Grok Imagine Image Quality is SpaceXAI’s named image generation and editing model with an emphasis on realistic detail, stronger text rendering and close following of a creative brief. It accepts text and optional image references and returns an image. Its use cases include product visualisation, campaign creative, social assets, illustrations and UI-style icons, with a style range that includes photographic and cinematic imagery as well as graphic artwork.
For a product scene, describe the object, arrangement, material, lighting and camera view before adding decorative style. Supply a reference when the product’s shape or lettering needs to remain recognisable. A useful brief can place a small labelled bottle on a stone surface with a defined palette and space for a heading. For an icon or graphic, state the shape, contrast and intended visual scale. The result is a rendered image rather than a running interface or an editable layout file.
Editing adds a source image to the instruction. Stored image references in the producer workflow must be fully uploaded and use PNG, JPEG or WebP. Name the change and what should be preserved: a new background, a different material, a focused style transformation or a corrected caption. When several references contribute to a composition, describe their roles separately, such as the product from one picture and the brand look from another. Keep the original product reference available so later revisions do not lose the identity established in the first asset.
A practical sequence can begin with a product rendering and then place that same visual into a different setting or a printed composition. Use the selected output as the next edit’s input and keep the new instruction focused on the transformation. For a campaign variation, retain the successful subject and hierarchy while changing the environment or supporting copy. This develops an image through explicit stages rather than expecting a later prompt to remember an earlier asset that was not supplied.
Typography and fine textures are part of the Quality model’s creative focus. Provide exact words, numerals and placement for a menu, label or advertisement, and describe how the text should fit the material or composition. Inspect spelling, reading order and small lettering at the actual display size. A realistic texture can support a product’s visual presentation, while the factual product attributes still need to come from the approved brief and references.
The producer image workflow supports 1K and 2K resolution choices and landscape, square or portrait compositions, with automatic aspect selection when none is specified. Choose the image shape around the subject and copy placement instead of treating resolution as a substitute for layout. Multiple alternatives can be requested through the common image-generation count setting, which ranges from one to ten and defaults to one. Comparing alternatives is useful for a composition choice; it does not establish that every requested detail is present in each result.
Images are normally returned through temporary hosted locations, with base64 delivery available when the image needs to be included directly in an application artifact. Retain the actual selected asset rather than relying on a temporary location as the project’s only copy. The producer’s image-file integration also demonstrates using stored image identifiers as references and storing generated image files for later use. These delivery and storage choices are separate from the visual brief that determines what the image should depict.
The named Image Quality model is distinct from Grok Imagine Image 2.0’s low, medium and auto quality parameter. Those later quality controls and expanded reference or aspect-ratio choices should not be treated as settings of this profile. Requesting several alternatives in one image call is also different from the manufacturer’s Batch API, which the exact Quality model page does not list as supported. Keep the image’s model choice, prompt, references and selected output connected when preparing a repeatable workflow.
For a useful finished image, compare the requested scene, product details, typography and preserved elements with the brief, then revise the specific part that missed the goal. A generated still can become a reference for a separate video task, but the image model’s own artifact remains an image. Preserve the successful version and the reference material so a later campaign edit or placement change can refine the same creative direction.
", "aboutText": "Grok Imagine Image Quality is SpaceXAI’s named image generation and editing model with an emphasis on realistic detail, stronger text rendering and close following of a creative brief. It accepts text and optional image references and returns an image. Its use cases include product visualisation, campaign creative, social assets, illustrations and UI-style icons, with a style range that includes photographic and cinematic imagery as well as graphic artwork.\n\nFor a product scene, describe the object, arrangement, material, lighting and camera view before adding decorative style. Supply a reference when the product’s shape or lettering needs to remain recognisable. A useful brief can place a small labelled bottle on a stone surface with a defined palette and space for a heading. For an icon or graphic, state the shape, contrast and intended visual scale. The result is a rendered image rather than a running interface or an editable layout file.\n\nEditing adds a source image to the instruction. Stored image references in the producer workflow must be fully uploaded and use PNG, JPEG or WebP. Name the change and what should be preserved: a new background, a different material, a focused style transformation or a corrected caption. When several references contribute to a composition, describe their roles separately, such as the product from one picture and the brand look from another. Keep the original product reference available so later revisions do not lose the identity established in the first asset.\n\nA practical sequence can begin with a product rendering and then place that same visual into a different setting or a printed composition. Use the selected output as the next edit’s input and keep the new instruction focused on the transformation. For a campaign variation, retain the successful subject and hierarchy while changing the environment or supporting copy. This develops an image through explicit stages rather than expecting a later prompt to remember an earlier asset that was not supplied.\n\nTypography and fine textures are part of the Quality model’s creative focus. Provide exact words, numerals and placement for a menu, label or advertisement, and describe how the text should fit the material or composition. Inspect spelling, reading order and small lettering at the actual display size. A realistic texture can support a product’s visual presentation, while the factual product attributes still need to come from the approved brief and references.\n\nThe producer image workflow supports 1K and 2K resolution choices and landscape, square or portrait compositions, with automatic aspect selection when none is specified. Choose the image shape around the subject and copy placement instead of treating resolution as a substitute for layout. Multiple alternatives can be requested through the common image-generation count setting, which ranges from one to ten and defaults to one. Comparing alternatives is useful for a composition choice; it does not establish that every requested detail is present in each result.\n\nImages are normally returned through temporary hosted locations, with base64 delivery available when the image needs to be included directly in an application artifact. Retain the actual selected asset rather than relying on a temporary location as the project’s only copy. The producer’s image-file integration also demonstrates using stored image identifiers as references and storing generated image files for later use. These delivery and storage choices are separate from the visual brief that determines what the image should depict.\n\nThe named Image Quality model is distinct from Grok Imagine Image 2.0’s low, medium and auto quality parameter. Those later quality controls and expanded reference or aspect-ratio choices should not be treated as settings of this profile. Requesting several alternatives in one image call is also different from the manufacturer’s Batch API, which the exact Quality model page does not list as supported. Keep the image’s model choice, prompt, references and selected output connected when preparing a repeatable workflow.\n\nFor a useful finished image, compare the requested scene, product details, typography and preserved elements with the brief, then revise the specific part that missed the goal. A generated still can become a reference for a separate video task, but the image model’s own artifact remains an image. Preserve the successful version and the reference material so a later campaign edit or placement change can refine the same creative direction.", "editorialOverlay": { "copy_fields": null, "copy_sha256": null, "copy_source": null, "html_sha256": "73083e5c054c0d0ca27886703a60ef2bdd3416eec3f56bebf8e957805d0a528f", "module_sha256": "ee9dc1c50b1e6a8fb7fa062030fcb4646b9aaaeb08be513b723a5a92a7290f06", "raw_model_unchanged": true, "schema": "ailoot-native-model-editorial-v1" }, "locale": "en", "methods": [ { "html": "x-ai/grok-imagine-image-qualityGrok Imagine Image Quality generates and edits images with an emphasis on realism, text rendering and creative control. Use a precise text brief and optional references to develop product visuals, campaign assets, icons or a focused revision of an existing picture.
This description covers the model’s capabilities. Available in Ailoot inputs, outputs and options are listed for the selected method below.
Grok Imagine Image Quality is SpaceXAI’s named image generation and editing model with an emphasis on realistic detail, stronger text rendering and close following of a creative brief. It accepts text and optional image references and returns an image. Its use cases include product visualisation, campaign creative, social assets, illustrations and UI-style icons, with a style range that includes photographic and cinematic imagery as well as graphic artwork.
For a product scene, describe the object, arrangement, material, lighting and camera view before adding decorative style. Supply a reference when the product’s shape or lettering needs to remain recognisable. A useful brief can place a small labelled bottle on a stone surface with a defined palette and space for a heading. For an icon or graphic, state the shape, contrast and intended visual scale. The result is a rendered image rather than a running interface or an editable layout file.
Editing adds a source image to the instruction. Stored image references in the producer workflow must be fully uploaded and use PNG, JPEG or WebP. Name the change and what should be preserved: a new background, a different material, a focused style transformation or a corrected caption. When several references contribute to a composition, describe their roles separately, such as the product from one picture and the brand look from another. Keep the original product reference available so later revisions do not lose the identity established in the first asset.
A practical sequence can begin with a product rendering and then place that same visual into a different setting or a printed composition. Use the selected output as the next edit’s input and keep the new instruction focused on the transformation. For a campaign variation, retain the successful subject and hierarchy while changing the environment or supporting copy. This develops an image through explicit stages rather than expecting a later prompt to remember an earlier asset that was not supplied.
Typography and fine textures are part of the Quality model’s creative focus. Provide exact words, numerals and placement for a menu, label or advertisement, and describe how the text should fit the material or composition. Inspect spelling, reading order and small lettering at the actual display size. A realistic texture can support a product’s visual presentation, while the factual product attributes still need to come from the approved brief and references.
The producer image workflow supports 1K and 2K resolution choices and landscape, square or portrait compositions, with automatic aspect selection when none is specified. Choose the image shape around the subject and copy placement instead of treating resolution as a substitute for layout. Multiple alternatives can be requested through the common image-generation count setting, which ranges from one to ten and defaults to one. Comparing alternatives is useful for a composition choice; it does not establish that every requested detail is present in each result.
Images are normally returned through temporary hosted locations, with base64 delivery available when the image needs to be included directly in an application artifact. Retain the actual selected asset rather than relying on a temporary location as the project’s only copy. The producer’s image-file integration also demonstrates using stored image identifiers as references and storing generated image files for later use. These delivery and storage choices are separate from the visual brief that determines what the image should depict.
The named Image Quality model is distinct from Grok Imagine Image 2.0’s low, medium and auto quality parameter. Those later quality controls and expanded reference or aspect-ratio choices should not be treated as settings of this profile. Requesting several alternatives in one image call is also different from the manufacturer’s Batch API, which the exact Quality model page does not list as supported. Keep the image’s model choice, prompt, references and selected output connected when preparing a repeatable workflow.
For a useful finished image, compare the requested scene, product details, typography and preserved elements with the brief, then revise the specific part that missed the goal. A generated still can become a reference for a separate video task, but the image model’s own artifact remains an image. Preserve the successful version and the reference material so a later campaign edit or placement change can refine the same creative direction.
POST /v1/images/generationstext, imageimage| Field | Type | Requirement | Values & limits | Default |
|---|---|---|---|---|
Fieldmodel | Typestring | RequirementRequired | Values & limits x-ai/grok-imagine-image-quality | Default— |
Fieldprompt | Typestring | RequirementRequired | Values & limits Minimum length: 1 | Default— |
Fieldresolution | Typestring | RequirementOptional | Values & limits 1K, 2K | Default— |
Fieldaspect_ratio | Typestring | RequirementOptional | Values & limits 1:1, 3:4, 4:3, 9:16, 16:9, 2:3, 3:2, 9:19.5, 19.5:9, 9:20, 20:9, 1:2, 2:1, auto | Default— |
Fieldn | Typeinteger | RequirementOptional | Values & limits Minimum: 1 Maximum: 1 | Default— |
Fieldinput_references | Typearray | RequirementOptional | Values & limits Minimum items: 0 Maximum items: 3 | Default— |
Fieldprovider | Typeobject | RequirementOptional | Values & limits | Default— |
| Parameter | Contract |
|---|---|
Parametercontent_type | Contractapplication/json |
Parameterrequired | Contractmodel, prompt |
Parametermaterial_types | Contracttext, image |
Lifecycle: synchronous_result_then_owned_library
GET /v1/media/tasks/{task_id} · actual returned task_id or media library record
GET /v1/media/assets/{asset_id}/content
GET /v1/media/assets
GET /v1/media/assets/{asset_id}
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.
Tariff references do not add request options. Supported parameters are listed for the selected method.
Match each charge to the conditions shown. Use one rate for each set of alternative configurations.
| Configuration | Rate schedule | Forecast quantity | Billing unit | Charge |
|---|---|---|---|---|
| ConfigurationBase token rates | Rate scheduleBase rate | Forecast quantity— | Billing unit— | Charge Input · Input tokens · Estimate for comparison only — / 1K tokens Output · Output tokens · Estimate for comparison only — / 1K tokens Input · Cache read · Estimate for comparison only — / 1K tokens Input · Cache write · Estimate for comparison only — / 1K tokens Input · Cache write, 1 hour · Estimate for comparison only — / 1K tokens |
| Configurationinput image | Rate schedule— | Forecast quantity— | Billing unitper input image | Charge Input · input image · Estimate for comparison only $0.02 per input image |
| ConfigurationEstimated generation cost | Rate schedule— | Forecast quantityone generation estimate | Billing unit— | Charge Output · Estimated generation cost · Estimate for comparison only $0.1 estimate before generation This estimate is not an additional charge or a fixed rate for the completed generation. |
Ailoot reserves an estimated amount before a request. After the result, it settles the final charge from measured usage. Streaming settlement uses the final usage record. How reservation and settlement work →
set -eu\n: "${AILOOT_API_KEY:?Set your Ailoot API key}"\nexport AILOOT_API_KEY\npython3 - <<'PY_REQUEST'\nimport json,os\nfrom pathlib import Path\np={'model': 'x-ai/grok-imagine-image-quality', '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\nDownload each returned image or save its Base64 contents
GET /v1/media/tasks/{task_id}GET /v1/media/assets/{asset_id}/contentGET /v1/media/assetsGET /v1/media/assets/{asset_id}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.\nSave every completed image; retrieve each returned URL or decode its Base64 contents.
Retain the complete response and headers, every actual output, original returned identifiers and all usage fields. Recover the original operation without submitting creation again.
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.
| Field | Type |
|---|---|
Fieldcreated | Type |
Fielddata[].url | Type |
Fielddata[].b64_json | Type |
Fieldusage | Type |
Ailoot Ultra x-ai/grok-imagine-image-quality
/v1/images