{"id":467,"date":"2026-06-25T06:08:55","date_gmt":"2026-06-25T06:08:55","guid":{"rendered":"https:\/\/a3bees.com\/blog\/?p=467"},"modified":"2026-06-25T06:38:45","modified_gmt":"2026-06-25T06:38:45","slug":"vision-language-models-explained-2026","status":"publish","type":"post","link":"https:\/\/a3bees.com\/blog\/vision-language-models-explained-2026\/","title":{"rendered":"Vision-Language Models Explained: How GPT-4o and Gemini See the World"},"content":{"rendered":"\n<p class=\"wp-block-paragraph\">Imagine uploading a photo of a damaged car and asking AI, <em>&#8220;What parts need replacing?&#8221;<\/em> Within seconds, the AI identifies the damaged bumper, estimates repair areas, and even explains the likely impact. Or imagine taking a picture of a restaurant menu written in another language and receiving an instant translation along with meal recommendations.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">This is the power of <strong>Vision-Language Models (VLMs)<\/strong>.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Unlike traditional AI systems that process either text or images independently, Vision-Language Models understand both simultaneously. They can analyze photographs, diagrams, documents, screenshots, charts, handwritten notes, and even complex scenes while responding naturally in human language.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">The demand for <a href=\"https:\/\/a3bees.com\/services\/business-automation\"><strong>multimodal AI<\/strong><\/a> is growing rapidly. Industry reports estimate the Vision-Language Model market will expand significantly over the next decade as businesses adopt AI-powered document understanding, healthcare imaging, autonomous vehicles, intelligent search, and accessibility solutions. Today, leading models like <strong>GPT-4o<\/strong>, <strong>Gemini 2.5 Pro<\/strong>, <strong>Claude<\/strong>, <strong>Qwen3-VL<\/strong>, and <strong>InternVL3<\/strong> are redefining how machines perceive and interpret the visual world.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">In this comprehensive guide, you&#8217;ll learn:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>What Vision-Language Models are<\/li>\n\n\n\n<li>How they work behind the scenes<\/li>\n\n\n\n<li>Why they&#8217;re different from traditional LLMs<\/li>\n\n\n\n<li>The best VLMs available in 2026<\/li>\n\n\n\n<li>Real-world business applications<\/li>\n\n\n\n<li>Future trends shaping multimodal AI<\/li>\n<\/ul>\n\n\n\n<h2 class=\"wp-block-heading\">Key Takeaways<\/h2>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Vision-Language Models combine image understanding with natural language processing.<\/li>\n\n\n\n<li>GPT-4o and Gemini can analyze images, charts, documents, and screenshots while answering complex questions.<\/li>\n\n\n\n<li>Modern VLMs use Vision Transformers and Large Language Models together.<\/li>\n\n\n\n<li>Businesses are using VLMs in healthcare, retail, education, manufacturing, accessibility, and document automation.<\/li>\n\n\n\n<li>Open-source models like Qwen3-VL and InternVL3 are becoming powerful alternatives to commercial AI.<\/li>\n<\/ul>\n\n\n\n<h2 class=\"wp-block-heading\">What Are Vision-Language Models?<\/h2>\n\n\n\n<figure class=\"wp-block-image size-large\"><img loading=\"lazy\" decoding=\"async\" width=\"1024\" height=\"683\" src=\"https:\/\/a3bees.com\/blog\/wp-content\/uploads\/2026\/06\/vision-1024x683.webp\" alt=\"Vision-Language Models\" class=\"wp-image-468\" srcset=\"https:\/\/a3bees.com\/blog\/wp-content\/uploads\/2026\/06\/vision-1024x683.webp 1024w, https:\/\/a3bees.com\/blog\/wp-content\/uploads\/2026\/06\/vision-300x200.webp 300w, https:\/\/a3bees.com\/blog\/wp-content\/uploads\/2026\/06\/vision-768x512.webp 768w, https:\/\/a3bees.com\/blog\/wp-content\/uploads\/2026\/06\/vision.webp 1536w\" sizes=\"auto, (max-width: 1024px) 100vw, 1024px\" \/><\/figure>\n\n\n\n<p class=\"wp-block-paragraph\">A <strong>Vision-Language Model (VLM)<\/strong> is an artificial intelligence system that understands both images and text within a single model.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Think of a human looking at a photograph while answering questions about it. A VLM works similarly. It &#8220;sees&#8221; the image, understands its content, and combines that understanding with language to generate intelligent responses.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">For example, if you upload a picture of your living room and ask:<\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><em>&#8220;Which wall color would match my furniture?&#8221;<\/em><\/p>\n\n\n\n<p class=\"wp-block-paragraph\">A Vision-Language Model can identify the furniture, lighting conditions, wall layout, decorative style, and recommend suitable colors.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Unlike traditional image recognition software that simply labels objects, VLMs understand relationships, context, and intent.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">They don&#8217;t just recognize a chair.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">They understand:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>where the chair is<\/li>\n\n\n\n<li>what material it&#8217;s made from<\/li>\n\n\n\n<li>how it relates to surrounding furniture<\/li>\n\n\n\n<li>whether it matches the room&#8217;s interior style<\/li>\n<\/ul>\n\n\n\n<p class=\"wp-block-paragraph\">This contextual understanding makes VLMs far more powerful than earlier computer vision systems.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\">Traditional AI vs Vision-Language Models<\/h2>\n\n\n\n<figure class=\"wp-block-image size-large\"><img loading=\"lazy\" decoding=\"async\" width=\"1024\" height=\"683\" src=\"https:\/\/a3bees.com\/blog\/wp-content\/uploads\/2026\/06\/Ai-vs-Vision-1024x683.webp\" alt=\"Traditional AI Vs Vision-Language Models\" class=\"wp-image-471\" srcset=\"https:\/\/a3bees.com\/blog\/wp-content\/uploads\/2026\/06\/Ai-vs-Vision-1024x683.webp 1024w, https:\/\/a3bees.com\/blog\/wp-content\/uploads\/2026\/06\/Ai-vs-Vision-300x200.webp 300w, https:\/\/a3bees.com\/blog\/wp-content\/uploads\/2026\/06\/Ai-vs-Vision-768x512.webp 768w, https:\/\/a3bees.com\/blog\/wp-content\/uploads\/2026\/06\/Ai-vs-Vision.webp 1536w\" sizes=\"auto, (max-width: 1024px) 100vw, 1024px\" \/><\/figure>\n\n\n\n<p class=\"wp-block-paragraph\">Earlier AI systems specialized in only one type of information.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">A <a href=\"https:\/\/a3bees.com\/services\/chatbot-virtual-assistant\"><strong>chatbot<\/strong><\/a> could answer text questions but couldn&#8217;t understand photographs.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">An image recognition system could identify objects but couldn&#8217;t explain what it saw.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Vision-Language Models combine both abilities.<\/p>\n\n\n\n<figure class=\"wp-block-table\"><table class=\"has-fixed-layout\"><tbody><tr><td><strong>Traditional AI<\/strong><\/td><td><strong>Vision-Language Models<\/strong><\/td><\/tr><tr><td>Understands text only<\/td><td>Understands text and images together<\/td><\/tr><tr><td>Limited context<\/td><td>Rich contextual understanding<\/td><\/tr><tr><td>Separate image models<\/td><td>Unified multimodal reasoning<\/td><\/tr><tr><td>Object recognition<\/td><td>Scene understanding<\/td><\/tr><tr><td>Cannot answer visual questions<\/td><td>Can explain images naturally<\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n<p class=\"wp-block-paragraph\">Think of traditional AI as someone who only speaks one language.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">A Vision-Language Model is like someone fluent in multiple languages who can also interpret maps, charts, photographs, and handwritten notes.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\">How Do Vision-Language Models Work?<\/h2>\n\n\n\n<p class=\"wp-block-paragraph\">Although the underlying technology is complex, the basic workflow is surprisingly simple.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\">Step 1: Breaking the Image into Small Patches<\/h3>\n\n\n\n<p class=\"wp-block-paragraph\">Instead of analyzing an entire image at once, the AI divides it into hundreds of tiny squares called <strong>patches<\/strong>.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Imagine cutting a large photograph into puzzle pieces.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Each piece contains small amounts of visual information.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">This allows the model to study every part individually.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Modern Vision Transformers (ViTs) use this approach because it captures both local details and global context.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\">Step 2: Converting Images into Numbers<\/h3>\n\n\n\n<p class=\"wp-block-paragraph\">Computers don&#8217;t understand photographs directly.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Each image patch is converted into numerical representations known as <strong>embeddings<\/strong>.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">These embeddings describe:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>color<\/li>\n\n\n\n<li>texture<\/li>\n\n\n\n<li>edges<\/li>\n\n\n\n<li>shapes<\/li>\n\n\n\n<li>patterns<\/li>\n<\/ul>\n\n\n\n<p class=\"wp-block-paragraph\">Think of this as translating a painting into a language computers understand.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\">Step 3: Combining Vision with Language<\/h3>\n\n\n\n<p class=\"wp-block-paragraph\">Once visual information becomes numerical data, it is passed to the language model.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">The language model combines:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>image understanding<\/li>\n\n\n\n<li>user question<\/li>\n\n\n\n<li>previous conversation<\/li>\n\n\n\n<li>contextual reasoning<\/li>\n<\/ul>\n\n\n\n<p class=\"wp-block-paragraph\">It then generates a meaningful response.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">This is why GPT-4o can answer questions like:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>&#8220;What does this chart show?&#8221;<\/li>\n\n\n\n<li>&#8220;Summarize this invoice.&#8221;<\/li>\n\n\n\n<li>&#8220;Is this plant healthy?&#8221;<\/li>\n\n\n\n<li>&#8220;Describe this medical scan.&#8221;<\/li>\n<\/ul>\n\n\n\n<p class=\"wp-block-paragraph\">The vision encoder acts as the AI&#8217;s eyes.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">The language model acts as its brain.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Together, they create a system capable of understanding the visual world almost like humans do.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\">Top Vision-Language Models in 2026<\/h2>\n\n\n\n<figure class=\"wp-block-table\"><table class=\"has-fixed-layout\"><tbody><tr><td><strong>Model<\/strong><\/td><td><strong>Best For<\/strong><\/td><td><strong>Open Source<\/strong><\/td><\/tr><tr><td>GPT-4o<\/td><td>Image conversations, documents, charts<\/td><td>No<\/td><\/tr><tr><td>Gemini 2.5 Pro<\/td><td>Video, coding, reasoning<\/td><td>No<\/td><\/tr><tr><td>Claude 3.5 Sonnet<\/td><td>Documents and long reports<\/td><td>No<\/td><\/tr><tr><td>Qwen3-VL<\/td><td>Research and development<\/td><td>Yes<\/td><\/tr><tr><td>InternVL3<\/td><td>Industrial AI applications<\/td><td>Yes<\/td><\/tr><tr><td>LLaVA<\/td><td>Learning and experimentation<\/td><td>Yes<\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n<h3 class=\"wp-block-heading\">GPT-4o<\/h3>\n\n\n\n<p class=\"wp-block-paragraph\">GPT-4o provides one of the most natural multimodal experiences available today. It excels at understanding images, interpreting documents, explaining charts, solving visual reasoning tasks, and maintaining conversational context.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\">Gemini 2.5 Pro<\/h3>\n\n\n\n<p class=\"wp-block-paragraph\">Gemini performs exceptionally well in video understanding, coding, scientific reasoning, and multimodal search. It is widely used for enterprise productivity and research.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\">Claude<\/h3>\n\n\n\n<p class=\"wp-block-paragraph\">Claude is particularly effective at analyzing lengthy documents, PDFs, technical diagrams, and structured reports while maintaining strong reasoning capabilities.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\">Qwen3-VL<\/h3>\n\n\n\n<p class=\"wp-block-paragraph\">Alibaba&#8217;s Qwen3-VL is among the strongest open-source Vision-Language Models available today, making it attractive for developers building custom AI solutions.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\">Real-World Applications of Vision-Language Models<\/h2>\n\n\n\n<h3 class=\"wp-block-heading\">Healthcare<\/h3>\n\n\n\n<p class=\"wp-block-paragraph\">Doctors use Vision-Language Models to analyze X-rays, MRI scans, pathology images, and medical reports. AI assists specialists by highlighting abnormalities and generating preliminary observations.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\">Retail &amp; E-commerce<\/h3>\n\n\n\n<p class=\"wp-block-paragraph\">Customers can upload product photos and instantly find visually similar products, compare prices, and receive personalized recommendations.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\">Self-Driving Vehicles<\/h3>\n\n\n\n<p class=\"wp-block-paragraph\">Autonomous vehicles continuously interpret:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>road signs<\/li>\n\n\n\n<li>traffic lights<\/li>\n\n\n\n<li>pedestrians<\/li>\n\n\n\n<li>lane markings<\/li>\n\n\n\n<li>road hazards<\/li>\n<\/ul>\n\n\n\n<p class=\"wp-block-paragraph\">using multimodal AI.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\">Accessibility<\/h3>\n\n\n\n<p class=\"wp-block-paragraph\">Vision-Language Models help visually impaired users by describing scenes, reading documents aloud, identifying products, and explaining surroundings in natural language.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\">Business Document Automation<\/h3>\n\n\n\n<p class=\"wp-block-paragraph\">Organizations use VLMs to extract information from:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>invoices<\/li>\n\n\n\n<li>contracts<\/li>\n\n\n\n<li>receipts<\/li>\n\n\n\n<li>financial reports<\/li>\n\n\n\n<li>insurance documents<\/li>\n<\/ul>\n\n\n\n<p class=\"wp-block-paragraph\">This significantly reduces manual data entry and improves operational efficiency.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\">Education<\/h3>\n\n\n\n<p class=\"wp-block-paragraph\">Students upload handwritten notes, mathematical equations, engineering diagrams, and scientific illustrations to receive personalized explanations.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\">How Are Vision-Language Models Trained?<\/h2>\n\n\n\n<figure class=\"wp-block-image size-large\"><img loading=\"lazy\" decoding=\"async\" width=\"1024\" height=\"683\" src=\"https:\/\/a3bees.com\/blog\/wp-content\/uploads\/2026\/06\/trained-1024x683.webp\" alt=\"Vision-Language Models Trained\" class=\"wp-image-473\" srcset=\"https:\/\/a3bees.com\/blog\/wp-content\/uploads\/2026\/06\/trained-1024x683.webp 1024w, https:\/\/a3bees.com\/blog\/wp-content\/uploads\/2026\/06\/trained-300x200.webp 300w, https:\/\/a3bees.com\/blog\/wp-content\/uploads\/2026\/06\/trained-768x512.webp 768w, https:\/\/a3bees.com\/blog\/wp-content\/uploads\/2026\/06\/trained.webp 1536w\" sizes=\"auto, (max-width: 1024px) 100vw, 1024px\" \/><\/figure>\n\n\n\n<p class=\"wp-block-paragraph\">Training a VLM typically involves two stages.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\">Pre-training<\/h3>\n\n\n\n<p class=\"wp-block-paragraph\">The model learns from millions\u2014or even billions\u2014of image-text pairs collected from diverse sources.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">This helps it understand how visual objects relate to language.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\">Fine-Tuning<\/h3>\n\n\n\n<p class=\"wp-block-paragraph\">The model is then optimized for specific tasks, such as:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>medical diagnosis<\/li>\n\n\n\n<li>legal document analysis<\/li>\n\n\n\n<li>product search<\/li>\n\n\n\n<li>visual question answering<\/li>\n\n\n\n<li>robotics<\/li>\n<\/ul>\n\n\n\n<p class=\"wp-block-paragraph\">This specialization dramatically improves performance in industry-specific applications.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\">Future of Vision-Language Models<\/h2>\n\n\n\n<p class=\"wp-block-paragraph\">The next generation of VLMs will become even more capable.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Future developments include:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Real-time video understanding<\/li>\n\n\n\n<li>AI agents capable of taking actions<\/li>\n\n\n\n<li>On-device multimodal AI<\/li>\n\n\n\n<li>Smarter robotics<\/li>\n\n\n\n<li>Better multilingual reasoning<\/li>\n\n\n\n<li>Improved scientific research assistants<\/li>\n\n\n\n<li>Enterprise workflow automation<\/li>\n<\/ul>\n\n\n\n<p class=\"wp-block-paragraph\">As computing power increases, Vision-Language Models will move beyond understanding information to actively assisting users in completing complex tasks.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\">Conclusion<\/h2>\n\n\n\n<p class=\"wp-block-paragraph\">Vision-Language Models represent one of the biggest advancements in artificial intelligence. By combining computer vision with natural language understanding, they enable AI systems to interpret images, documents, videos, and real-world environments more naturally than ever before.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Whether you&#8217;re using GPT-4o to analyze charts, Gemini to understand videos, or Qwen3-VL to build custom AI applications, Vision-Language Models are transforming how humans interact with machines.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">As multimodal AI continues to evolve, organizations that embrace Vision-Language Models today will be better positioned to automate workflows, improve customer experiences, and unlock new opportunities across industries.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\">Frequently Asked Questions<\/h2>\n\n\n\n<h3 class=\"wp-block-heading\">1. What is a Vision-Language Model?<\/h3>\n\n\n\n<p class=\"wp-block-paragraph\">A Vision-Language Model (VLM) is an AI model that understands both images and text simultaneously, allowing it to answer questions about visual content.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\">2. How does GPT-4o understand images?<\/h3>\n\n\n\n<p class=\"wp-block-paragraph\">GPT-4o converts images into numerical representations using a vision encoder before combining them with language understanding to generate responses.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\">3. What is the difference between a VLM and an LLM?<\/h3>\n\n\n\n<p class=\"wp-block-paragraph\">A Large Language Model processes only text, while a Vision-Language Model processes both images and text together.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\">4. Can Gemini understand images?<\/h3>\n\n\n\n<p class=\"wp-block-paragraph\">Yes. Gemini can analyze images, videos, diagrams, screenshots, and documents while answering complex questions in natural language.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\">5. Which is the best open-source Vision-Language Model?<\/h3>\n\n\n\n<p class=\"wp-block-paragraph\">Qwen3-VL and InternVL3 are among the strongest open-source Vision-Language Models available in 2026.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\">6. What industries use Vision-Language Models?<\/h3>\n\n\n\n<p class=\"wp-block-paragraph\">Healthcare, finance, manufacturing, retail, education, autonomous vehicles, accessibility technology, legal services, and enterprise automation all benefit from Vision-Language Models.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Imagine uploading a photo of a damaged car and asking AI, &#8220;What parts need replacing?&#8221; Within seconds, the AI identifies the damaged bumper, estimates repair areas, and even explains the likely impact. Or imagine taking a picture of a restaurant menu written in another language and receiving an instant translation along with meal recommendations. This [&hellip;]<\/p>\n","protected":false},"author":1,"featured_media":469,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[1],"tags":[],"class_list":["post-467","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-uncategorized"],"_links":{"self":[{"href":"https:\/\/a3bees.com\/blog\/wp-json\/wp\/v2\/posts\/467","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/a3bees.com\/blog\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/a3bees.com\/blog\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/a3bees.com\/blog\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/a3bees.com\/blog\/wp-json\/wp\/v2\/comments?post=467"}],"version-history":[{"count":3,"href":"https:\/\/a3bees.com\/blog\/wp-json\/wp\/v2\/posts\/467\/revisions"}],"predecessor-version":[{"id":474,"href":"https:\/\/a3bees.com\/blog\/wp-json\/wp\/v2\/posts\/467\/revisions\/474"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/a3bees.com\/blog\/wp-json\/wp\/v2\/media\/469"}],"wp:attachment":[{"href":"https:\/\/a3bees.com\/blog\/wp-json\/wp\/v2\/media?parent=467"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/a3bees.com\/blog\/wp-json\/wp\/v2\/categories?post=467"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/a3bees.com\/blog\/wp-json\/wp\/v2\/tags?post=467"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}