Flux 2 vs GPT-Image 1.5
Close-up headshots and environmental portraits — see how these models compare with real AI-generated outputs.
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For portrait work on Influencer Studio—clean close-up headshots and story-rich environmental portraits—Flux 2 and GPT-Image 1.5 take different paths to great results. Both can generate high-quality faces, but they differ in how controllable they are for likeness, how well they follow nuanced prompts, and how efficiently you can iterate.
This comparison focuses on the portrait essentials: natural skin texture, accurate facial features, consistent identity across a set, hair and eye detail, flattering lighting, and believable backgrounds that don’t distract from the subject. We’ll also look at practical workflow factors like editing tools, style options, and credit cost per image.
Portrait — Side-by-Side Results
Prompt
"Portrait photo of a 20s woman with shoulder-length wavy dark hair in a cozy oversized hoodie and leggings, holding her phone slightly out for a casual selfie while glancing near the camera with a relaxed half-smile. She’s standing by a kitchen counter mid–morning coffee routine (mug, open laptop, a few groceries in the background), natural window light on her face, shallow depth of field with soft bokeh and an 85mm lens feel. Authentic, everyday UGC vibe—slightly imperfect framing, candid expression, realistic skin texture."
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
- Portrait control via LoRA support for consistent identity, style, or brand look across multiple headshots
- Versatile image-to-image editing for refining facial details, lighting, wardrobe, or background without restarting
- Up to 4MP output for crisp headshots and tighter crops while retaining detail
- Style transfer options that help keep a cohesive portrait series (editorial, cinematic, lifestyle, etc.)
- Face-swap support for fast concepting and controlled identity variations (useful for mockups and iterations)
GPT-Image 1.5 Strengths
- Strong prompt adherence for precise portrait direction (lighting, lens feel, pose, expression, and environment cues)
- High-fidelity facial rendering that often looks clean and polished for close-up beauty and professional headshots
- Reliable results for complex environmental portraits where the scene description matters (location, time of day, mood)
- Flexible quality tiers (low/medium/high) to balance speed, iteration volume, and final-quality exports
- Good at maintaining overall scene coherence so backgrounds complement the subject instead of competing with it
Verdict
Choose Flux 2 if your portrait workflow depends on control and repeatability—especially when you need the same person (or the same brand aesthetic) across a series. Its editing features, style transfer, and LoRA support make it a strong fit for iterating on headshots, refining facial details, and producing consistent sets for campaigns.
Choose GPT-Image 1.5 if you prioritize prompt accuracy and clean, high-fidelity portrait outputs—particularly for environmental portraits where you want the model to “listen” closely to your creative direction. It’s also attractive for budget-conscious iteration at the low tier, while still offering higher tiers when you need maximum polish.
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