GPT-Image 1.5 vs Seedream 4.5
Film grain, retro aesthetic, and nostalgic filters — see how these models compare with real AI-generated outputs.
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Vintage & retro visuals live or die by the details: believable film grain, era-accurate color palettes, subtle halation, and that “printed photo” softness that still preserves key features. On Influencer Studio, GPT-Image 1.5 and Seedream 4.5 both aim to deliver nostalgic aesthetics—but they get there in different ways.
Below is a focused comparison on retro styling performance: how well each model follows era-specific prompts (70s, 80s, 90s, early 2000s), how natural the grain and wear look, and how easy it is to iterate toward a consistent, throwback visual identity.
Vintage & Retro — Side-by-Side Results
Prompt
"A 22–28-year-old woman with shoulder-length wavy dark hair in a thrifted graphic tee and high-waisted light-wash jeans holds her phone slightly above eye level for a casual selfie, glancing near the camera mid-laugh with a coffee cup in her other hand. She’s in a small neighborhood café by a sunny window with plants and mismatched chairs, natural morning light washing the scene. Vintage 90s disposable-camera look with film grain, faded colors, warm nostalgic tone, subtle light leaks and a slightly off-center, imperfect framing like an Instagram Story."
Feature Comparison
| Feature | GPT-Image 1.5 | Seedream 4.5 |
|---|---|---|
| Provider | OpenAI | ByteDance |
| Subcategories | text-to-image | text-to-image, image-to-image |
| 1080p / 2k Mode | Yes | Yes |
| 4k Mode | No | No |
| NSFW Rating | Strict | Low |
| Aspect Ratio | 1:1, 16:9, 9:16, 3:4, 4:3 | 1:1, 16:9, 9:16, 3:4, 4:3 |
| Starting Price | 8 credits | 16 credits |
GPT-Image 1.5 Strengths
- Strong prompt adherence for era-specific direction (e.g., “1970s Kodachrome look,” “90s point-and-shoot flash”) with consistent scene details
- High-fidelity results that keep faces, outfits, and props readable even after adding film grain and nostalgic softness
- Detailed scenes that support authentic retro storytelling (period interiors, signage, textures) without losing clarity
- Flexible output tiers (8/16/32 credits) that make quick vintage concepting cheaper before committing to higher-detail renders
Seedream 4.5 Strengths
- Image-to-image editing is ideal for dialing in retro filters on an existing photo or prior generation (grain strength, color cast, wear, and vibe)
- High-resolution output helps preserve “scanned print” details like paper texture, micro-contrast, and subtle dust/scratch overlays
- Versatile style range for switching between retro sub-genres (film still, disposable camera, VHS-era promo shot, magazine editorial)
- Predictable per-image pricing (16 credits) simplifies budgeting for iterative vintage look development
Verdict
If you’re primarily generating vintage scenes from text and need tight adherence to era cues (wardrobe, set dressing, lighting language), GPT-Image 1.5 is the stronger starting point—especially when you want to explore multiple retro directions at a lower cost before scaling quality.
If your workflow depends on refining an existing image—adding authentic film grain, nostalgic color shifts, and controlled “aged” texture while maintaining high resolution—Seedream 4.5 is typically the better pick thanks to its editing-oriented flexibility.
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