[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"$ft4xQae-GWhP1mdTH82_7URduadTVDZNkc6kjycDrszM":3,"$fSbGUqcG0dZUmyMrQjMn_NRcrQ0brx1fkw46XZKwfAQ4":143,"$fpAUeNSCoIV_l2HdpZ7M3K4CEDXBCuvFQg_8dJsbBgzE":148},{"modelA":4,"modelB":23,"comparisons":40,"seoContent":48,"isGenerating":142},{"slug":5,"name":6,"provider":7,"category":8,"capabilities":9,"pricing":15,"badge":22},"flux-2","Flux 2","Black Forest Labs","image",[10,11,12,13,14],"Text-to-image","Image-to-image editing","LoRA fine-tuning support","Up to 4MP resolution","Style transfer",[16,19],{"label":17,"credits":18},"Standard (per image)",22,{"label":20,"credits":21},"Klein 9B (per image)",16,"New",{"slug":24,"name":25,"provider":26,"category":8,"capabilities":27,"pricing":31},"gpt-image-1-5","GPT-Image 1.5","OpenAI",[10,28,29,30],"Strong prompt adherence","High fidelity","Detailed scenes",[32,35,37],{"label":33,"credits":34},"low",8,{"label":36,"credits":21},"medium",{"label":38,"credits":39},"high",32,[41],{"id":42,"prompt":43,"modelAUrl":44,"modelBUrl":45,"mediaAStatus":46,"mediaBStatus":46,"mediaType":8,"status":46,"category":47},"cmlm4u8fq008yzjrqal2rcpi5","Hyperrealistic DSLR-quality photo of a 20s woman with shoulder-length wavy dark brown hair and minimal makeup, wearing an oversized gray hoodie and black leggings, holding her phone up for a mirror selfie while glancing slightly toward the camera with a relaxed half-smile. She’s in a slightly messy bedroom getting ready—open closet behind her, unmade bed, skincare bottles on a dresser—captured in soft natural window light with realistic skin texture, flyaway hairs, and subtle under-eye shadows. Candid “GRWM” vibe like an Instagram story, handheld framing with tiny motion blur and true-to-life indoor lighting.","https:\u002F\u002Finfluencer-studio.b-cdn.net\u002Fproduction\u002Fshowcase\u002F2ff880c7-4f41-4236-952c-f9b200028b70.jpg","https:\u002F\u002Finfluencer-studio.b-cdn.net\u002Fproduction\u002Fshowcase\u002Fd3168f13-6d6e-451d-9885-63545bfd302f.jpg","completed","photorealistic",{"metaTitle":49,"metaDescription":50,"introText":51,"modelAStrengths":52,"modelBStrengths":58,"verdict":64,"faqs":65,"shortAnswer":81,"bestForRows":82,"attributeScores":102,"whatExamplesShow":123,"methodology":134},"Flux 2 vs GPT-Image 1.5: Photorealistic Comparison","Compare Flux 2 and GPT-Image 1.5 for photorealistic images: fidelity, prompt adherence, editing, LoRA workflows, and credit costs.","\u003Cp>For photorealistic work—images that can pass as real camera captures—small differences in skin texture, lens behavior, lighting falloff, and background coherence matter. Flux 2 and GPT-Image 1.5 both target high-fidelity output, but they approach “photo-real” from different strengths: controllability and editing depth vs prompt-true generation.\u003C\u002Fp>\u003Cp>Below is a practical comparison focused on hyperrealistic results: how reliably each model produces believable people and products, how well it holds up under close inspection, and which workflows (editing, style transfer, LoRA, resolution) help you land consistent, photographic renders.\u003C\u002Fp>",[53,54,55,56,57],"LoRA support for consistent photoreal subjects, faces, and brand\u002Fproduct looks across a series","Versatile image-to-image editing for refining realism (lighting tweaks, background swaps, wardrobe\u002Fproduct changes) without restarting","Up to 4MP output for sharper “camera-like” detail and better crops for ads and social placements","Style transfer and face-swap support for controlled variations while keeping a realistic base","Flexible workflow for iterative realism: generate → edit → upscale\u002Fcrop → re-edit",[59,60,61,62,63],"Strong prompt adherence for photoreal briefs with many constraints (wardrobe, setting, lens cues, composition, props)","High-fidelity text-to-image output that can render detailed scenes with realistic materials and lighting","Good at producing coherent, story-like frames where multiple elements must match the prompt","Tiered quality\u002Fcredit options (low\u002Fmedium\u002Fhigh) to balance photoreal detail vs cost per image","Efficient for “one-shot” photoreal generations when you don’t need heavy post-editing","\u003Cp>If your definition of photorealistic includes \u003Cstrong>repeatability\u003C\u002Fstrong> (same person\u002Fproduct across many images) and \u003Cstrong>hands-on refinement\u003C\u002Fstrong> (surgical edits to make the render feel truly photographed), \u003Cstrong>Flux 2\u003C\u002Fstrong> is typically the stronger workflow thanks to LoRA support, image editing, and up to 4MP output.\u003C\u002Fp>\u003Cp>If you prioritize \u003Cstrong>prompt-accurate photoreal generation\u003C\u002Fstrong>—especially complex scenes with lots of specified details—and you want flexible spend levels per render, \u003Cstrong>GPT-Image 1.5\u003C\u002Fstrong> is a solid pick. Many teams use it for fast, prompt-true “hero frames,” then rely on an editing-centric model when continuity and micro-fixes become the priority.\u003C\u002Fp>",[66,69,72,75,78],{"question":67,"answer":68},"Which model looks more like a real photograph?","Both can achieve hyperrealistic results, but they excel differently. Flux 2 tends to shine when you iterate with image-to-image edits and need consistent realism across variations. GPT-Image 1.5 often excels at producing prompt-accurate photoreal frames in fewer attempts, especially for detailed scene descriptions.",{"question":70,"answer":71},"Which is better for photorealistic people and consistent faces?","Flux 2 is generally better suited for consistency because it supports LoRA workflows and includes face-swap support for controlled variations. GPT-Image 1.5 can generate realistic people, but it’s typically less “locked in” for the same identity across a long series without additional consistency tooling.",{"question":73,"answer":74},"How do they compare for photorealistic product shots and brand consistency?","Flux 2 is often the better fit when you need the same product look repeated across many images (angles, lighting setups, backgrounds) due to LoRA support and strong editing. GPT-Image 1.5 is effective for quickly generating diverse, prompt-accurate product concepts, especially when you’re exploring multiple directions.",{"question":76,"answer":77},"Which model is more cost-effective for photorealistic work?","It depends on the quality tier and iteration count. Flux 2 costs 22 credits per image (or 16 credits for the Klein 9B option) and can be efficient when editing reduces re-generation. GPT-Image 1.5 ranges from 8\u002F16\u002F32 credits (low\u002Fmedium\u002Fhigh), which can be cheaper for drafts but may require higher tiers or extra attempts for the most convincing photoreal detail.",{"question":79,"answer":80},"Which model is better for photorealistic edits (changing background, lighting, or details)?","Flux 2 is the clearer choice for photorealistic editing workflows because it supports image-to-image editing and style transfer, letting you preserve a realistic base while making targeted changes. GPT-Image 1.5 is primarily strongest as a generator with high prompt adherence rather than an edit-first tool.","Short answer: Flux 2 is better for style control & LoRA workflows, while GPT-Image 1.5 is better for accurate prompt adherence. If you are creating photorealistic, start with GPT-Image 1.5 because it costs fewer credits per output and lets you test more directions, then switch to Flux 2 for polished, higher-resolution final assets.",[83,86,90,93,96,99],{"need":84,"pick":25,"why":85},"Lower-cost exploration and more variants per credit","GPT-Image 1.5 costs 8 credits to start, so you can test more directions for less.",{"need":87,"pick":88,"why":89},"Polished, ready-to-ship final assets","Either model","Either model produces stronger final-asset polish for campaign-ready output.",{"need":91,"pick":25,"why":92},"Readable text in designs, overlays, and packaging","GPT-Image 1.5 renders labels and typography more cleanly.",{"need":94,"pick":6,"why":95},"Editing and reference-driven iteration","Flux 2 is more flexible for editing from references or existing outputs.",{"need":97,"pick":6,"why":98},"Consistent characters and repeated campaign visuals","Flux 2 holds character and style consistency better across outputs.",{"need":100,"pick":6,"why":101},"Photorealistic specifically","Flux 2 scores higher on realism, which matters most for photorealistic.",[103,107,111,115,117,119,121],{"criteria":104,"aScore":105,"bScore":105,"winner":106},"Realism",4,"tie",{"criteria":108,"aScore":109,"bScore":105,"winner":110},"Text accuracy",3,"B",{"criteria":112,"aScore":113,"bScore":109,"winner":114},"Editing flexibility",5,"A",{"criteria":116,"aScore":105,"bScore":109,"winner":114},"Cost efficiency",{"criteria":118,"aScore":105,"bScore":105,"winner":106},"Final polish",{"criteria":120,"aScore":113,"bScore":105,"winner":114},"Consistency",{"criteria":122,"aScore":105,"bScore":109,"winner":110},"Best first test",[124,126,128,131],{"label":104,"text":125},"Both models produce comparably natural results in these examples.",{"label":108,"text":127},"GPT-Image 1.5 renders any labels, overlays, or typography more cleanly.",{"label":129,"text":130},"Commercial usability","Either output is close to a usable asset with light cleanup.",{"label":132,"text":133},"Recommended next step","Use GPT-Image 1.5 for first-pass variants, then Flux 2 for final polish.",{"lastUpdated":135,"modelsCompared":136,"useCase":137,"bestForA":138,"bestForB":139,"avoidA":140,"avoidB":141,"creditsA":18,"creditsB":34},"June 8, 2026","Flux 2 vs GPT-Image 1.5","Photorealistic","style control & LoRA workflows","accurate prompt adherence","Accurate rendered text is your top priority","You need the lowest cost or advanced editing flexibility",false,{"prices":144,"source":147},[145,146],{"label":17,"credits":18},{"label":20,"credits":21},"registry",{"prices":149,"source":153},[150,151,152],{"label":33,"credits":34},{"label":36,"credits":21},{"label":38,"credits":39},"definitions"]