{"id":3007,"date":"2026-09-10T05:31:56","date_gmt":"2026-09-10T05:31:56","guid":{"rendered":"https:\/\/dmarketertayeeb.com\/blog\/chatgpt-images-2-5-marketers-workflow\/"},"modified":"2026-09-10T05:37:03","modified_gmt":"2026-09-10T05:37:03","slug":"chatgpt-images-2-5-marketers-workflow","status":"publish","type":"post","link":"https:\/\/dmarketertayeeb.com\/blog\/chatgpt-images-2-5-marketers-workflow\/","title":{"rendered":"ChatGPT Images 2.5 for Marketers: Flare vs Sunburst, Workflow and Cost Checks"},"content":{"rendered":"\n<p><strong>Short answer:<\/strong> ChatGPT Images 2.5 is most useful to marketers when it is treated as a controlled creative workflow, not as a promise of one-click, publish-ready advertising. Use the ChatGPT interface for fast briefs, references and edits; choose between the API&#8217;s <strong>Flare<\/strong> and <strong>Sunburst<\/strong> models only after you know whether your priority is faster everyday generation or more demanding editing. In both cases, keep a human approval gate for product facts, brand rules, rights, accessibility and channel requirements.<\/p>\n\n\n\n<p>OpenAI announced ChatGPT Images 2.5 on 8 September 2026. Its launch page describes a broad rollout across ChatGPT, Work and Codex on web, desktop and mobile, plus new creative features such as Sketch, templates, comments and prompt sharing. The API model catalogue separates the faster GPT-Image-2.5 Flare from the more editing-focused GPT-Image-2.5 Sunburst. Those are useful starting positions, not a universal quality ranking. The practical question is narrower: which route can produce an approved asset for your brief with the least avoidable rework?<\/p>\n\n\n\n<div class=\"wp-block-group dmt-fact-box\"><div class=\"wp-block-group__inner-container is-layout-flow wp-block-group-is-layout-flow\">\n<h2 class=\"wp-block-heading\">ChatGPT Images 2.5 at a glance<\/h2>\n\n\n<ul class=\"wp-block-list\"><li><strong>Product:<\/strong> ChatGPT Images 2.5, announced by OpenAI on 8 September 2026.<\/li><li><strong>Interface:<\/strong> OpenAI describes Sketch, templates, comments and prompt sharing alongside image creation and editing.<\/li><li><strong>API choice:<\/strong> GPT-Image-2.5 Flare is positioned for faster everyday generation; GPT-Image-2.5 Sunburst is positioned for more capable editing.<\/li><li><strong>Pricing unit:<\/strong> The API is priced by text tokens, image-input tokens and output tokens. There is no honest universal \u201ccost per image\u201d without the request&#8217;s actual token usage.<\/li><li><strong>Approval rule:<\/strong> Generated output still needs human review for claims, rights, brand fit, accessibility, disclosure and final channel specifications.<\/li><\/ul>\n<\/div><\/div>\n\n\n\n<h2 class=\"wp-block-heading\">What changed, and what the announcement does not prove<\/h2>\n\n\n\n<p>OpenAI says ChatGPT Images 2.5 can create and edit images with sharper results, more precise changes and faster generation than the previous Images 2.0 system. The product announcement also reports more than three billion images generated per week across ChatGPT Images and the GPT-Image API, and says latency can be up to 50% lower than Images 2.0. These are OpenAI&#8217;s product claims, not a DMT benchmark or a guarantee for a particular prompt, account, image size or workflow. Read the <a href=\"https:\/\/openai.com\/index\/introducing-chatgpt-images-2-5\/\">OpenAI launch announcement<\/a> for the dated product description.<\/p>\n\n\n\n<p>The current <a href=\"https:\/\/help.openai.com\/en\/articles\/11084440-im\">ChatGPT Images help page<\/a> is the better reference for the user-facing experience and availability. The <a href=\"https:\/\/developers.openai.com\/api\/docs\/models\">developer model catalogue<\/a> is the better reference for API model identity and current model documentation. Keeping those sources separate prevents a common mistake: assuming a feature visible in the ChatGPT interface automatically has the same controls, limits or output behaviour in an API integration.<\/p>\n\n\n\n<p>For a marketing team, the meaningful change is therefore not \u201cAI can make pictures.\u201d It is that the same product family now supports a more explicit choice between exploratory interface work and repeatable API work. That choice affects briefs, approvals, logging, cost controls and who is responsible for the final asset.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\">ChatGPT interface or API: choose by workflow<\/h2>\n\n\n\n<p>Start in the interface when a person is still deciding what the asset should communicate. Start with the API when the brief is stable enough to express as inputs, checks and an output contract. Many teams should use both: the interface for exploration and the API for a small, approved production path.<\/p>\n\n\n\n<figure class=\"wp-block-table\"><table><thead><tr><th>Decision<\/th><th>ChatGPT interface<\/th><th>API workflow<\/th><\/tr><\/thead><tbody><tr><td><strong>Best starting point<\/strong><\/td><td>Exploring a concept, editing a reference, or getting stakeholder feedback on direction<\/td><td>Generating repeatable variants after the brief, inputs and review rules are stable<\/td><\/tr><tr><td><strong>Useful strengths<\/strong><\/td><td>Fast conversation, visual iteration, templates, comments and shared prompts<\/td><td>Model selection, application integration, logging, repeatability and controlled batch work<\/td><\/tr><tr><td><strong>Main risk<\/strong><\/td><td>A useful-looking image is mistaken for an approved advertising asset<\/td><td>Automation scales a weak brief, unreviewed claims or an expensive revision loop<\/td><\/tr><tr><td><strong>Approval owner<\/strong><\/td><td>Named marketer or designer reviews the output before export<\/td><td>Named creative owner plus technical owner reviews inputs, output and usage record<\/td><\/tr><tr><td><strong>When to stop<\/strong><\/td><td>Stop iterating when the brief is approved or the output cannot meet a known constraint<\/td><td>Stop the test when cost per approved asset, quality or review time misses the preset threshold<\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n<p>This is a workflow decision, not a claim that one surface is \u201cbetter.\u201d If the team has not agreed on the audience, offer, product details, format or prohibited claims, a model comparison will produce noise. Fix the brief first.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\">Flare vs Sunburst: a decision matrix for marketers<\/h2>\n\n\n\n<p>The official model pages describe the two API choices differently. <strong>Flare<\/strong> is the faster everyday option; <strong>Sunburst<\/strong> is the more capable editing option. Treat that language as a routing hypothesis to verify on your own creative job. Do not turn it into a general leaderboard.<\/p>\n\n\n\n<figure class=\"wp-block-table\"><table><thead><tr><th>If the brief prioritises\u2026<\/th><th>Start with\u2026<\/th><th>Check before keeping the choice<\/th><\/tr><\/thead><tbody><tr><td>Many simple concepts, quick social variations or low-friction ideation<\/td><td><strong>Flare<\/strong><\/td><td>Prompt adherence, latency, rejected generations and the time a reviewer spends correcting each variant<\/td><\/tr><tr><td>Precise changes to an approved reference or a difficult edit<\/td><td><strong>Sunburst<\/strong><\/td><td>Whether the requested detail survives the edit without damaging product geometry, text, people or brand elements<\/td><\/tr><tr><td>Template-driven production at a known scale<\/td><td>Run a small paired test; do not decide from the model name<\/td><td>Cost per approved asset, revision count, output dimensions, failure reasons and approval time<\/td><\/tr><tr><td>Regulated, sensitive or high-value creative<\/td><td>Either model with a human-led review path<\/td><td>Claims, disclosures, likeness\/rights, accessibility and a recoverable source-asset record<\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n<p>Both official API pages document text and image input\/output and current model snapshots. They also publish quality controls and token rates. A model snapshot is a useful reproducibility field in an internal log; it is not proof that two snapshots will behave identically months later. Record it beside the brief and review result.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\">A marketing workflow that survives review<\/h2>\n\n\n\n<p>The safest useful workflow is deliberately ordinary. The model supplies visual variations; the team supplies the product truth, brand rules, rights decision and approval. The following sequence works whether the first pass happens in ChatGPT or through the API.<\/p>\n\n\n\n<ol class=\"wp-block-list\"><li><strong>Write the brief before opening the prompt box.<\/strong> Name the audience, offer, channel, aspect ratio, mandatory product details, approved claims, prohibited claims, palette, typography constraints and final reviewer.<\/li><li><strong>Use an approved reference.<\/strong> Provide the source product or pack shot when accuracy matters. Say what may change\u2014background, crop, lighting or composition\u2014and what must not change.<\/li><li><strong>Ask for one controlled variation.<\/strong> Change one meaningful variable at a time. A prompt that asks for a new product, a new scene, a new claim and six formats cannot produce an explainable test.<\/li><li><strong>Keep the original and the edit together.<\/strong> Save the source asset, prompt or request body, model\/snapshot, output and revision notes. A final image without its lineage is difficult to approve or reproduce.<\/li><li><strong>Run content and brand QA.<\/strong> Check product text, prices, colours, logos, faces, hands, layout, contrast, cropping and any small print. Do not accept a plausible-looking invented feature.<\/li><li><strong>Run rights and disclosure QA.<\/strong> Confirm permission for supplied images and people, check the channel&#8217;s disclosure rules, and preserve available provenance signals. Do not remove metadata or watermarks to make generated work look organic.<\/li><li><strong>Approve for one channel.<\/strong> A square social asset, a paid-ad placement and an ecommerce image have different constraints. Approve the exact export, not a vague promise that a later crop will be fine.<\/li><\/ol>\n\n\n\n<h3 class=\"wp-block-heading\">A brief the reviewer can actually grade<\/h3>\n\n\n\n<p>Use a short brief with explicit pass conditions:<\/p>\n\n\n\n<blockquote class=\"wp-block-quote is-layout-flow wp-block-quote-is-layout-flow\"><p><strong>Asset:<\/strong> 1:1 social image for a reusable water bottle launch.<br><strong>Audience:<\/strong> Urban commuters choosing a durable bottle.<br><strong>Must preserve:<\/strong> The supplied bottle shape, lid, logo placement and colour.<br><strong>Allowed changes:<\/strong> Neutral commuter setting, soft daylight and background composition.<br><strong>Must not invent:<\/strong> Capacity, certification, health claim, discount, warranty or material specification.<br><strong>Output:<\/strong> One controlled variant plus a short list of any visual detail requiring human verification.<br><strong>Reviewer:<\/strong> Brand owner before export.<\/p><\/blockquote>\n\n\n\n<p>That brief gives a reviewer something better than \u201clooks good\u201d to assess. The expected output is not merely an attractive image. It is an image that retains the approved product, avoids an unapproved claim, meets the channel format and arrives with enough information to explain what changed.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\">A small test beats a dramatic model comparison<\/h2>\n\n\n\n<p>The comparison below is a proposed test design, not a DMT-run benchmark. Use three to five representative briefs: a product hero, a background replacement, a social crop and one precise edit. Run the same input and approval rules through the chosen interface or API path. If you compare Flare and Sunburst, keep the brief, reference, output size, reviewer and acceptance rule constant.<\/p>\n\n\n\n<ol class=\"wp-block-list\"><li><strong>Freeze the input.<\/strong> Version the brief and reference assets before generating anything.<\/li><li><strong>Define pass\/fail.<\/strong> For example: product identity intact, no unsupported claim, required crop present, brand review passed and no critical edit defect.<\/li><li><strong>Record the request.<\/strong> Log model, snapshot, quality setting, input token counts, image-token counts, output token counts, latency and revision count where the surface exposes them.<\/li><li><strong>Have one reviewer score both routes.<\/strong> Record pass, minor correction, major rework, rejected or correctly escalated. A safe escalation is useful information, not a quality failure.<\/li><li><strong>Calculate cost per approved asset.<\/strong> Include rejected generations and meaningful reviewer time. A cheap first image that needs four corrections may be the expensive route.<\/li><li><strong>Set a stop rule.<\/strong> Stop when the route misses the quality threshold, spends beyond the test budget or fails a mandatory rights\/brand check. Do not keep generating until one image happens to work.<\/li><\/ol>\n\n\n\n<figure class=\"wp-block-table\"><table><thead><tr><th>Field to record<\/th><th>Why it matters<\/th><\/tr><\/thead><tbody><tr><td>Brief and reference version<\/td><td>Prevents a model change from being confused with an input change<\/td><\/tr><tr><td>Model and snapshot<\/td><td>Makes a later rerun explainable when the catalogue changes<\/td><\/tr><tr><td>Input, image-input and output tokens<\/td><td>Supports an actual cost calculation rather than a guessed per-image rate<\/td><\/tr><tr><td>Revision and rejection reason<\/td><td>Shows whether the route creates hidden review work<\/td><\/tr><tr><td>Approval outcome<\/td><td>Measures the deliverable the team needs: an approved asset<\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n<h2 class=\"wp-block-heading\">API cost: use token arithmetic, not a fixed cost per image<\/h2>\n\n\n\n<p>The current Flare and Sunburst model pages list the same broad token-rate structure: text input at <strong>$5 per million tokens<\/strong>, cached text input at <strong>$1.25 per million<\/strong>, image input at <strong>$8 per million<\/strong>, cached image input at <strong>$2 per million<\/strong> and output at <strong>$30 per million<\/strong>. Check the live model pages before budgeting because rates, snapshots and product surfaces can change.<\/p>\n\n\n\n<figure class=\"wp-block-table\"><table><thead><tr><th>Illustrative usage assumption<\/th><th>Rate<\/th><th>Arithmetic<\/th><th>Illustrative cost<\/th><\/tr><\/thead><tbody><tr><td>100,000 uncached text-input tokens<\/td><td>$5 \/ 1M<\/td><td>0.10 \u00d7 $5<\/td><td>$0.50<\/td><\/tr><tr><td>20,000 image-input tokens<\/td><td>$8 \/ 1M<\/td><td>0.02 \u00d7 $8<\/td><td>$0.16<\/td><\/tr><tr><td>5,000 output tokens<\/td><td>$30 \/ 1M<\/td><td>0.005 \u00d7 $30<\/td><td>$0.15<\/td><\/tr><tr><td><strong>Total before revisions<\/strong><\/td><td>\u2014<\/td><td>\u2014<\/td><td><strong>$0.81<\/strong><\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n<p>The $0.81 figure is an arithmetic illustration, not the price of a standard image and not a measured request. Replace every assumption with the usage returned by your actual request. If 80,000 of the text tokens are cached in a comparable request, the text-input component would be 0.08 \u00d7 $1.25 = $0.10; that still does not tell you how many image tokens or output tokens your image will use.<\/p>\n\n\n\n<p>The Sunburst documentation also notes that the calculator does not estimate GPT Image 2.5 token consumption. For planning, maintain a small worksheet with model snapshot, token fields, number of revisions and approved-asset count. The number worth comparing is <strong>total request cost plus meaningful review effort divided by approved assets<\/strong>. Do not report a universal per-image number from a single prompt.<\/p>\n\n\n\n<p>For a broader explanation of dated API rates, caching and budget assumptions, see DMT&#8217;s <a href=\"https:\/\/dmarketertayeeb.com\/blog\/gpt-6-astra-pricing-api-rates\">API budget-planning guide<\/a>. The model is different, but the discipline\u2014dated units, explicit assumptions and no hidden revision cost\u2014is the useful part.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\">Approval and brand-safety checklist<\/h2>\n\n\n\n<ul class=\"wp-block-list\"><li><strong>Product truth:<\/strong> Does the output show the supplied product, pack, UI or service accurately?<\/li><li><strong>Claim control:<\/strong> Did the model invent a price, result, certification, ingredient, feature or customer outcome?<\/li><li><strong>Brand fit:<\/strong> Are colour, logo, typography, composition and tone consistent with the current brief?<\/li><li><strong>Rights:<\/strong> Do you have permission to use supplied reference images, people, locations and third-party marks?<\/li><li><strong>Provenance:<\/strong> Have you retained the prompt\/request, reference, model snapshot and available content-provenance signals?<\/li><li><strong>Accessibility:<\/strong> Is the contrast adequate, is important information duplicated in text, and does the crop work without relying on tiny generated lettering?<\/li><li><strong>Channel rules:<\/strong> Does the final size, disclosure and wording meet the destination&#8217;s ad, social, ecommerce or email requirements?<\/li><li><strong>Accountability:<\/strong> Is one named person responsible for final approval and rollback if a defect is found later?<\/li><\/ul>\n\n\n\n<p>OpenAI describes safety measures including C2PA-related provenance and invisible watermarking in the product announcement. Those measures are useful signals, not a substitute for a rights review or an approval record. A provenance marker cannot make a false product claim true, and it does not transfer permission for an image of a person or a third-party asset.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\">How this fits a wider marketing stack<\/h2>\n\n\n\n<p>ChatGPT Images 2.5 is one component of a governed creative workflow, not a replacement for strategy or production ownership. DMT&#8217;s <a href=\"https:\/\/dmarketertayeeb.com\/blog\/chatgpt-for-digital-marketing-guide\">ChatGPT digital-marketing framework<\/a> is the useful parent for deciding where an image task belongs in a broader campaign. For a neighbouring multimodal API perspective, see the <a href=\"https:\/\/dmarketertayeeb.com\/blog\/meta-muse-spark-1-1-model-api-marketers\">Meta Muse API guide for marketers<\/a>. For a visual workflow that includes structured image inputs, the <a href=\"https:\/\/dmarketertayeeb.com\/blog\/vlm-run-gateway-marketers-ocr-visual-workflows\">VLM Run visual-AI workflow guide<\/a> covers a different but related problem.<\/p>\n\n\n\n<p>Teams planning a migration or vendor change should also read the <a href=\"https:\/\/dmarketertayeeb.com\/blog\/google-imagen-4-api-shutdown-migration\">Imagen API migration checklist<\/a>, especially its treatment of provenance and asset inventories. If generated images need to feed repeatable research, content or campaign work, DMT&#8217;s <a href=\"https:\/\/dmarketertayeeb.com\/blog\/gpt-6-astra-for-marketers\">marketer workflow guide for GPT-6 Astra<\/a> is the better link for orchestration decisions. These are adjacent owners, not evidence that the products are interchangeable.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\">What ChatGPT Images 2.5 does not prove<\/h2>\n\n\n\n<p>It does not prove that Images 2.5 will outperform every image model, that Flare is always cheaper, that Sunburst is always better, or that an API workflow will reduce total creative cost. It does not prove that a generated ad complies with a platform&#8217;s policy or that a visually accurate image contains accurate text. It does not prove that an OpenAI-reported usage or latency figure will appear in your account.<\/p>\n\n\n\n<p>Independent hands-on coverage can reveal useful interface changes. For example, TechRadar&#8217;s 24-hour test described an editing toolbar and actions such as background removal, erasing, resizing, markup, templates and comments. That is an anecdotal workflow observation, not a representative benchmark. Use it to form questions for your own test, not to promise a result.<\/p>\n\n\n\n<p>The strongest claim a marketing team can make after a controlled trial is local and measurable: \u201cThis route cleared our brief and approval rule at this recorded cost and review time.\u201d That is more useful than a general claim that an image model is revolutionary.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\">Frequently asked questions<\/h2>\n\n\n\n<h3 class=\"wp-block-heading\">Is ChatGPT Images 2.5 available to every ChatGPT user?<\/h3>\n\n\n\n<p>OpenAI&#8217;s current launch record describes a broad rollout across ChatGPT, Work and Codex on web, desktop and mobile, including ChatGPT tiers. Check the current product surface and workspace account before promising a particular control or API entitlement; UI availability and API model access are separate questions.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\">What is the difference between GPT-Image-2.5 Flare and Sunburst?<\/h3>\n\n\n\n<p>OpenAI positions Flare as the faster everyday model and Sunburst as the more capable editing model. Use those descriptions to choose a first test, then compare the models on the same approved brief, reference and pass\/fail criteria.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\">How much does one ChatGPT Images 2.5 API image cost?<\/h3>\n\n\n\n<p>There is no fixed universal cost per image. The API charges for text input, image input and output tokens, with different rates for cached input. Record the actual usage for your request, include revisions and divide total cost by approved assets rather than quoting a guessed unit price.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\">Can I publish generated images directly in an ad?<\/h3>\n\n\n\n<p>You can use a generated image only after your own rights, brand, claim, accessibility, disclosure and channel checks pass. A model&#8217;s safety or provenance features do not replace the advertiser&#8217;s approval responsibility.<\/p>\n\n\n\n<div class=\"wp-block-group dmt-author-note\"><div class=\"wp-block-group__inner-container is-layout-flow wp-block-group-is-layout-flow\">\n<h3 class=\"wp-block-heading\">Editorial note<\/h3>\n\n\n<p>This source-led guide was prepared for Digital Marketer Tayeeb from current OpenAI product and developer documentation, an independent hands-on report and a dated keyword-demand snapshot. It contains a proposed workflow and illustrative cost arithmetic, not an author-run benchmark. Product availability, model snapshots, pricing and platform controls can change; recheck the linked official pages before acting.<\/p>\n<\/div><\/div>\n\n\n\n<h2 class=\"wp-block-heading\">Sources<\/h2>\n\n\n\n<ul class=\"wp-block-list\"><li><a href=\"https:\/\/openai.com\/index\/introducing-chatgpt-images-2-5\/\">OpenAI: Introducing ChatGPT Images 2.5<\/a> \u2014 product announcement and vendor-reported capabilities.<\/li><li><a href=\"https:\/\/help.openai.com\/en\/articles\/11084440-im\">OpenAI Help: Images in ChatGPT<\/a> \u2014 current user-facing availability and feature reference.<\/li><li><a href=\"https:\/\/developers.openai.com\/api\/docs\/models\/gpt-image-2.5-flare\">OpenAI Developers: GPT-Image-2.5 Flare<\/a> \u2014 model identity, capabilities and token rates.<\/li><li><a href=\"https:\/\/developers.openai.com\/api\/docs\/models\/gpt-image-2.5-sunburst\">OpenAI Developers: GPT-Image-2.5 Sunburst<\/a> \u2014 model identity, editing position and token rates.<\/li><li><a href=\"https:\/\/developers.openai.com\/api\/docs\/models\">OpenAI Developers: Models<\/a> \u2014 current model catalogue context.<\/li><li><a href=\"https:\/\/www.techradar.com\/ai-platforms-assistants\/chatgpt\/chatgpt-images-2-5-is-out-ive-been-testing-it-for-24-hours-and-these-are-the-3-new-features-youll-actually-use\">TechRadar: ChatGPT Images 2.5 hands-on observations<\/a> \u2014 independent, anecdotal interface testing.<\/li><\/ul>\n\n\n\n<p><em>Last checked: 10 September 2026. Recheck official documentation for changes after this date.<\/em><\/p>\n","protected":false},"excerpt":{"rendered":"<p>A practical ChatGPT Images 2.5 guide for marketers: choose Flare or Sunburst, run a controlled creative test, calculate token costs, and approve outputs safely.<\/p>\n","protected":false},"author":1,"featured_media":3006,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[386,183,180],"tags":[427,250,194,292,319,428,422,421,296],"class_list":["post-3007","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-ai-for-marketers","category-ai-in-marketing","category-ai-news","tag-ai-disclosure","tag-ai-for-marketers","tag-ai-marketing","tag-ai-tools-for-marketers","tag-ai-workflows","tag-content-provenance","tag-marketing-operations","tag-multimodal-ai","tag-openai","has-featured-image"],"_links":{"self":[{"href":"https:\/\/dmarketertayeeb.com\/blog\/wp-json\/wp\/v2\/posts\/3007","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/dmarketertayeeb.com\/blog\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/dmarketertayeeb.com\/blog\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/dmarketertayeeb.com\/blog\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/dmarketertayeeb.com\/blog\/wp-json\/wp\/v2\/comments?post=3007"}],"version-history":[{"count":1,"href":"https:\/\/dmarketertayeeb.com\/blog\/wp-json\/wp\/v2\/posts\/3007\/revisions"}],"predecessor-version":[{"id":3008,"href":"https:\/\/dmarketertayeeb.com\/blog\/wp-json\/wp\/v2\/posts\/3007\/revisions\/3008"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/dmarketertayeeb.com\/blog\/wp-json\/wp\/v2\/media\/3006"}],"wp:attachment":[{"href":"https:\/\/dmarketertayeeb.com\/blog\/wp-json\/wp\/v2\/media?parent=3007"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/dmarketertayeeb.com\/blog\/wp-json\/wp\/v2\/categories?post=3007"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/dmarketertayeeb.com\/blog\/wp-json\/wp\/v2\/tags?post=3007"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}