Launching GPT Image 1.5: Faster Prompts, Truer Edits, Production-Ready Visuals

GPT Image 1.5 Is Here: Ship Visuals Faster With More Control

If you’ve been waiting for a faster, more faithful image model that treats references and prompt nuance seriously, GPT Image 1.5 (also called chatgpt image 1.5 / gpt-image-1.5 / openai image 1.5) is ready. This post is your 1,000-ish-word primer: what changed, how to use it, and a handful of workflows you can ship today.

Why a New Version?

Two big reasons: instruction following and reference fidelity. GPT Image 1.5 was tuned to keep tiny prompt details intact—fonts stay legible, product edges stay clean, skin tones stay natural. When you add references, the first five images can be preserved at higher fidelity (enable high input fidelity in the UI or set input_fidelity="high" in the API).

Who It’s For

• Content teams that need thumbnails and hero graphics in consistent ratios (1:1, 9:16, 16:9).
• Designers and marketers who need campaign variations with brand-safe colors, typography, and logos.
• Merch sellers who want transparent PNGs for stickers, tees, and labels.
• Cosplayers/gamers or hobbyists who need identity-stable characters across multiple poses.
• Anyone who needs to edit an existing image with precise, prompt-level control.

What’s New in GPT Image 1.5

• Higher prompt fidelity. Small details in lighting, materials, and text render more reliably.
• Better reference handling. Up to 16 references; the first 5 get higher fidelity with the “high” setting.
• Flexible output control. Sizes 1024x1024, 1536x1024, 1024x1536, transparent backgrounds (PNG/WebP), and batch generation (1–10).
• Queue + history. Every request is tracked (Queued → Generating → Succeeded/Failed) with a version tree so you can compare and roll back.

(Image idea: A split-screen showing a prompt + reference on the left, and three consistent GPT Image 1.5 outputs on the right.)

Getting Started in the UI

1. Sign in (required). New accounts get 30 credits; each generation costs 10.
2. Pick a mode. “Generate” for text-to-image; “Edit/Inpaint” for image + instruction.
3. Write a technical prompt. Subject + environment, lens (optional), lighting, composition, style constraints.
4. Add references (optional). Up to 16 images; keep key identities in the first 5 when using high input fidelity.
5. Tune outputs. Choose size/quality, count, moderation level (auto/low), and enable high input fidelity for edits.
6. Generate, download, iterate. Export PNG/JPEG/WebP; regenerate any node in your history.

Five Workflows to Try Today

1. Product hero swap: Upload one product shot; change backgrounds by prompt while keeping edges/logo sharp.
2. Brand-safe posters: Describe typography, materials, and lighting; keep size at 1024×1536 for vertical key art.
3. Identity-stable characters: Place 3–5 reference portraits first, enable high input fidelity, and iterate poses.
4. Transparent stickers: Set background transparent, use PNG/WebP, and export at 1024×1024.
5. Versioned marketing variants: Branch in history—A/B test colorways or lighting without losing the original prompt.

Credit Model (Simple by Design)

• 30 welcome credits on signup.
• 10 credits per generation (regardless of mode).
• Buy credit packs as needed; upgrades remove watermarks and keep balances synced.

Pro Tips

• Put the most critical reference first; the first five get extra fidelity.
• Use concise, technical prompts; specify materials, lighting, and lenses to avoid ambiguity.
• When typography matters, call it out (“sharp label text”, “vector-like edges”, “sans-serif headline”).
• If a job fails, check the queue message—often it’s output count, size, or overly broad prompts.

Final Take

GPT Image 1.5 is about speed + fidelity: it keeps your prompt intent and your references intact while giving you a predictable, credit-based way to ship visuals. Whether you’re designing ads, stickers, character sheets, or product heroes, this release should feel like the balanced default for quality, throughput, and control.