Which AI Model Works Best for Jewelry Photography?

We tested 11 AI image generators so you don’t have to. Here’s what actually works.

The Short Answer

If you’re selling jewelry online and want AI-generated lifestyle photos, use one of these:

Skip these entirely: Qwen-Image, Runway Gen-4, Seedream 4, GPT Image 1.5

Why This Matters

Lifestyle product photos — showing your jewelry worn on a hand, around a neck, or styled in a scene — convert better than studio shots. But they’re expensive:

• Professional photographer: $50-200+ per shot
• DIY with models: Hours of time, inconsistent results
• Stock photos: Generic, not your actual product

AI image generation promises to change this. Upload a photo of your ring, get a lifestyle shot in seconds. But which AI actually works?

We tested 11 of the leading AI image generators on a simple task: generate a “ring on hand” product photo. The results were surprising.

The Test: 132 Images, 11 Models

We gave each model the same challenge:

1. Here’s a photo of a ring
2. Generate a lifestyle shot showing it worn on a woman’s hand
3. The ring should be recognizable, the hand should look real

We tested 3 rings (simple, medium complexity, complex) across 4 different prompting approaches. That’s 132 total images, all evaluated blind (we didn’t know which model made which image while scoring).

What We Measured

• Ring accuracy: Does it match the reference?
• Hand quality: Does it look human?
• Placement: Is the ring actually on a finger?
• AI look: Would a customer notice it’s AI-generated?
• Usability: Would you publish this on your shop?

The Results: Clear Winners and Losers

The Winners

#1: Nano Banana Pro (Google)

• 85% of images were usable
• 0% rejected — literally never failed
• Perfect for complex jewelry

This is Google’s flagship image model. It costs more ($0.15/image) but it never produced an unusable result. For hero images, marketing materials, or complex pieces, it’s worth the premium.

#2: FLUX.2 Pro (Black Forest Labs)

• 69% usable
• Only 8% rejected
• Best balance of quality and cost

At $0.045/image, FLUX.2 Pro is our pick for most sellers. You’ll occasionally need to regenerate, but it’s 3x cheaper than Nano Banana Pro.

#3: Nano Banana (Google)

• 46% usable
• 8% rejected
• Good for simple rings

The budget Google option. Works well for straightforward pieces but struggles with intricate details.

The Losers

Qwen-Image & Runway Gen-4: 100% Failure Rate

Every single image from these models was rejected. They simply couldn’t reproduce the reference ring — they generated different rings entirely.

GPT Image 1.5: 58% Rejected

OpenAI’s image model surprised us (negatively). More than half the outputs were unusable. The ring style would be “inspired by” but not match the reference.

Seedream 4 & 4.5: 58-75% Rejected

ByteDance’s models couldn’t handle jewelry details. They work fine for other use cases, but not for precise product photography.

What Actually Improves Results?

Scenario: Replace > Generate

We tested two approaches:

1. Generate from scratch: Give the AI just the ring photo and ask for a lifestyle shot
2. Replace: Give the AI a hand photo WITH a ring, ask it to swap in your ring

Result: Replace works better (46% win rate vs 35%)

Why? When you provide a hand reference, the AI has more context. It knows exactly what pose, lighting, and style you want. It just needs to change the ring.

Recommendation: Find or generate a base hand photo you like, then use the Replace approach for all your rings.

Description: Doesn’t Help Much

We expected adding a text description (“gold ring with pear-shaped diamond…”) would improve accuracy. It didn’t.

• With description: 41% win rate
• Without description: 40% win rate

The reference image contains more information than words can convey. For complex rings, descriptions may actually hurt by adding conflicting details.

Recommendation: Keep prompts simple. Focus on the scene, not the ring details.

Ring Complexity: Simpler = Better

Simple rings have 50% higher success rates. If you’re new to AI photography, start with your simpler pieces.

Practical Workflow

Based on our research, here’s how to get started:

Step 1: Choose Your Model

• Quality priority: Nano Banana Pro ($0.15)
• Volume priority: FLUX.2 Pro ($0.045)
• Budget priority: Nano Banana ($0.039)

Step 2: Prepare Reference Images

• Use high-quality photos of your jewelry
• Clean white/neutral backgrounds work best
• Front-facing, well-lit shots

Step 3: Get a Base Hand Photo

Either:

• Generate one with AI (just once)
• Use a stock photo with appropriate license
• Photograph your own hand

This becomes your template for the Replace scenario.

Step 4: Generate with Replace Approach

Prompt structure:

Replace the ring in this photo with the ring from the reference image.
Keep the hand pose and lighting unchanged.

Step 5: Budget for Iterations

Even the best model doesn’t hit 100%. Plan for:

• Nano Banana Pro: 1.2x generations per usable image
• FLUX.2 Pro: 1.5x generations per usable image
• Nano Banana: 2x generations per usable image

Common Problems & Fixes

Problem: Ring doesn’t match reference

Cause: Model isn’t capturing the details from your reference image.

Fixes:

• Try a cleaner reference photo
• Use FLUX.2 Pro or Nano Banana Pro (they have better reference fidelity)
• Simplify: test with a simpler ring first

Problem: Wrong finger

Cause: Models often put rings on index or middle finger instead of ring finger.

Fixes:

• Specify “ring finger” in your prompt
• Use a hand reference photo where the ring is already on the correct finger
• Regenerate — this is somewhat random

Problem: Obviously AI-looking hands

Cause: Some models generate “uncanny valley” skin textures.

Fixes:

• Switch to Nano Banana Pro (best hand quality)
• Use the Replace approach with a real hand photo
• Check the “AI Look” rating before publishing

Problem: Ring floating or clipping into hand

Cause: The AI struggles with 3D geometry for complex rings.

Fixes:

• Simplify: test with simpler rings
• Use Replace approach (gives AI better spatial context)
• Regenerate and pick the best

Cost Comparison

For 100 product lifestyle photos:

Hidden cost: Your time reviewing and regenerating. Nano Banana Pro’s zero-failure rate means less manual work.

What We’re Testing Next

This study answered the baseline question: Can AI do this at all? Next, we’re investigating:

1. Ideogram inpainting: Does the mask-based workflow beat these results?
2. Consistency testing: Can winning models produce 10 good images in a row?
3. Other jewelry types: Do bracelets, necklaces, and earrings work the same?
4. Prompt optimization: Can we improve failing models with better prompts?

Bottom Line

AI jewelry photography works — but only with the right models. Use Nano Banana Pro for quality, FLUX.2 Pro for volume, and skip Qwen, Runway, and Seedream entirely.

Start with simple rings, use the Replace approach, and budget for some regenerations. You’ll be producing professional lifestyle shots at a fraction of traditional photography costs.

Based on original research by studio formel. Full methodology and data available in the complete research report.

Related Articles

• The Complete Guide to Jewelry Photography — Every shot type you need for e-commerce
• AI Image Generation Studios & Models: 2025 Guide — Complete overview of every major AI platform
• Head-to-Head Model Comparison (Research) — Deep dive into model performance

About studio formel

studio formel is an AI-powered creative platform built specifically for jewelry brands. We combine systematic research on AI generation with a flexible asset management system, helping jewelry sellers create professional images, videos, and ads at scale.

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