Flux 2 vs GPT-Image 1.5
Hyperrealistic renders indistinguishable from photographs — see how these models compare with real AI-generated outputs.
Full comparisonCompare Models (select 4)
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.
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.
Photorealistic — Side-by-Side Results
Prompt
"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."
Feature Comparison
| Feature | Flux 2 | GPT-Image 1.5 |
|---|---|---|
| Provider | Black Forest Labs | OpenAI |
| Subcategories | text-to-image, image-to-image | text-to-image |
| 1080p / 2k Mode | Yes | Yes |
| 4k Mode | Yes | No |
| NSFW Rating | Low | Strict |
| Aspect Ratio | 1:1, 16:9, 9:16, 3:4, 4:3 | 1:1, 16:9, 9:16, 3:4, 4:3 |
| Model Variant | Standard, Klein 9B | — |
| Starting Price | 22 credits | 8 credits |
Flux 2 Strengths
- LoRA support for consistent photoreal subjects, faces, and brand/product looks across a series
- Versatile image-to-image editing for refining realism (lighting tweaks, background swaps, wardrobe/product 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/crop → re-edit
GPT-Image 1.5 Strengths
- 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/credit options (low/medium/high) to balance photoreal detail vs cost per image
- Efficient for “one-shot” photoreal generations when you don’t need heavy post-editing
Verdict
If your definition of photorealistic includes repeatability (same person/product across many images) and hands-on refinement (surgical edits to make the render feel truly photographed), Flux 2 is typically the stronger workflow thanks to LoRA support, image editing, and up to 4MP output.
If you prioritize prompt-accurate photoreal generation—especially complex scenes with lots of specified details—and you want flexible spend levels per render, GPT-Image 1.5 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.
Frequently Asked Questions
More Comparisons by Category
Try Both Models Free
Sign up and get credits to test Flux 2, GPT-Image 1.5, and all our other AI models for photorealistic.
Join Influencer Studio Today
Start creating amazing AI-generated content for your brand