzIQSoQ0SICOowUIpzLoQAdYgIEUEdBkpxzoUQoA4RISKow0ApzrkQAtQhIkQEdRgoxTkXQoA6RISIoA4DpTjnQghQh4gQEdRhoBTnXAgB6hARIoI6DJTinAshQB0iQkRQh4FSnHMhBKhDRIgI6jBQinMuhAB1iAgRQR0GSnHOhRCgDhEhIqjDQCnOuRAC1CEiRAR1GCjFORdCgDpEhIigDgOlOOdCCFCHiBAR1GGgFOdcCAHqEBEigjoMlOKcCyFAHSJCRFCHgVKccyEEfMbU1FQulwvDEM4LIkJEUIeBUpxzIQScYRjGL3/5y7179z7//PNwXhARIoI6DJTinAsh4IxUKjU6Ovqzn/1s/fr1cF4QESKCOgyU4pwLIaBtyZIlO3bscBzHNM1isXjNNdfA7CMiRAR1GMyCVCo1NDSUzWbh3+GcCyHgjMcff9z3fdM0BwcHp6amYPYRESKCOgxmwQcffDA1NXXjjTfCv8M5F0LAGXfccceyZcsMw7jqqqvgvCAiRAR1GMyCp59+eunSpd/85jcPHToE58Q5F0LAGUEQQNuKFSs2b94Ms4+IEBHUYTALEonE888/H4lEFi5cmMvlrrvuuuPHj8O/WLNmza233ur7vpTS87xarRaPx4MgsG07Fosxxnzfj0QisVjs/fffX7Fiheu6MNOICBFBHQYzbWBg4Gtf+9rtt98eBEGz2QzD8IMPPvjRj36UTCbhjE8//dTzvEqlout6KpVyHMf3/TAMpZRaG2MsDEMpZastFou5riulvO2228bHx2HmEBEigjoMZto777xz7NixU6dO2bbtOM7ixYsXLlyYTCallDfeeCMAbNy4sa+vT0qZbms2m5qmmabJ2nzf9zyPMQYAhmFIKVutluM4nudVKpVCobBmzRqYOUSEiKAO45zDzLnvvvvGxsaGh4fHxsaq1arnealUKpvNXnnllfV63XXdN954AwC+8pWvAICUcs6cOadPn5ZSMsagTdM0Xdc1TWNtYRhKKYMg0DTN9/2PPvqo0WjAv3PnnXemUqmtW7fCv8M5F0KAOgxmzuWXX/7AAw/s37+fiD755BP4jCVLltx2220jIyM7duw4fvw4ACxdutRxnOuvv37Pnj0AwNo0TQMAXdcBgDEWthmGEYYhY8y27bfeegvOiTH2xhtvNBqNSqXy6aefHjt2rFQqVSqV/v7+3/3ud/AviAgRQR0GM+f1118/fPjwO++8s2fPHgBgjEkp4Yx77723v7//wIEDv/71rwFg9erVnucNDAzs27dP1/VYLKbrengGYwwAGGORSAQAWq2WbdvPPfdcs9mEc3rllVeKxeLJkydPnz793nvvffTRR3BORISIoA6DmfPss8/m8/k333zz4MGDUkr4Z5qmPfTQQ2NjY1u3bgWAdevWWZY1b968EydO2Lat63o0Gg3DMGgDAKMtk8mUy2UpZaFQ2LJlC5zTD37wg5tvvvnQoUNDQ0Pbt2+HaSAiRAR1GMycLVu2jI6O7t69e3x8HP5ZLBZrNBqPPvro4cOHX3755WKx+PWvf/2LX/ziJZdcMjo62mw2GWORSETTtDAMfd/XNE3X9Wg0GgRBvV4vlUqtVutXv/oVnNOzzz4bj8eHh4efeOKJZrMJ00BEiAjqMJg5mzZtKpVKu3btGhkZgc+QUu7atSsajb733ntXXnllPp+/++67I5HIww8/fMUVVxw6dMj3/SAIIm1BEHiep+u6pmmxWKxUKlmWZdv2xMTEc889B2eXTqefeOIJXdfr9foDDzwA00NEiAjqMJg5mzdvdhznL3/5y969e+GfhWHY399fqVR27NhRr9cffvjh3W39/f3Hjh1LJpOVSsUwjHg8LqVstVp6WyQSqdVqkUikUCgcOHBg3759cHb33HPP5Zdfruv6W2+9tWvXLpgeIkJEUIfBzNm6dWtnZ+fevXt/+9vfwlls2LDh8ssvZ4z5vv/BBx/MmTPn448/TqfTlUolCIJEIgEAruvqup5IJDRNq9VqnucFQbB58+ZWqwVnt2bNmlwul0wmH3rooWKxCNNDRIgI6jCYOYsWLfrJT37yj3/8Y/PmzYwx+N+EYbhu3bpcLtfR0XHgwIGrrrrq+PHjzWbT933HceLxuKZptm0bhpHJZFzXtSyr3rZhwwY4p7Vr1/b09MTj8e9973swbUSEiKAOgxm1bdu2Wq329ttv79u3D/6FlJIxJqV85JFHPve5z/3973///Oc/XywWXdeNRCLVatU0TcMwHMexLKu7u7ter5umOTk5OT4+vnXrVjin1atXz507t7Oz84477oBpIyJEBHUYzKiVK1fOnz//9OnT27Ztg7MzDOOxxx6r1Wq9vb3FYtH3/VQq5bqu1ea6rq7r6XR6bGzMNM1KpTI1NbVlyxY4p1WrVvX29maz2e985zswbUSEiKAOg5m2Y8eOZrP5+9///tChQ3CGlJIxBgBSSmhbvXp1GIYXXnjh8PBws9ns6OiwbduyrFgs1mw2DcPIZDKjo6OxWKxer1cqlaeffhrOaeXKlX19fT09PcuXLx8bG4PpISJEBHUYzLQ1a9b09/efPHly8+bNACClZIxBm5SSMQYAUsowDO+///6rr776008/bbVaiUSiVquZpplIJGq1mmVZXV1dhULBsqxGo1GpVDZs2ADn9OCDDy5atCidTr/wwgt/+tOfYHqICBFBHQazYHBwkDH20ksv/fWvfwUAKSX8bx588MGBgYGhoaFWqxWPx23bNk0zkUjU63XDMNLp9MTERCwWq9fr5XJ5/fr1cE4PPPBAX19fNps9derU6tWrYXqICBFBHQaz4LbbbrvmmmsmJyefeeYZOLtHH330wgsvHB4edl03lUrZtm1ZViqVqtfrjLFMJjM2NpZIJKrVaqFQ2LhxI5zTj3/84/nz58+ZMyeTydx8880wPUSEiKAOg9nx85//3DCM1157bf/+/XAWmzZtSqVS5XK52Wxms1nP8wzDSCQSjUaDMZZKpUZGRuLxeKlUKhQKTz31FJzTihUrent7u7q6stns0qVLYXqICBFBHQaz47LLLrvrrrtKpdKWLVvgLH7xi18kEgnXdW3b7ujoaLVauq7H43HbtgEgkUiUSiVN0/L5fKlUevrpp23bhrNbtmzZokWLIpFIf3//zTffDNNDRIgI6jCYNY899lg8Ht++ffv4+DicIaVkjEHbpk2bLrzwwnw+r2maaZrlclnX9UQiYdu2lDKVSmmaVq1Wx8fHG43G4cOHd+7cCWe3bNmyhQsX5nK5eDx+6623hmEI00BEiAjqMJg1ixcvvueee8rl8jPPPAMAUkoAYIxJKQHANM3169f39PT4vm9Zlu/7lUrFNM1YLGbbtpQy2ZbP533fLxQK5XJ53bp1cHYrVqzoaevu7l65cuWRI0dgGogIEUEdBrNpw4YNpmmuXLnSMAz4Z9u3b49Go6Zpep7X3d19+vRpx3GSyaRlWW5bJBLp7u5utVqVSmViYqJara5du1ZKCWexZs2azs7OZDKZzWaPHz++atUqmAYiQkRQh8FsuuWWW7761a++/fbbr7/+OvyzP/zhD2NjY/39/VJK27ZLpZLruqlUyrKsVqvluq5hGOl0OpVKnThxQko5OTl5+vTpTZs2wVmsXbt27ty5Usru7u5UKnXTTTfBNBARIoI6DGbZ+vXrJycnt23bBp/x5JNPXnTRRb7va5rW1dU1NjZWr9fj8bhlWZqmhWHoOI7nedFotLu723XdY8eOBUEwNTX105/+FM7iySefnDt3LgDEYjFN02655RaYBiJCRFCHwSzbsGFDGIZr167VNE1KyRgLguDFF1+Mx+PNZnPhwoUTExO2bRuGEYvFwjCUUjLGWq2W67qMsXg8rut6tVodHx/3fX94eHhwcBD+xb333nvRRRdFIpF0Om2aZhAEt99+O0wDESEiqMNglt13333z589/8sknHcdhjEkpX3311UQiMTEx4XleR0dHJBJpNptBEEQiEQDwPM+yLNd1DcPwPM8wDNd1JyYmUqnUxMTEiRMndu7cOTw8DJ9xwQUXLFu2bP78+c1mMwiCTCbTaDS++93vwjQQESKCOgxmWSQSWbdu3Ysvvvjxxx8DQF9f3+DgYF9f35EjR5LJZG9vr+/7tVqt1WoxxqLRaBiG0Wg0CIIwDHVdTyaTADA+Pp7P5w3DOHXqVKFQeOaZZ+CMH/7whxdccEE6nfY8L5fLOY5jGEatVvv+978P00BEiAjqMJh9mzZt2rt372uvvQYAr7/+erPZrNfrc+bMqdVq8Xi8Xq83Gg3GmKZp0WjUMIxoNBoEQaPRaLVahmF0dnbW63UpZaPRqNVqp06d6u3tHRoa0jQtFotFo9ErrrjCcZxKpZLNZpvNpmVZQ0NDy5cvh2kgIkQEdRjMvsHBwQ8//HD37t0rVqz48pe/PG/evKGhIU3TEm2Tk5NhGGqaJqUEgEQiYRiG4zitVgvaYrGYZVljY2O+72cymZMnT37pS186dOhQIpHQdb2npycajdq2rWkaABw5cqSnp+f48eOrV6+GaSAiRAR1GMy+jRs3vvvuu3feeWcYhrE2TdMAIJVKNZvNRqNRr9d1XWeMBUGQTCY1TavVapqmAYDneV1dXfF4vNVqNRoN27ZPnTr1rW9967333stkMqOjoxdffHG1Wi2Xy47jzJkzp1gsTk1NDQ0Nbd68GaaBiBAR1GEw+wYHB2+44YYwDMvlsuM4mqaVy+UwDOfNm9dqtQAgDMNKpaJpGgAkEgkAsG0bAHzfz2QymqaZplkul6vVKmMsl8tdeumlBw4c6OzsrNVqAFAsFh3H8TzP933XdWu12uOPPy6lhGkgIkQEdRjMvqeeeur6668fHx83DKNerwNAEATpdDoWi0kpi8ViT09PtVpttVphGMZiMQDwPA8ALMuKxWKlUimTyUgpJycnPc/r6upavHjx8ePHDcOoVCqRSKRSqbRarWq16nmepmmjo6NbtmyB6SEiRAR1GMy+xx577Nprr83n847jXHbZZfV6HQCi0aht20EQVKtVAOjs7KxUKgAQiUR83w/burq6pqamACCRSMTjcdd1GWOdnZ0HDx5cuHCh4zhjY2O5XK5cLruuG4/Hh4eHT548KYSAaSMiRAR1GMy+G264YdWqVYcPH543b14ikZiYmNA0rbe317KsRqNRqVQAIJPJlMtlXdcjkYjneb7vB0GQy+XK5XIYhvF4PJvNDg0NhWGYTCZffvnl5cuXv/POOz09PZ988onruslksl6vNxqNnTt3joyMwLQRESKCOgzOi+XLl1977bXFYnHBggX5fF7TtO7u7larZRhGrVaTUqbT6Xq9rmmaaZq+7wNAEASmaQZt8+bN830/n8/7vp9Op/P5/HXXXffnP//Zdd1ms6lpWrPZrFar+9vgP0FEiAjqMDgv7r///i984QtSyoULFxYKhWq1umDBgkql0t/ff/ToUV3XNU0LgiASiZim6ft+EASmabquq7VFo1HLsgqFguu62Wy2XC5ns9mRkZF8Pl+tVsMwbDQa77777pEjR+A/RESICOowOC/uu+++K6+80jTNnp6eWq3m+34sFms0Gl1dXVNTU77vM8Z0XTfagiCQUiaTyXK5rGlaOp2uVCqdnZ2Tk5OJRELX9Uaj8be//W3RokUnTpwoFou1Wm3fvn3j4+PwnyMiRAR1GJwXS5cu/cY3vuG6biQSCcMwHo/rul4qlXK5XLPZtG3b87x4PK7rummafltHR0epVGKMpVKpSqWSSqVs29Y0rdlstlqtcrk8MDCwc+dO13Vfeukl3/fh/4SIEBHUYXBe6Lo+ODgIAFJKTdMymQxjrFgsLliwoNFoVCoV0zRjsZiU0jTNIAjCMMxkMvl8XtO0ZDJZKpXS6bRhGOVyudFoRCKRarUaiUTef//93bt3w3+BiBAR1GFwvmzcuFFK6TiOZVm5XK7RaDiOs2jRonK5XKvVotFoIpEIgsAwjLAtkUgUCgUAiMfjjUYjDMPe3t7R0VHbtpPJZKFQ+OMf/3jw4EH47xARIoI6DM6XVatWJZNJ3/cZY9lstlqtBkGwePHiycnJMAyNNt/3GWMAoGlaOp2uVCqO4xiG4TiO7/vd3d3VarXRaMRisZGRkWeffdbzPPjvEBEigjoMzqO777577ty5uq53dHQUCgUAuPjii4vFYhiGABCGoeu6rM00zUwm43mebdtSStu2gyBIpVKtVsu2bSnl1NTUtm3b4L9GRIgI6jA4j2699dZcLmdZVkdHR7FY1HV9YGBgamqqVqt5nqfruu/7uq5LKXVdT6VSvu8bhsEYm5ycBABd1w3DKBaL+Xx+586dMBOICBFBHQbn1x133OG6bi6XcxzHMIyrr756eHjYtm3XdbU2wzCCIACATCbjum40GtV1fWJiIgiCSCQyOTmp6/qePXtOnjwJM4GIEBHUYXDeffvb3w7DMBaLSSmXLFny4Ycf+r4fhmEQBLqum6YZBIGmaalUyrbtSCQShmGz2XQcJwgCz/M+/PDDo0ePwgwhIkQEdRgRwf9Th4Ei1157bTQaXbJkyZ49e3Rdj8fjUkpd103TDIJASul5nq7rjUbDsqx6vR6Lxfbv3z85OQkziogQEdRhoMLAwMCjjz766quvXnLJJS+//DJjTNM0AAjD0DRN3/c1TdN1XUoZhiFjLJlM9vf3Z7PZXbt2ffTRRzBziAgRQR0GKvzmN7+JxWLFYjEWi7322mvNZrPVagFAEAQAEIah1haNRnVd7+7uXrBggaZpYRiWy+XBwUGYOUSEiKAOg/NuYGBgzZo16XSaMVav1w8ePBiGYT6fdxxHSmkYBmPMMAyrraenJ5FIZLPZarUahmGhUBgcHKxUKjBDiAgRQR0G5x0iPvLII8lk8uTJk/39/YcOHert7T169KhpmgDAGItGo5ZlNZtNwzC6u7tTqVS1Wu3s7Dxy5Iiu6ytXrmw2mzBDiAgRQR0G5x1jjIgmJiaazWZXV1cQBL7v5/P5VCrlOI5hGNFo1DAMTdMmJiZ6e3t939d1vdFolMvl+fPn33TTTTBziAgRQR0GKuzcufPSSy8dGRkxTbNWq8ViMdu2o9Go7/t6WyKRsCyrUChommbbtu/7hmF0dnZu2rTplVdegZlDRIgI6jBQRAjR19c3b948TdM8z6tUKslk0vd9z/PCMDRNs1arSSlt204mkx0dHUePHt2+ffvevXthRhERIoI6DNRJJpMvvPDC5ORkNpvt6+uzLAsApJSO42iaFolEWq3W8PBwrVY7evTounXrYBYQESKCOgyU4pwLIXp6eu6666758+frug4AQRBYluV53ptvvvnKK68EQQCzhogQEdRhoBTnXAgB6hARIoI6DJTinAshQB0iQkRQh4FSnHMhBKhDRIgI6jBQinMuhAB1iAgRQR0GSnHOhRCgDhEhIqjDQCnOuRAC1CEiRAR1GCjFORdCgDpEhIigDgOlOOdCCFCHiBAR1GGgFOdcCAHqEBEigjoMlOKcCyFAHSJCRFCHgVKccyEEqENEiAjqMFCKcy6EAHWICBFBHQZKcc6FEKAOESEiqMNAKc65EALUISJEBHUYKMU5F0KAOkSEiKAOA6U450IIUIeIEBHUYaAU51wIAeoQESKCOgyU4pwLIUAdIkJEUIeBUpxzIQSoQ0SICOowUIpzLoQAdYgIEUEdBkpxzoUQoA4RISKow0ApzrkQAtQhIkQEdRgoxTkXQoA6RISIoA4DpTjnQghQh4gQEdRhoBTnXAgB6hARIoI6DJTinAshQB0iQkRQh4FSnHMhBKhDRIgI6jBQinMuhAB1iAgRQR0GSnHOhRCgDhEhIqjDQCnOuRAC1CEiRAR1GCjFORdCgDpEhIigDgOlOOdCCFCHiBAR1PkfBxiFuXBNku8AAAAASUVORK5CYII=)