{
  "aboutHtml": "<h4>Fast exploration within the Krea 2 family</h4><p>Krea 2 Medium Turbo is the generation edition Krea presents as Krea 2 Turbo. Its model-specific interface identifies the Medium Turbo variant, and Krea’s user guide describes a distilled sampling schedule that reduces the work needed to generate an image. Krea positions it as the family’s fastest option for broad creative exploration, expressive rough drafts, illustration and graphic directions.</p><p>Use it when the immediate goal is to compare ideas: alternative compositions for a cover, visual treatments for a campaign or different illustration styles for the same scene. A concise, concrete starting brief makes comparisons easier. For example: “A folded red paper bird above a pale-blue desk, bold editorial illustration, hard afternoon shadow, simple geometric shapes, vertical composition with clear space at the bottom.” Keep the subject and frame steady while exploring the visual treatment, then develop the selected direction further.</p><p>Krea’s edition guidance favors Medium when a more stable illustration treatment is needed and Large for a photographic or raw-textured final direction. Turbo remains its own edition; a later pass in another model is a separate generation rather than an automatic quality upgrade or an identical continuation.</p><h4>Prepare the prompt and visual inputs</h4><p>The model’s generation schema requires a prompt, aspect ratio and resolution. Optional image-to-image input starts generation from a source image rather than pure noise. Its denoising strength runs from 0 to 1: 0 keeps the input, 1 fully replaces it, and the documented default is 0.99. Prepare the starting composition carefully and describe what should change; a high strength allows substantial replacement of the source.</p><p>Style references supply appearance through images rather than changing the starting-image strength. The model-specific schema limits source-image and style-reference URI strings to 1,024 characters. The model-specific request schema accepts up to ten references, each with influence from 0 to 1 and a default of 0.5. Select references with clear roles, such as a color palette, drawing treatment or lighting direction. The separate Krea workspace guide describes up to four style references in that interface; the two interfaces should be prepared with their respective limits.</p><p>Moodboards organize a coherent visual direction into a reusable input. Create the moodboard first and use its existing identifier when generating. The model schema accepts one moodboard, with influence from 0 to 1 and a default of 0.23. Trained styles, typically LoRAs, are another input selected by identifier and strength from -2 to 2. A source image, a style reference, a moodboard and a trained style have different roles, so avoid treating them as interchangeable ways to preserve every detail.</p><h4>Adjust creativity and the three visual sliders</h4><p>Creativity controls prompt expansion. Raw disables it; low, medium and high change how much interpretation is added to the brief. The model-specific schema defaults to low. Use a restrained setting to compare a precise brief, or increase interpretation when the purpose is to discover a broader range of ideas.</p><p>Intensity, Complexity and Movement are independent integer sliders from -100 to 100, with 0 neutral. Intensity moves between muted and bold treatment. Complexity moves between simpler compositions and denser detail. Movement changes pose, visual energy and implied motion. These sliders can be combined with references and moodboards, and they are separate from creativity’s prompt expansion.</p><p>For the paper-bird brief, first compare a clean composition with a more detailed one while holding the other settings steady. Then explore a stronger visual treatment or a more energetic pose. Change one control at a time and keep the optional seed, prompt and reference set recorded. Movement affects a still image’s character; it does not produce an animated bird, camera move or video sequence.</p><h4>Frames, batches and completed images</h4><p>The model-specific generation schema offers a 1K resolution scale and nine aspect ratios: 1:1, 4:3, 3:2, 16:9, 2.35:1, 4:5, 3:4, 2:3 and 9:16. Krea’s Turbo workspace guide also describes generating up to four images in a batch. That batch setting belongs to the documented workspace workflow; it is distinct from the individual generation request schema.</p><p>Select the frame for the intended asset before generation. A vertical cover needs a different balance of subject and open space from a wide editorial image. Keep the generation scale separate from any subsequent enhancement or finished-layout export.</p><p>Krea’s documented generation flow returns a job that may initially be pending. Follow the job to completion and retrieve its resulting image locations. Compare the actual finished candidates for composition, shape, texture, palette and visible text, then preserve the selected image with its inputs and settings. If the asset needs precise lettering, place or correct that lettering in the finished design.</p><p>Turbo’s fast-exploration role does not guarantee a particular completion time, perfect lettering or an exact reconstruction of a reference image. Source-image strength and reference influence still require inspection of the result. Use the edition to resolve visual direction efficiently, select a concrete candidate, and make any final detail, layout or production corrections required by the intended use.</p>",
  "aboutText": "### Fast exploration within the Krea 2 family\n\nKrea 2 Medium Turbo is the generation edition Krea presents as Krea 2 Turbo. Its model-specific interface identifies the Medium Turbo variant, and Krea’s user guide describes a distilled sampling schedule that reduces the work needed to generate an image. Krea positions it as the family’s fastest option for broad creative exploration, expressive rough drafts, illustration and graphic directions.\n\nUse it when the immediate goal is to compare ideas: alternative compositions for a cover, visual treatments for a campaign or different illustration styles for the same scene. A concise, concrete starting brief makes comparisons easier. For example: “A folded red paper bird above a pale-blue desk, bold editorial illustration, hard afternoon shadow, simple geometric shapes, vertical composition with clear space at the bottom.” Keep the subject and frame steady while exploring the visual treatment, then develop the selected direction further.\n\nKrea’s edition guidance favors Medium when a more stable illustration treatment is needed and Large for a photographic or raw-textured final direction. Turbo remains its own edition; a later pass in another model is a separate generation rather than an automatic quality upgrade or an identical continuation.\n\n### Prepare the prompt and visual inputs\n\nThe model’s generation schema requires a prompt, aspect ratio and resolution. Optional image-to-image input starts generation from a source image rather than pure noise. Its denoising strength runs from 0 to 1: 0 keeps the input, 1 fully replaces it, and the documented default is 0.99. Prepare the starting composition carefully and describe what should change; a high strength allows substantial replacement of the source.\n\nStyle references supply appearance through images rather than changing the starting-image strength. The model-specific schema limits source-image and style-reference URI strings to 1,024 characters. The model-specific request schema accepts up to ten references, each with influence from 0 to 1 and a default of 0.5. Select references with clear roles, such as a color palette, drawing treatment or lighting direction. The separate Krea workspace guide describes up to four style references in that interface; the two interfaces should be prepared with their respective limits.\n\nMoodboards organize a coherent visual direction into a reusable input. Create the moodboard first and use its existing identifier when generating. The model schema accepts one moodboard, with influence from 0 to 1 and a default of 0.23. Trained styles, typically LoRAs, are another input selected by identifier and strength from -2 to 2. A source image, a style reference, a moodboard and a trained style have different roles, so avoid treating them as interchangeable ways to preserve every detail.\n\n### Adjust creativity and the three visual sliders\n\nCreativity controls prompt expansion. Raw disables it; low, medium and high change how much interpretation is added to the brief. The model-specific schema defaults to low. Use a restrained setting to compare a precise brief, or increase interpretation when the purpose is to discover a broader range of ideas.\n\nIntensity, Complexity and Movement are independent integer sliders from -100 to 100, with 0 neutral. Intensity moves between muted and bold treatment. Complexity moves between simpler compositions and denser detail. Movement changes pose, visual energy and implied motion. These sliders can be combined with references and moodboards, and they are separate from creativity’s prompt expansion.\n\nFor the paper-bird brief, first compare a clean composition with a more detailed one while holding the other settings steady. Then explore a stronger visual treatment or a more energetic pose. Change one control at a time and keep the optional seed, prompt and reference set recorded. Movement affects a still image’s character; it does not produce an animated bird, camera move or video sequence.\n\n### Frames, batches and completed images\n\nThe model-specific generation schema offers a 1K resolution scale and nine aspect ratios: 1:1, 4:3, 3:2, 16:9, 2.35:1, 4:5, 3:4, 2:3 and 9:16. Krea’s Turbo workspace guide also describes generating up to four images in a batch. That batch setting belongs to the documented workspace workflow; it is distinct from the individual generation request schema.\n\nSelect the frame for the intended asset before generation. A vertical cover needs a different balance of subject and open space from a wide editorial image. Keep the generation scale separate from any subsequent enhancement or finished-layout export.\n\nKrea’s documented generation flow returns a job that may initially be pending. Follow the job to completion and retrieve its resulting image locations. Compare the actual finished candidates for composition, shape, texture, palette and visible text, then preserve the selected image with its inputs and settings. If the asset needs precise lettering, place or correct that lettering in the finished design.\n\nTurbo’s fast-exploration role does not guarantee a particular completion time, perfect lettering or an exact reconstruction of a reference image. Source-image strength and reference influence still require inspection of the result. Use the edition to resolve visual direction efficiently, select a concrete candidate, and make any final detail, layout or production corrections required by the intended use.",
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      "html": "<div class=\"sheet-head\"><span class=\"mav\" aria-hidden=\"true\">•</span><h2 id=\"sheet-title\">Krea: Krea 2 Medium Turbo</h2><button class=\"icon-btn\" type=\"button\" data-close-sheet aria-label=\"Close\">×</button></div><div class=\"idline\"><span>Krea /</span><code>krea/krea-2-medium-turbo</code><button type=\"button\" id=\"copy-id\">Copy ID</button></div><nav class=\"card-jump-nav\" aria-label=\"Model card sections\"><button type=\"button\" data-card-jump=\"overview\">Overview</button><button type=\"button\" data-card-jump=\"methods\">Inputs &amp; methods</button><button type=\"button\" data-card-jump=\"pricing\">Pricing</button><button type=\"button\" data-card-jump=\"examples\">Examples</button><button type=\"button\" data-card-jump=\"results\">Results</button><button type=\"button\" data-card-jump=\"aliases\">Aliases</button></nav><div class=\"card-method-tabs\" role=\"tablist\" aria-label=\"API methods\"><button type=\"button\" role=\"tab\" tabindex=\"0\" aria-controls=\"card-method-content\" aria-selected=\"true\" id=\"card-method-tab-0\" data-card-method=\"Ultra|images|/v1/images/generations|krea%2Fkrea-2-medium-turbo\">Images</button></div><div id=\"card-method-content\" role=\"tabpanel\" aria-labelledby=\"card-method-tab-0\"><section class=\"card-section\" data-card-section=\"overview\"><h3 tabindex=\"-1\">Overview</h3><p class=\"mdesc-full\">Krea 2 Medium Turbo is Krea’s fast image-generation edition for exploring visual ideas and producing expressive drafts. It combines a distilled sampling schedule with text, source-image and style controls, including independent adjustments for intensity, complexity and implied motion.</p><dl class=\"card-io\" data-card-io><div><dt>Accepted inputs</dt><dd>Text · Images</dd></div><div><dt>Results</dt><dd>Images</dd></div></dl><details class=\"card-about\"><summary>About the model</summary><p class=\"note-s\" data-model-method-boundary>This description covers the model’s capabilities. Available in Ailoot inputs, outputs and options are listed for the selected method below.</p><div class=\"mabout\" id=\"m-about\"><h4>Fast exploration within the Krea 2 family</h4><p>Krea 2 Medium Turbo is the generation edition Krea presents as Krea 2 Turbo. Its model-specific interface identifies the Medium Turbo variant, and Krea’s user guide describes a distilled sampling schedule that reduces the work needed to generate an image. Krea positions it as the family’s fastest option for broad creative exploration, expressive rough drafts, illustration and graphic directions.</p><p>Use it when the immediate goal is to compare ideas: alternative compositions for a cover, visual treatments for a campaign or different illustration styles for the same scene. A concise, concrete starting brief makes comparisons easier. For example: “A folded red paper bird above a pale-blue desk, bold editorial illustration, hard afternoon shadow, simple geometric shapes, vertical composition with clear space at the bottom.” Keep the subject and frame steady while exploring the visual treatment, then develop the selected direction further.</p><p>Krea’s edition guidance favors Medium when a more stable illustration treatment is needed and Large for a photographic or raw-textured final direction. Turbo remains its own edition; a later pass in another model is a separate generation rather than an automatic quality upgrade or an identical continuation.</p><h4>Prepare the prompt and visual inputs</h4><p>The model’s generation schema requires a prompt, aspect ratio and resolution. Optional image-to-image input starts generation from a source image rather than pure noise. Its denoising strength runs from 0 to 1: 0 keeps the input, 1 fully replaces it, and the documented default is 0.99. Prepare the starting composition carefully and describe what should change; a high strength allows substantial replacement of the source.</p><p>Style references supply appearance through images rather than changing the starting-image strength. The model-specific schema limits source-image and style-reference URI strings to 1,024 characters. The model-specific request schema accepts up to ten references, each with influence from 0 to 1 and a default of 0.5. Select references with clear roles, such as a color palette, drawing treatment or lighting direction. The separate Krea workspace guide describes up to four style references in that interface; the two interfaces should be prepared with their respective limits.</p><p>Moodboards organize a coherent visual direction into a reusable input. Create the moodboard first and use its existing identifier when generating. The model schema accepts one moodboard, with influence from 0 to 1 and a default of 0.23. Trained styles, typically LoRAs, are another input selected by identifier and strength from -2 to 2. A source image, a style reference, a moodboard and a trained style have different roles, so avoid treating them as interchangeable ways to preserve every detail.</p><h4>Adjust creativity and the three visual sliders</h4><p>Creativity controls prompt expansion. Raw disables it; low, medium and high change how much interpretation is added to the brief. The model-specific schema defaults to low. Use a restrained setting to compare a precise brief, or increase interpretation when the purpose is to discover a broader range of ideas.</p><p>Intensity, Complexity and Movement are independent integer sliders from -100 to 100, with 0 neutral. Intensity moves between muted and bold treatment. Complexity moves between simpler compositions and denser detail. Movement changes pose, visual energy and implied motion. These sliders can be combined with references and moodboards, and they are separate from creativity’s prompt expansion.</p><p>For the paper-bird brief, first compare a clean composition with a more detailed one while holding the other settings steady. Then explore a stronger visual treatment or a more energetic pose. Change one control at a time and keep the optional seed, prompt and reference set recorded. Movement affects a still image’s character; it does not produce an animated bird, camera move or video sequence.</p><h4>Frames, batches and completed images</h4><p>The model-specific generation schema offers a 1K resolution scale and nine aspect ratios: 1:1, 4:3, 3:2, 16:9, 2.35:1, 4:5, 3:4, 2:3 and 9:16. Krea’s Turbo workspace guide also describes generating up to four images in a batch. That batch setting belongs to the documented workspace workflow; it is distinct from the individual generation request schema.</p><p>Select the frame for the intended asset before generation. A vertical cover needs a different balance of subject and open space from a wide editorial image. Keep the generation scale separate from any subsequent enhancement or finished-layout export.</p><p>Krea’s documented generation flow returns a job that may initially be pending. Follow the job to completion and retrieve its resulting image locations. Compare the actual finished candidates for composition, shape, texture, palette and visible text, then preserve the selected image with its inputs and settings. If the asset needs precise lettering, place or correct that lettering in the finished design.</p><p>Turbo’s fast-exploration role does not guarantee a particular completion time, perfect lettering or an exact reconstruction of a reference image. Source-image strength and reference influence still require inspection of the result. Use the edition to resolve visual direction efficiently, select a concrete candidate, and make any final detail, layout or production corrections required by the intended use.</p></div></details></section><section class=\"card-section\" data-card-section=\"methods\"><h3 tabindex=\"-1\">Available in Ailoot · inputs &amp; methods</h3><details class=\"card-method\" open><summary><b>Ailoot Ultra · Images</b> <code>POST /v1/images/generations</code></summary><dl class=\"method-capabilities\"><div><dt>Input types</dt><dd><code>text</code>, <code>image</code></dd></div><div><dt>Output types</dt><dd><code>image</code></dd></div></dl><div class=\"tw\" data-card-parameters data-typed-parameters><table><thead><tr><th>Field</th><th>Type</th><th>Requirement</th><th>Values &amp; limits</th><th>Default</th></tr></thead><tbody><tr><th data-cell-label=\"Field\" scope=\"row\"><span class=\"card-cell-label\">Field</span><code class=\"card-field-name\">model</code></th><td data-cell-label=\"Type\" data-field-type><span class=\"card-cell-label\">Type</span><code>string</code></td><td data-cell-label=\"Requirement\"><span class=\"card-cell-label\">Requirement</span>Required</td><td data-cell-label=\"Values &amp; limits\"><span class=\"card-cell-label\">Values &amp; limits</span><div>krea/krea-2-medium-turbo</div></td><td data-cell-label=\"Default\" data-default=\"unspecified\"><span class=\"card-cell-label\">Default</span>—</td></tr><tr><th data-cell-label=\"Field\" scope=\"row\"><span class=\"card-cell-label\">Field</span><code class=\"card-field-name\">prompt</code></th><td data-cell-label=\"Type\" data-field-type><span class=\"card-cell-label\">Type</span><code>string</code></td><td data-cell-label=\"Requirement\"><span class=\"card-cell-label\">Requirement</span>Required</td><td data-cell-label=\"Values &amp; limits\"><span class=\"card-cell-label\">Values &amp; limits</span><div>Minimum length: 1</div></td><td data-cell-label=\"Default\" data-default=\"unspecified\"><span class=\"card-cell-label\">Default</span>—</td></tr><tr><th data-cell-label=\"Field\" scope=\"row\"><span class=\"card-cell-label\">Field</span><code class=\"card-field-name\">resolution</code></th><td data-cell-label=\"Type\" data-field-type><span class=\"card-cell-label\">Type</span><code>string</code></td><td data-cell-label=\"Requirement\"><span class=\"card-cell-label\">Requirement</span>Optional</td><td data-cell-label=\"Values &amp; limits\"><span class=\"card-cell-label\">Values &amp; limits</span><div>1K</div></td><td data-cell-label=\"Default\" data-default=\"unspecified\"><span class=\"card-cell-label\">Default</span>—</td></tr><tr><th data-cell-label=\"Field\" scope=\"row\"><span class=\"card-cell-label\">Field</span><code class=\"card-field-name\">aspect_ratio</code></th><td data-cell-label=\"Type\" data-field-type><span class=\"card-cell-label\">Type</span><code>string</code></td><td data-cell-label=\"Requirement\"><span class=\"card-cell-label\">Requirement</span>Optional</td><td data-cell-label=\"Values &amp; limits\"><span class=\"card-cell-label\">Values &amp; limits</span><div>1:1, 4:3, 3:2, 16:9, 4:5, 2:3, 9:16</div></td><td data-cell-label=\"Default\" data-default=\"unspecified\"><span class=\"card-cell-label\">Default</span>—</td></tr><tr><th data-cell-label=\"Field\" scope=\"row\"><span class=\"card-cell-label\">Field</span><code class=\"card-field-name\">input_references</code></th><td data-cell-label=\"Type\" data-field-type><span class=\"card-cell-label\">Type</span><code>array</code></td><td data-cell-label=\"Requirement\"><span class=\"card-cell-label\">Requirement</span>Optional</td><td data-cell-label=\"Values &amp; limits\"><span class=\"card-cell-label\">Values &amp; limits</span><div>Minimum items: 0</div><div>Maximum items: 1</div></td><td data-cell-label=\"Default\" data-default=\"unspecified\"><span class=\"card-cell-label\">Default</span>—</td></tr><tr><th data-cell-label=\"Field\" scope=\"row\"><span class=\"card-cell-label\">Field</span><code class=\"card-field-name\">provider</code></th><td data-cell-label=\"Type\" data-field-type><span class=\"card-cell-label\">Type</span><code>object</code></td><td data-cell-label=\"Requirement\"><span class=\"card-cell-label\">Requirement</span>Optional</td><td data-cell-label=\"Values &amp; limits\"><span class=\"card-cell-label\">Values &amp; limits</span></td><td data-cell-label=\"Default\" data-default=\"unspecified\"><span class=\"card-cell-label\">Default</span>—</td></tr></tbody></table></div><details class=\"note-s\" data-method-contract><summary>Method parameters and lifecycle</summary><div class=\"tw\" data-card-table=\"contract\"><table><thead><tr><th>Parameter</th><th>Contract</th></tr></thead><tbody><tr><th data-cell-label=\"Parameter\" scope=\"row\"><span class=\"card-cell-label\">Parameter</span><code>content_type</code></th><td data-cell-label=\"Contract\"><span class=\"card-cell-label\">Contract</span>application/json</td></tr><tr><th data-cell-label=\"Parameter\" scope=\"row\"><span class=\"card-cell-label\">Parameter</span><code>required</code></th><td data-cell-label=\"Contract\"><span class=\"card-cell-label\">Contract</span>model, prompt</td></tr><tr><th data-cell-label=\"Parameter\" scope=\"row\"><span class=\"card-cell-label\">Parameter</span><code>material_types</code></th><td data-cell-label=\"Contract\"><span class=\"card-cell-label\">Contract</span>text, image</td></tr></tbody></table></div><p>Lifecycle: <code>synchronous_result_then_owned_library</code></p><p class=\"note-s\"><code>GET /v1/media/tasks/{task_id}</code> · actual returned task_id or media library record</p><p class=\"note-s\"><code>GET /v1/media/assets/{asset_id}/content</code></p><p class=\"note-s\"><code>GET /v1/media/assets</code></p><p class=\"note-s\"><code>GET /v1/media/assets/{asset_id}</code></p></details></details></section><section class=\"card-section\" data-card-section=\"pricing\"><h3 tabindex=\"-1\">Pricing</h3><div class=\"card-result-process\" data-billing-basis><h5>How the final charge is calculated</h5><p class=\"note-s\">The displayed rates estimate the cost before generation. The final charge is calculated from the cost recorded for the original generation. Measured output duration and forecast quantities are not the final billable quantity.</p></div><div data-native-semantic-method=\"v1\" data-tariff-reference-only><p class=\"note-s\" data-rate-support-note>Tariff references do not add request options. Supported parameters are listed for the selected method.</p><dl data-price-conditions><dt>Fast mode</dt><dd>Not specified <span class=\"note-s\">When fast mode is selected</span></dd><dt>Flex mode</dt><dd>Not specified <span class=\"note-s\">When flex mode is selected</span></dd><dt>Maximum reasoning effort</dt><dd>Not specified <span class=\"note-s\">When maximum reasoning effort uses the default adjustment</span></dd></dl></div><div data-declared-tariff-pricing><h4>Estimated rates for comparison</h4><h4>Prices by configuration</h4><p class=\"note-s\">Match each charge to the conditions shown. Use one rate for each set of alternative configurations.</p><div class=\"tw\" data-pricing-profiles><table><thead><tr><th>Configuration</th><th>Rate schedule</th><th>Forecast quantity</th><th>Charge</th></tr></thead><tbody><tr><th data-cell-label=\"Configuration\" scope=\"row\"><span class=\"card-cell-label\">Configuration</span>Base token rates</th><td data-cell-label=\"Rate schedule\"><span class=\"card-cell-label\">Rate schedule</span>Base rate</td><td data-cell-label=\"Forecast quantity\"><span class=\"card-cell-label\">Forecast quantity</span>—</td><td data-cell-label=\"Charge\"><span class=\"card-cell-label\">Charge</span><div><span>Input · Input tokens · Estimate for comparison only</span> <b>—</b> <span class=\"price-unit\">/ 1K tokens</span></div><div><span>Output · Output tokens · Estimate for comparison only</span> <b>—</b> <span class=\"price-unit\">/ 1K tokens</span></div><div><span>Input · Cache read · Estimate for comparison only</span> <b>—</b> <span class=\"price-unit\">/ 1K tokens</span></div><div><span>Input · Cache write · Estimate for comparison only</span> <b>—</b> <span class=\"price-unit\">/ 1K tokens</span></div><div><span>Input · Cache write, 1 hour · Estimate for comparison only</span> <b>—</b> <span class=\"price-unit\">/ 1K tokens</span></div></td></tr><tr><th data-cell-label=\"Configuration\" scope=\"row\"><span class=\"card-cell-label\">Configuration</span>Estimated generation cost</th><td data-cell-label=\"Rate schedule\"><span class=\"card-cell-label\">Rate schedule</span>—</td><td data-cell-label=\"Forecast quantity\"><span class=\"card-cell-label\">Forecast quantity</span>one generation estimate</td><td data-cell-label=\"Charge\"><span class=\"card-cell-label\">Charge</span><div><span>Output · Estimated generation cost · Estimate for comparison only</span> <b>$0.03</b> <span class=\"price-unit\">estimate before generation</span></div><p class=\"note-s\">This estimate is not an additional charge or a fixed rate for the completed generation.</p></td></tr></tbody></table></div></div><p class=\"note-s\">Ailoot reserves an estimated amount before a request. After the result, it settles the final charge from measured usage. Streaming settlement uses the final usage record. <a href=\"/docs/en/billing/reserve/\">How reservation and settlement work →</a></p></section><section class=\"card-section\" data-card-section=\"examples\"><h3 tabindex=\"-1\">Example requests</h3><h4>Ailoot Ultra · Images</h4><div class=\"code-group\"><div class=\"cg-bar\"><div class=\"cg-tabs\" role=\"tablist\" aria-label=\"Code options\"><button class=\"cg-tab\" id=\"model-code-1777-tab-0\" role=\"tab\" type=\"button\" aria-controls=\"model-code-1777-panel-0\" aria-selected=\"true\" tabindex=\"0\">curl</button></div><div class=\"cg-tools\"><button class=\"cg-btn cg-copy\" type=\"button\" aria-label=\"Copy code\"><svg class=\"cp\" viewBox=\"0 0 16 16\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"1.4\"><rect x=\"5.25\" y=\"5.25\" width=\"8.5\" height=\"8.5\" rx=\"1.75\"/><path d=\"M10.75 5.25V3.5a1.25 1.25 0 0 0-1.25-1.25H3.5A1.25 1.25 0 0 0 2.25 3.5v6a1.25 1.25 0 0 0 1.25 1.25h1.75\"/></svg><svg class=\"ok\" viewBox=\"0 0 16 16\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"1.4\"><path d=\"m3 8.5 3.25 3.25L13 5\"/></svg></button></div></div><div class=\"cg-body\"><div class=\"cg-pane\" id=\"model-code-1777-panel-0\" role=\"tabpanel\" aria-labelledby=\"model-code-1777-tab-0\"><pre data-lang=\"bash\"><code>set -eu\n: &quot;${AILOOT_API_KEY:?Set your Ailoot API key}&quot;\nexport AILOOT_API_KEY\npython3 - &lt;&lt;&#39;PY_REQUEST&#39;\nimport json,os\nfrom pathlib import Path\np={&#39;model&#39;: &#39;krea/krea-2-medium-turbo&#39;, &#39;prompt&#39;: &#39;a red panda astronaut floating in space, studio lighting&#39;}\n\nPath(&quot;request.json&quot;).write_text(json.dumps(p,ensure_ascii=False))\nPY_REQUEST\ncurl --fail-with-body --silent --show-error https://api.ailoot.ai/v1/images/generations \\\n  -H &quot;Authorization: Bearer $AILOOT_API_KEY&quot; -H &#39;Content-Type: application/json&#39; \\\n  --data-binary @request.json -D response-headers.txt -o result.json\npython3 - &lt;&lt;&#39;PY_RESULT&#39;\nimport base64, json, os, subprocess\nfrom pathlib import Path\nfrom urllib.parse import urlsplit, urljoin\n\ndef save_images(items):\n    if not items: raise SystemExit(&quot;No completed images; retain the full response&quot;)\n    for index, item in enumerate(items):\n        encoded=item.get(&quot;b64_json&quot;)\n        uri=item.get(&quot;url&quot;, &quot;&quot;)\n        if not encoded and uri.startswith(&quot;data:image/&quot;):\n            header, separator, encoded=uri.partition(&quot;,&quot;)\n            if not separator or &quot;;base64&quot; not in header: raise SystemExit(&quot;Unsupported image data URI&quot;)\n        if encoded:\n            raw=base64.b64decode(encoded,validate=True)\n        elif uri:\n            uri=urljoin(&quot;https://api.ailoot.ai&quot;,uri)\n            parsed=urlsplit(uri)\n            if parsed.scheme!=&quot;https&quot; or not parsed.netloc or parsed.username or parsed.password:\n                raise SystemExit(&quot;Invalid returned image URL&quot;)\n            owned=parsed.netloc==&quot;api.ailoot.ai&quot; and parsed.path.startswith(&quot;/v1/media/assets/&quot;) and parsed.path.endswith(&quot;/content&quot;)\n            args=[&quot;curl&quot;,&quot;--fail-with-body&quot;,&quot;--silent&quot;,&quot;--show-error&quot;,uri]\n            if owned: args += [&quot;-H&quot;,&quot;Authorization: Bearer &quot;+os.environ[&quot;AILOOT_API_KEY&quot;]]\n            temporary=Path(f&quot;image-{index}.bin&quot;)\n            subprocess.run(args+[&quot;-o&quot;,str(temporary)],check=True)\n            raw=temporary.read_bytes()\n            temporary.unlink()\n        else: raise SystemExit(&quot;Image has neither bytes nor URL&quot;)\n        if not raw: raise SystemExit(&quot;Empty image result&quot;)\n        ext=&quot;png&quot; if raw.startswith(b&quot;\\x89PNG&quot;) else &quot;jpg&quot; if raw.startswith(b&quot;\\xff\\xd8&quot;) else &quot;webp&quot; if raw[:4]==b&quot;RIFF&quot; and raw[8:12]==b&quot;WEBP&quot; else &quot;svg&quot; if raw.lstrip().startswith((b&quot;&lt;svg&quot;,b&quot;&lt;?xml&quot;)) else &quot;bin&quot;\n        Path(f&quot;image-{index}.{ext}&quot;).write_bytes(raw)\n    print(&quot;Every returned image saved; complete response metadata retained&quot;)\nsave_images(json.loads(Path(&quot;result.json&quot;).read_text())[&quot;data&quot;])\nPY_RESULT\n</code></pre></div></div></div></section><section class=\"card-section\" data-card-section=\"results\"><h3 tabindex=\"-1\">Receive and save results</h3><h4>Ailoot Ultra · Images</h4><p class=\"note-s\">Download each returned image or save its Base64 contents</p><ul class=\"card-result-paths\"><li><code>GET /v1/media/tasks/{task_id}</code></li><li><code>GET /v1/media/assets/{asset_id}/content</code></li><li><code>GET /v1/media/assets</code></li><li><code>GET /v1/media/assets/{asset_id}</code></li></ul><details class=\"card-about\"><summary>Other content reads</summary><div class=\"code-group\"><div class=\"cg-bar\"><div class=\"cg-tabs\" role=\"tablist\" aria-label=\"Code options\"><button class=\"cg-tab\" id=\"model-code-1778-tab-0\" role=\"tab\" type=\"button\" aria-controls=\"model-code-1778-panel-0\" aria-selected=\"true\" tabindex=\"0\">Read existing owned assets</button></div><div class=\"cg-tools\"><button class=\"cg-btn cg-copy\" type=\"button\" aria-label=\"Copy code\"><svg class=\"cp\" viewBox=\"0 0 16 16\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"1.4\"><rect x=\"5.25\" y=\"5.25\" width=\"8.5\" height=\"8.5\" rx=\"1.75\"/><path d=\"M10.75 5.25V3.5a1.25 1.25 0 0 0-1.25-1.25H3.5A1.25 1.25 0 0 0 2.25 3.5v6a1.25 1.25 0 0 0 1.25 1.25h1.75\"/></svg><svg class=\"ok\" viewBox=\"0 0 16 16\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"1.4\"><path d=\"m3 8.5 3.25 3.25L13 5\"/></svg></button></div></div><div class=\"cg-body\"><div class=\"cg-pane\" id=\"model-code-1778-panel-0\" role=\"tabpanel\" aria-labelledby=\"model-code-1778-tab-0\"><pre data-lang=\"bash\"><code>set -eu\n: &quot;${AILOOT_API_KEY:?Set your Ailoot API key}&quot;\ncurl --fail-with-body --silent --show-error https://api.ailoot.ai/v1/media/assets \\\n  -H &quot;Authorization: Bearer $AILOOT_API_KEY&quot; -o owned-assets.json\n# Preserve every returned asset and follow its exact signed content URL. Do not construct a signed token.\n</code></pre></div></div></div></details><div class=\"card-result-process\" data-all-results><h5>Keep all completed results</h5><p class=\"note-s\">Save every completed image; retrieve each returned URL or decode its Base64 contents.</p><p class=\"note-s\">Retain the complete response and headers, every actual output, original returned identifiers and all usage fields. Recover the original operation without submitting creation again.</p></div><div class=\"card-result-process\" data-unknown-recovery><h5>If the original response needs checking</h5><p class=\"note-s\">Keep the returned X-Client-Request-ID for reconciliation. Read only actual returned task_id/asset_id values or the owned media library; never build a task URL from the operation ID and never resubmit creation.</p></div><details class=\"card-about\" data-output-fields><summary>Response fields</summary><div class=\"tw\" data-card-table=\"output\"><table><thead><tr><th>Field</th><th>Type</th></tr></thead><tbody><tr><th data-cell-label=\"Field\" scope=\"row\"><span class=\"card-cell-label\">Field</span><code class=\"card-field-name\">created</code></th><td data-cell-label=\"Type\" data-field-type><span class=\"card-cell-label\">Type</span></td></tr><tr><th data-cell-label=\"Field\" scope=\"row\"><span class=\"card-cell-label\">Field</span><code class=\"card-field-name\">data[].url</code></th><td data-cell-label=\"Type\" data-field-type><span class=\"card-cell-label\">Type</span></td></tr><tr><th data-cell-label=\"Field\" scope=\"row\"><span class=\"card-cell-label\">Field</span><code class=\"card-field-name\">data[].b64_json</code></th><td data-cell-label=\"Type\" data-field-type><span class=\"card-cell-label\">Type</span></td></tr><tr><th data-cell-label=\"Field\" scope=\"row\"><span class=\"card-cell-label\">Field</span><code class=\"card-field-name\">usage</code></th><td data-cell-label=\"Type\" data-field-type><span class=\"card-cell-label\">Type</span></td></tr></tbody></table></div></details></section><section class=\"card-section\" data-card-section=\"aliases\"><h3 tabindex=\"-1\">Aliases</h3><h4>Model aliases</h4><p class=\"note-s\"><span data-model-alias-route=\"Ultra\"><b>Ailoot Ultra</b> <a href=\"#m=krea%2Fkrea-2-medium-turbo&amp;route=Ultra&amp;caller=krea%2Fkrea-2-medium-turbo&amp;fmt=images\"><code>krea/krea-2-medium-turbo</code></a></span></p><h4>Method path aliases</h4><p class=\"note-s\"><code>/v1/images</code></p><h4>Related caller IDs</h4><p class=\"note-s\"><a href=\"#m=krea%2Fkrea-2-medium-turbo&amp;route=Ultra&amp;caller=krea%2Fkrea-2-medium-turbo&amp;fmt=images\"><code>krea/krea-2-medium-turbo</code></a></p></section></div>",
      "method_identity": {
        "effective_request_model_id": "krea/krea-2-medium-turbo",
        "fmt": "images",
        "http": "POST",
        "path": "/v1/images/generations",
        "request_model_id": "krea/krea-2-medium-turbo",
        "route_label": "Ultra"
      },
      "method_key": "Ultra|images|/v1/images/generations|krea%2Fkrea-2-medium-turbo",
      "ordinal": 0,
      "rawMethod": {
        "available": null,
        "billing_basis": {
          "basis": "original_invoice_usd",
          "description": "The displayed rates estimate the cost before generation. The final charge is calculated from the cost recorded for the original generation. Measured output duration and forecast quantities are not the final billable quantity.",
          "forecast_quantity_is_estimate": true,
          "physical_output_is_billable_quantity": false,
          "version": "original_invoice_usd_v1"
        },
        "cache_read": null,
        "cache_write": null,
        "cache_write_1h": null,
        "contract": {
          "data": {
            "all_results": "Retain the complete response and headers, every actual output, original returned identifiers and all usage fields. Recover the original operation without submitting creation again.",
            "lifecycle": {
              "assets": [
                {
                  "http": "GET",
                  "path": "/v1/media/assets"
                },
                {
                  "http": "GET",
                  "path": "/v1/media/assets/{asset_id}"
                }
              ],
              "content": [
                {
                  "http": "GET",
                  "path": "/v1/media/assets/{asset_id}/content",
                  "url_source": "exact returned signed URL; never construct token"
                }
              ],
              "mode": "synchronous_result_then_owned_library",
              "operation_id_is_not_task_id": true,
              "status": [
                {
                  "http": "GET",
                  "id_source": "actual returned task_id or media library record",
                  "path": "/v1/media/tasks/{task_id}"
                }
              ],
              "unknown": "Keep the returned X-Client-Request-ID for reconciliation. Read only actual returned task_id/asset_id values or the owned media library; never build a task URL from the operation ID and never resubmit creation."
            },
            "outputs": {
              "all_results": "Retain the complete response and headers, every actual output, original returned identifiers and all usage fields. Recover the original operation without submitting creation again.",
              "family": "image",
              "fields": [
                {
                  "description": null,
                  "name": "created",
                  "type": null
                },
                {
                  "description": null,
                  "name": "data[].url",
                  "type": null
                },
                {
                  "description": null,
                  "name": "data[].b64_json",
                  "type": null
                },
                {
                  "description": null,
                  "name": "usage",
                  "type": null
                }
              ]
            },
            "parameters": [
              {
                "enum": [
                  "krea/krea-2-medium-turbo"
                ],
                "enum_known": true,
                "name": "model",
                "required": true,
                "type": "string"
              },
              {
                "min_length": 1,
                "name": "prompt",
                "required": true,
                "type": "string"
              },
              {
                "enum": [
                  "1K"
                ],
                "enum_known": true,
                "name": "resolution",
                "required": false,
                "type": "string"
              },
              {
                "enum": [
                  "1:1",
                  "4:3",
                  "3:2",
                  "16:9",
                  "4:5",
                  "2:3",
                  "9:16"
                ],
                "enum_known": true,
                "name": "aspect_ratio",
                "required": false,
                "type": "string"
              },
              {
                "items": {
                  "properties": {
                    "image_url": {
                      "properties": {
                        "url": {
                          "type": "string"
                        }
                      },
                      "required": [
                        "url"
                      ],
                      "type": "object"
                    },
                    "type": {
                      "const": "image_url"
                    }
                  },
                  "required": [
                    "type",
                    "image_url"
                  ],
                  "type": "object"
                },
                "maximum_items": 1,
                "minimum_items": 0,
                "name": "input_references",
                "required": false,
                "type": "array"
              },
              {
                "name": "provider",
                "required": false,
                "type": "object"
              }
            ],
            "request_schema": {
              "properties": {
                "aspect_ratio": {
                  "enum": [
                    "1:1",
                    "4:3",
                    "3:2",
                    "16:9",
                    "4:5",
                    "2:3",
                    "9:16"
                  ],
                  "type": "string"
                },
                "input_references": {
                  "items": {
                    "properties": {
                      "image_url": {
                        "properties": {
                          "url": {
                            "type": "string"
                          }
                        },
                        "required": [
                          "url"
                        ],
                        "type": "object"
                      },
                      "type": {
                        "const": "image_url"
                      }
                    },
                    "required": [
                      "type",
                      "image_url"
                    ],
                    "type": "object"
                  },
                  "maxItems": 1,
                  "minItems": 0,
                  "type": "array"
                },
                "model": {
                  "enum": [
                    "krea/krea-2-medium-turbo"
                  ],
                  "type": "string"
                },
                "prompt": {
                  "minLength": 1,
                  "type": "string"
                },
                "provider": {
                  "description": "Exact image provider preferences from the documented image request schema.",
                  "type": "object"
                },
                "resolution": {
                  "enum": [
                    "1K"
                  ],
                  "type": "string"
                }
              },
              "required": [
                "model",
                "prompt"
              ],
              "type": "object"
            },
            "schema_template": {
              "actual_file_preparation_required": false,
              "body": {
                "model": "krea/krea-2-medium-turbo",
                "prompt": "a red panda astronaut floating in space, studio lighting"
              },
              "content_type": "application/json"
            }
          },
          "input": {
            "content_type": "application/json",
            "material_types": [
              "text",
              "image"
            ],
            "required": [
              "model",
              "prompt"
            ]
          },
          "lifecycle": {
            "assets": [
              {
                "http": "GET",
                "path": "/v1/media/assets"
              },
              {
                "http": "GET",
                "path": "/v1/media/assets/{asset_id}"
              }
            ],
            "content": [
              {
                "http": "GET",
                "path": "/v1/media/assets/{asset_id}/content",
                "url_source": "exact returned signed URL; never construct token"
              }
            ],
            "mode": "synchronous_result_then_owned_library",
            "operation_id_is_not_task_id": true,
            "status": [
              {
                "http": "GET",
                "id_source": "actual returned task_id or media library record",
                "path": "/v1/media/tasks/{task_id}"
              }
            ],
            "unknown": "Keep the returned X-Client-Request-ID for reconciliation. Read only actual returned task_id/asset_id values or the owned media library; never build a task URL from the operation ID and never resubmit creation."
          },
          "method": {
            "http": "POST",
            "path": "/v1/images/generations"
          },
          "output": {
            "all_results": "Retain the complete response and headers, every actual output, original returned identifiers and all usage fields. Recover the original operation without submitting creation again.",
            "family": "image",
            "fields": [
              {
                "description": null,
                "name": "created",
                "type": null
              },
              {
                "description": null,
                "name": "data[].url",
                "type": null
              },
              {
                "description": null,
                "name": "data[].b64_json",
                "type": null
              },
              {
                "description": null,
                "name": "usage",
                "type": null
              }
            ]
          }
        },
        "ctx": null,
        "declared_pricing_profiles": [
          {
            "dimensions": {
              "regime": "base"
            },
            "label": "Base token rates",
            "units": [
              {
                "amount": null,
                "amount_unit": "usd_per_thousand_tokens",
                "billing_input": false,
                "estimate_only": true,
                "key": "input_price",
                "label": "Input tokens",
                "native_amount_usd_per_unit": null,
                "native_quantity": 1,
                "native_unit": "input_token",
                "public_unit_label": "/ 1K tokens",
                "quantity": 1000,
                "quantity_is_estimate": true,
                "rate_role": "typed_native_retail_rate",
                "side": "in",
                "unit": "input_token"
              },
              {
                "amount": null,
                "amount_unit": "usd_per_thousand_tokens",
                "billing_input": false,
                "estimate_only": true,
                "key": "output_price",
                "label": "Output tokens",
                "native_amount_usd_per_unit": null,
                "native_quantity": 1,
                "native_unit": "output_token",
                "public_unit_label": "/ 1K tokens",
                "quantity": 1000,
                "quantity_is_estimate": true,
                "rate_role": "typed_native_retail_rate",
                "side": "out",
                "unit": "output_token"
              },
              {
                "amount": null,
                "amount_unit": "usd_per_thousand_tokens",
                "billing_input": false,
                "estimate_only": true,
                "key": "cache_read_price",
                "label": "Cache read",
                "native_amount_usd_per_unit": null,
                "native_quantity": 1,
                "native_unit": "cached_input_token",
                "public_unit_label": "/ 1K tokens",
                "quantity": 1000,
                "quantity_is_estimate": true,
                "rate_role": "typed_native_retail_rate",
                "side": "in",
                "unit": "cached_input_token"
              },
              {
                "amount": null,
                "amount_unit": "usd_per_thousand_tokens",
                "billing_input": false,
                "estimate_only": true,
                "key": "cache_write_price",
                "label": "Cache write",
                "native_amount_usd_per_unit": null,
                "native_quantity": 1,
                "native_unit": "generic_cache_creation_token",
                "public_unit_label": "/ 1K tokens",
                "quantity": 1000,
                "quantity_is_estimate": true,
                "rate_role": "typed_native_retail_rate",
                "side": "in",
                "unit": "generic_cache_creation_token"
              },
              {
                "amount": null,
                "amount_unit": "usd_per_thousand_tokens",
                "billing_input": false,
                "estimate_only": true,
                "key": "cache_write_1h_price",
                "label": "Cache write, 1 hour",
                "native_amount_usd_per_unit": null,
                "native_quantity": 1,
                "native_unit": "one_hour_cache_creation_token",
                "public_unit_label": "/ 1K tokens",
                "quantity": 1000,
                "quantity_is_estimate": true,
                "rate_role": "typed_native_retail_rate",
                "side": "in",
                "unit": "one_hour_cache_creation_token"
              }
            ]
          },
          {
            "basis": "This estimate is not an additional charge or a fixed rate for the completed generation.",
            "dimensions": {
              "forecast_quantity": "one generation estimate"
            },
            "label": "Estimated generation cost",
            "units": [
              {
                "amount": "0.03",
                "amount_unit": "usd_per_exact_native_unit",
                "billing_input": false,
                "estimate_only": true,
                "key": "forecast_usd",
                "label": "Estimated generation cost",
                "native_amount_usd_per_unit": "0.03",
                "native_quantity": 1,
                "public_unit_label": "estimate before generation",
                "quantity": 1,
                "quantity_is_estimate": true,
                "rate_role": "typed_native_retail_rate",
                "side": "out",
                "unit": "request_estimate"
              }
            ]
          }
        ],
        "examples": [
          {
            "code": "set -eu\n: \"${AILOOT_API_KEY:?Set your Ailoot API key}\"\nexport AILOOT_API_KEY\npython3 - <<'PY_REQUEST'\nimport json,os\nfrom pathlib import Path\np={'model': 'krea/krea-2-medium-turbo', 'prompt': 'a red panda astronaut floating in space, studio lighting'}\n\nPath(\"request.json\").write_text(json.dumps(p,ensure_ascii=False))\nPY_REQUEST\ncurl --fail-with-body --silent --show-error https://api.ailoot.ai/v1/images/generations \\\n  -H \"Authorization: Bearer $AILOOT_API_KEY\" -H 'Content-Type: application/json' \\\n  --data-binary @request.json -D response-headers.txt -o result.json\npython3 - <<'PY_RESULT'\nimport base64, json, os, subprocess\nfrom pathlib import Path\nfrom urllib.parse import urlsplit, urljoin\n\ndef save_images(items):\n    if not items: raise SystemExit(\"No completed images; retain the full response\")\n    for index, item in enumerate(items):\n        encoded=item.get(\"b64_json\")\n        uri=item.get(\"url\", \"\")\n        if not encoded and uri.startswith(\"data:image/\"):\n            header, separator, encoded=uri.partition(\",\")\n            if not separator or \";base64\" not in header: raise SystemExit(\"Unsupported image data URI\")\n        if encoded:\n            raw=base64.b64decode(encoded,validate=True)\n        elif uri:\n            uri=urljoin(\"https://api.ailoot.ai\",uri)\n            parsed=urlsplit(uri)\n            if parsed.scheme!=\"https\" or not parsed.netloc or parsed.username or parsed.password:\n                raise SystemExit(\"Invalid returned image URL\")\n            owned=parsed.netloc==\"api.ailoot.ai\" and parsed.path.startswith(\"/v1/media/assets/\") and parsed.path.endswith(\"/content\")\n            args=[\"curl\",\"--fail-with-body\",\"--silent\",\"--show-error\",uri]\n            if owned: args += [\"-H\",\"Authorization: Bearer \"+os.environ[\"AILOOT_API_KEY\"]]\n            temporary=Path(f\"image-{index}.bin\")\n            subprocess.run(args+[\"-o\",str(temporary)],check=True)\n            raw=temporary.read_bytes()\n            temporary.unlink()\n        else: raise SystemExit(\"Image has neither bytes nor URL\")\n        if not raw: raise SystemExit(\"Empty image result\")\n        ext=\"png\" if raw.startswith(b\"\\x89PNG\") else \"jpg\" if raw.startswith(b\"\\xff\\xd8\") else \"webp\" if raw[:4]==b\"RIFF\" and raw[8:12]==b\"WEBP\" else \"svg\" if raw.lstrip().startswith((b\"<svg\",b\"<?xml\")) else \"bin\"\n        Path(f\"image-{index}.{ext}\").write_bytes(raw)\n    print(\"Every returned image saved; complete response metadata retained\")\nsave_images(json.loads(Path(\"result.json\").read_text())[\"data\"])\nPY_RESULT\n",
            "label": "curl · exact creation/save all outputs",
            "language": "bash"
          },
          {
            "code": "set -eu\n: \"${AILOOT_API_KEY:?Set your Ailoot API key}\"\ncurl --fail-with-body --silent --show-error https://api.ailoot.ai/v1/media/assets \\\n  -H \"Authorization: Bearer $AILOOT_API_KEY\" -o owned-assets.json\n# Preserve every returned asset and follow its exact signed content URL. Do not construct a signed token.\n",
            "label": "Read existing owned assets",
            "language": "bash"
          }
        ],
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    "description": "Krea 2 Medium Turbo is Krea’s fast image-generation edition for exploring visual ideas and producing expressive drafts. It combines a distilled sampling schedule with text, source-image and style controls, including independent adjustments for intensity, complexity and implied motion.",
    "locale": "en",
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    "about": "### Fast exploration within the Krea 2 family\n\nKrea 2 Medium Turbo is the generation edition Krea presents as Krea 2 Turbo. Its model-specific interface identifies the Medium Turbo variant, and Krea’s user guide describes a distilled sampling schedule that reduces the work needed to generate an image. Krea positions it as the family’s fastest option for broad creative exploration, expressive rough drafts, illustration and graphic directions.\n\nUse it when the immediate goal is to compare ideas: alternative compositions for a cover, visual treatments for a campaign or different illustration styles for the same scene. A concise, concrete starting brief makes comparisons easier. For example: “A folded red paper bird above a pale-blue desk, bold editorial illustration, hard afternoon shadow, simple geometric shapes, vertical composition with clear space at the bottom.” Keep the subject and frame steady while exploring the visual treatment, then develop the selected direction further.\n\nKrea’s edition guidance favors Medium when a more stable illustration treatment is needed and Large for a photographic or raw-textured final direction. Turbo remains its own edition; a later pass in another model is a separate generation rather than an automatic quality upgrade or an identical continuation.\n\n### Prepare the prompt and visual inputs\n\nThe model’s generation schema requires a prompt, aspect ratio and resolution. Optional image-to-image input starts generation from a source image rather than pure noise. Its denoising strength runs from 0 to 1: 0 keeps the input, 1 fully replaces it, and the documented default is 0.99. Prepare the starting composition carefully and describe what should change; a high strength allows substantial replacement of the source.\n\nStyle references supply appearance through images rather than changing the starting-image strength. The model-specific schema limits source-image and style-reference URI strings to 1,024 characters. The model-specific request schema accepts up to ten references, each with influence from 0 to 1 and a default of 0.5. Select references with clear roles, such as a color palette, drawing treatment or lighting direction. The separate Krea workspace guide describes up to four style references in that interface; the two interfaces should be prepared with their respective limits.\n\nMoodboards organize a coherent visual direction into a reusable input. Create the moodboard first and use its existing identifier when generating. The model schema accepts one moodboard, with influence from 0 to 1 and a default of 0.23. Trained styles, typically LoRAs, are another input selected by identifier and strength from -2 to 2. A source image, a style reference, a moodboard and a trained style have different roles, so avoid treating them as interchangeable ways to preserve every detail.\n\n### Adjust creativity and the three visual sliders\n\nCreativity controls prompt expansion. Raw disables it; low, medium and high change how much interpretation is added to the brief. The model-specific schema defaults to low. Use a restrained setting to compare a precise brief, or increase interpretation when the purpose is to discover a broader range of ideas.\n\nIntensity, Complexity and Movement are independent integer sliders from -100 to 100, with 0 neutral. Intensity moves between muted and bold treatment. Complexity moves between simpler compositions and denser detail. Movement changes pose, visual energy and implied motion. These sliders can be combined with references and moodboards, and they are separate from creativity’s prompt expansion.\n\nFor the paper-bird brief, first compare a clean composition with a more detailed one while holding the other settings steady. Then explore a stronger visual treatment or a more energetic pose. Change one control at a time and keep the optional seed, prompt and reference set recorded. Movement affects a still image’s character; it does not produce an animated bird, camera move or video sequence.\n\n### Frames, batches and completed images\n\nThe model-specific generation schema offers a 1K resolution scale and nine aspect ratios: 1:1, 4:3, 3:2, 16:9, 2.35:1, 4:5, 3:4, 2:3 and 9:16. Krea’s Turbo workspace guide also describes generating up to four images in a batch. That batch setting belongs to the documented workspace workflow; it is distinct from the individual generation request schema.\n\nSelect the frame for the intended asset before generation. A vertical cover needs a different balance of subject and open space from a wide editorial image. Keep the generation scale separate from any subsequent enhancement or finished-layout export.\n\nKrea’s documented generation flow returns a job that may initially be pending. Follow the job to completion and retrieve its resulting image locations. Compare the actual finished candidates for composition, shape, texture, palette and visible text, then preserve the selected image with its inputs and settings. If the asset needs precise lettering, place or correct that lettering in the finished design.\n\nTurbo’s fast-exploration role does not guarantee a particular completion time, perfect lettering or an exact reconstruction of a reference image. Source-image strength and reference influence still require inspection of the result. Use the edition to resolve visual direction efficiently, select a concrete candidate, and make any final detail, layout or production corrections required by the intended use.",
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                "native_quantity": 1,
                "native_unit": "cached_input_token",
                "public_unit_label": "/ 1K tokens",
                "quantity": 1000,
                "quantity_is_estimate": true,
                "rate_role": "typed_native_retail_rate",
                "side": "in",
                "unit": "cached_input_token"
              },
              {
                "amount": null,
                "amount_unit": "usd_per_thousand_tokens",
                "billing_input": false,
                "estimate_only": true,
                "key": "cache_write_price",
                "label": "Cache write",
                "native_amount_usd_per_unit": null,
                "native_quantity": 1,
                "native_unit": "generic_cache_creation_token",
                "public_unit_label": "/ 1K tokens",
                "quantity": 1000,
                "quantity_is_estimate": true,
                "rate_role": "typed_native_retail_rate",
                "side": "in",
                "unit": "generic_cache_creation_token"
              },
              {
                "amount": null,
                "amount_unit": "usd_per_thousand_tokens",
                "billing_input": false,
                "estimate_only": true,
                "key": "cache_write_1h_price",
                "label": "Cache write, 1 hour",
                "native_amount_usd_per_unit": null,
                "native_quantity": 1,
                "native_unit": "one_hour_cache_creation_token",
                "public_unit_label": "/ 1K tokens",
                "quantity": 1000,
                "quantity_is_estimate": true,
                "rate_role": "typed_native_retail_rate",
                "side": "in",
                "unit": "one_hour_cache_creation_token"
              }
            ]
          },
          {
            "basis": "This estimate is not an additional charge or a fixed rate for the completed generation.",
            "dimensions": {
              "forecast_quantity": "one generation estimate"
            },
            "label": "Estimated generation cost",
            "units": [
              {
                "amount": "0.03",
                "amount_unit": "usd_per_exact_native_unit",
                "billing_input": false,
                "estimate_only": true,
                "key": "forecast_usd",
                "label": "Estimated generation cost",
                "native_amount_usd_per_unit": "0.03",
                "native_quantity": 1,
                "public_unit_label": "estimate before generation",
                "quantity": 1,
                "quantity_is_estimate": true,
                "rate_role": "typed_native_retail_rate",
                "side": "out",
                "unit": "request_estimate"
              }
            ]
          }
        ],
        "examples": [
          {
            "code": "set -eu\n: \"${AILOOT_API_KEY:?Set your Ailoot API key}\"\nexport AILOOT_API_KEY\npython3 - <<'PY_REQUEST'\nimport json,os\nfrom pathlib import Path\np={'model': 'krea/krea-2-medium-turbo', 'prompt': 'a red panda astronaut floating in space, studio lighting'}\n\nPath(\"request.json\").write_text(json.dumps(p,ensure_ascii=False))\nPY_REQUEST\ncurl --fail-with-body --silent --show-error https://api.ailoot.ai/v1/images/generations \\\n  -H \"Authorization: Bearer $AILOOT_API_KEY\" -H 'Content-Type: application/json' \\\n  --data-binary @request.json -D response-headers.txt -o result.json\npython3 - <<'PY_RESULT'\nimport base64, json, os, subprocess\nfrom pathlib import Path\nfrom urllib.parse import urlsplit, urljoin\n\ndef save_images(items):\n    if not items: raise SystemExit(\"No completed images; retain the full response\")\n    for index, item in enumerate(items):\n        encoded=item.get(\"b64_json\")\n        uri=item.get(\"url\", \"\")\n        if not encoded and uri.startswith(\"data:image/\"):\n            header, separator, encoded=uri.partition(\",\")\n            if not separator or \";base64\" not in header: raise SystemExit(\"Unsupported image data URI\")\n        if encoded:\n            raw=base64.b64decode(encoded,validate=True)\n        elif uri:\n            uri=urljoin(\"https://api.ailoot.ai\",uri)\n            parsed=urlsplit(uri)\n            if parsed.scheme!=\"https\" or not parsed.netloc or parsed.username or parsed.password:\n                raise SystemExit(\"Invalid returned image URL\")\n            owned=parsed.netloc==\"api.ailoot.ai\" and parsed.path.startswith(\"/v1/media/assets/\") and parsed.path.endswith(\"/content\")\n            args=[\"curl\",\"--fail-with-body\",\"--silent\",\"--show-error\",uri]\n            if owned: args += [\"-H\",\"Authorization: Bearer \"+os.environ[\"AILOOT_API_KEY\"]]\n            temporary=Path(f\"image-{index}.bin\")\n            subprocess.run(args+[\"-o\",str(temporary)],check=True)\n            raw=temporary.read_bytes()\n            temporary.unlink()\n        else: raise SystemExit(\"Image has neither bytes nor URL\")\n        if not raw: raise SystemExit(\"Empty image result\")\n        ext=\"png\" if raw.startswith(b\"\\x89PNG\") else \"jpg\" if raw.startswith(b\"\\xff\\xd8\") else \"webp\" if raw[:4]==b\"RIFF\" and raw[8:12]==b\"WEBP\" else \"svg\" if raw.lstrip().startswith((b\"<svg\",b\"<?xml\")) else \"bin\"\n        Path(f\"image-{index}.{ext}\").write_bytes(raw)\n    print(\"Every returned image saved; complete response metadata retained\")\nsave_images(json.loads(Path(\"result.json\").read_text())[\"data\"])\nPY_RESULT\n",
            "label": "curl · exact creation/save all outputs",
            "language": "bash"
          },
          {
            "code": "set -eu\n: \"${AILOOT_API_KEY:?Set your Ailoot API key}\"\ncurl --fail-with-body --silent --show-error https://api.ailoot.ai/v1/media/assets \\\n  -H \"Authorization: Bearer $AILOOT_API_KEY\" -o owned-assets.json\n# Preserve every returned asset and follow its exact signed content URL. Do not construct a signed token.\n",
            "label": "Read existing owned assets",
            "language": "bash"
          }
        ],
        "family": "openai",
        "fast_multiplier": null,
        "flex_multiplier": null,
        "fmt": "images",
        "hints": [
          "Use the exact caller model ID and documented input representation.",
          "Retain the complete response and headers, every actual output, original returned identifiers and all usage fields. Recover the original operation without submitting creation again."
        ],
        "http": "POST",
        "in": null,
        "input": [
          "text",
          "image"
        ],
        "label": "Images",
        "max_out": null,
        "max_reasoning_effort_multiplier": null,
        "method_aliases": [
          "/v1/images"
        ],
        "native_endpoint": "images",
        "out": null,
        "output": [
          "image"
        ],
        "path": "/v1/images/generations",
        "price_conditions": [
          {
            "label": "Fast mode",
            "value": "Not specified",
            "when": "When fast mode is selected"
          },
          {
            "label": "Flex mode",
            "value": "Not specified",
            "when": "When flex mode is selected"
          },
          {
            "label": "Maximum reasoning effort",
            "value": "Not specified",
            "when": "When maximum reasoning effort uses the default adjustment"
          }
        ],
        "pricing": {
          "billing_mode": "original_invoice_usd",
          "image_input_price": null,
          "image_output_price": null
        },
        "pricing_profiles": [
          {
            "dimensions": {
              "regime": "base"
            },
            "label": "Base token rates",
            "units": [
              {
                "amount": null,
                "amount_unit": "usd_per_thousand_tokens",
                "billing_input": false,
                "estimate_only": true,
                "key": "input_price",
                "label": "Input tokens",
                "native_amount_usd_per_unit": null,
                "native_quantity": 1,
                "native_unit": "input_token",
                "public_unit_label": "/ 1K tokens",
                "quantity": 1000,
                "quantity_is_estimate": true,
                "rate_role": "typed_native_retail_rate",
                "side": "in",
                "unit": "input_token"
              },
              {
                "amount": null,
                "amount_unit": "usd_per_thousand_tokens",
                "billing_input": false,
                "estimate_only": true,
                "key": "output_price",
                "label": "Output tokens",
                "native_amount_usd_per_unit": null,
                "native_quantity": 1,
                "native_unit": "output_token",
                "public_unit_label": "/ 1K tokens",
                "quantity": 1000,
                "quantity_is_estimate": true,
                "rate_role": "typed_native_retail_rate",
                "side": "out",
                "unit": "output_token"
              },
              {
                "amount": null,
                "amount_unit": "usd_per_thousand_tokens",
                "billing_input": false,
                "estimate_only": true,
                "key": "cache_read_price",
                "label": "Cache read",
                "native_amount_usd_per_unit": null,
                "native_quantity": 1,
                "native_unit": "cached_input_token",
                "public_unit_label": "/ 1K tokens",
                "quantity": 1000,
                "quantity_is_estimate": true,
                "rate_role": "typed_native_retail_rate",
                "side": "in",
                "unit": "cached_input_token"
              },
              {
                "amount": null,
                "amount_unit": "usd_per_thousand_tokens",
                "billing_input": false,
                "estimate_only": true,
                "key": "cache_write_price",
                "label": "Cache write",
                "native_amount_usd_per_unit": null,
                "native_quantity": 1,
                "native_unit": "generic_cache_creation_token",
                "public_unit_label": "/ 1K tokens",
                "quantity": 1000,
                "quantity_is_estimate": true,
                "rate_role": "typed_native_retail_rate",
                "side": "in",
                "unit": "generic_cache_creation_token"
              },
              {
                "amount": null,
                "amount_unit": "usd_per_thousand_tokens",
                "billing_input": false,
                "estimate_only": true,
                "key": "cache_write_1h_price",
                "label": "Cache write, 1 hour",
                "native_amount_usd_per_unit": null,
                "native_quantity": 1,
                "native_unit": "one_hour_cache_creation_token",
                "public_unit_label": "/ 1K tokens",
                "quantity": 1000,
                "quantity_is_estimate": true,
                "rate_role": "typed_native_retail_rate",
                "side": "in",
                "unit": "one_hour_cache_creation_token"
              }
            ]
          },
          {
            "basis": "This estimate is not an additional charge or a fixed rate for the completed generation.",
            "dimensions": {
              "forecast_quantity": "one generation estimate"
            },
            "label": "Estimated generation cost",
            "units": [
              {
                "amount": "0.03",
                "amount_unit": "usd_per_exact_native_unit",
                "billing_input": false,
                "estimate_only": true,
                "key": "forecast_usd",
                "label": "Estimated generation cost",
                "native_amount_usd_per_unit": "0.03",
                "native_quantity": 1,
                "public_unit_label": "estimate before generation",
                "quantity": 1,
                "quantity_is_estimate": true,
                "rate_role": "typed_native_retail_rate",
                "side": "out",
                "unit": "request_estimate"
              }
            ]
          }
        ],
        "request_model_id": "krea/krea-2-medium-turbo",
        "route_label": "Ultra",
        "status_reads": [
          "GET /v1/media/tasks/{task_id}"
        ],
        "tiers": [],
        "units": [
          {
            "amount": null,
            "amount_unit": "usd_per_thousand_tokens",
            "billing_input": false,
            "estimate_only": true,
            "key": "input_price",
            "label": "Input tokens",
            "native_amount_usd_per_unit": null,
            "native_quantity": 1,
            "native_unit": "input_token",
            "public_unit_label": "/ 1K tokens",
            "quantity": 1000,
            "quantity_is_estimate": true,
            "rate_role": "typed_native_retail_rate",
            "side": "in",
            "unit": "input_token"
          },
          {
            "amount": null,
            "amount_unit": "usd_per_thousand_tokens",
            "billing_input": false,
            "estimate_only": true,
            "key": "output_price",
            "label": "Output tokens",
            "native_amount_usd_per_unit": null,
            "native_quantity": 1,
            "native_unit": "output_token",
            "public_unit_label": "/ 1K tokens",
            "quantity": 1000,
            "quantity_is_estimate": true,
            "rate_role": "typed_native_retail_rate",
            "side": "out",
            "unit": "output_token"
          },
          {
            "amount": null,
            "amount_unit": "usd_per_thousand_tokens",
            "billing_input": false,
            "estimate_only": true,
            "key": "cache_read_price",
            "label": "Cache read",
            "native_amount_usd_per_unit": null,
            "native_quantity": 1,
            "native_unit": "cached_input_token",
            "public_unit_label": "/ 1K tokens",
            "quantity": 1000,
            "quantity_is_estimate": true,
            "rate_role": "typed_native_retail_rate",
            "side": "in",
            "unit": "cached_input_token"
          },
          {
            "amount": null,
            "amount_unit": "usd_per_thousand_tokens",
            "billing_input": false,
            "estimate_only": true,
            "key": "cache_write_price",
            "label": "Cache write",
            "native_amount_usd_per_unit": null,
            "native_quantity": 1,
            "native_unit": "generic_cache_creation_token",
            "public_unit_label": "/ 1K tokens",
            "quantity": 1000,
            "quantity_is_estimate": true,
            "rate_role": "typed_native_retail_rate",
            "side": "in",
            "unit": "generic_cache_creation_token"
          },
          {
            "amount": null,
            "amount_unit": "usd_per_thousand_tokens",
            "billing_input": false,
            "estimate_only": true,
            "key": "cache_write_1h_price",
            "label": "Cache write, 1 hour",
            "native_amount_usd_per_unit": null,
            "native_quantity": 1,
            "native_unit": "one_hour_cache_creation_token",
            "public_unit_label": "/ 1K tokens",
            "quantity": 1000,
            "quantity_is_estimate": true,
            "rate_role": "typed_native_retail_rate",
            "side": "in",
            "unit": "one_hour_cache_creation_token"
          },
          {
            "amount": "0.03",
            "amount_unit": "usd_per_exact_native_unit",
            "billing_input": false,
            "estimate_only": true,
            "key": "forecast_usd",
            "label": "Estimated generation cost",
            "native_amount_usd_per_unit": "0.03",
            "native_quantity": 1,
            "public_unit_label": "estimate before generation",
            "quantity": 1,
            "quantity_is_estimate": true,
            "rate_role": "typed_native_retail_rate",
            "side": "out",
            "unit": "request_estimate"
          }
        ]
      }
    ],
    "model_aliases": [
      {
        "canonical_model_id": "krea/krea-2-medium-turbo",
        "request_model_id": "krea/krea-2-medium-turbo",
        "route_label": "Ultra"
      }
    ],
    "name": "Krea: Krea 2 Medium Turbo",
    "price": {
      "estimate_only": true,
      "in": null,
      "in_label": null,
      "out": 0.03,
      "out_label": "estimate before generation",
      "scope_label": "Estimated generation cost",
      "sort_in": null,
      "sort_out": 0.03,
      "varies": false
    },
    "short": "Krea 2 Medium Turbo is Krea’s fast image-generation edition for exploring visual ideas and producing expressive drafts. It combines a distilled sampling schedule with text, source-image and style controls, including independent adjustments for intensity, complexity and implied motion."
  },
  "renderer_schema": {
    "method_order": "Original DTO methods order; every exact route/format/path/caller survives.",
    "prices": "Original public DTO fields and original native display HTML; no flattened or normalized offers."
  },
  "representation": "exact-public-dto-and-native-renderer-html",
  "representationNotes": {
    "current_reference": {
      "about_json_pointer": "/aboutHtml",
      "methods": [
        {
          "contract_json_pointer": "/methods/0/rawMethod/contract",
          "html_json_pointer": "/methods/0/html",
          "method_ordinal": 0
        }
      ],
      "role": "current-semantic-reference"
    },
    "raw_input": {
      "examples_role": "historical-input-not-current-ready-examples",
      "json_pointers": [
        "/rawModel",
        "/methods/0/rawMethod"
      ],
      "role": "historical-owner-input"
    },
    "schema": "ailoot-native-model-representations-v1"
  },
  "schema": "ailoot-static-model-facts-v1",
  "schema_version": 1,
  "shortText": "Krea 2 Medium Turbo is Krea’s fast image-generation edition for exploring visual ideas and producing expressive drafts. It combines a distilled sampling schedule with text, source-image and style controls, including independent adjustments for intensity, complexity and implied motion.",
  "source": {
    "audit_sha256": "2e00086bcbfc28e64d0cebe97aa47c17d8d5618963027f8ffb9dc6123d7d25b1",
    "bridge_map_sha256": "1125275768b9636fc8461bc7da5061239a81ddfe508e2557843ca42c58ab0036",
    "raw_model_json_sha256": "3c9d1986e555190683e1641c59b3b21ff1c75b2228b90d1b6ace2fa933e43a3b",
    "renderer_sha256": "fed50305bd3bcc4980ac14df23640efb8c1bc1e819f9d53643d6f43e8974d3fe"
  },
  "sourceRevision": "67d31ae2efeee74e49c7aaf920a4e07ce337cff095e381ae7892e639b2322285"
}
