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Lesson 01 of 10 · published

The Image Model Landscape

~12 min · models, tradeoffs, l1

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피파 한 줄 정리: Image 모델 landscape (2026 초): GPT-Image 1.5 (text·conv editing), Midjourney v7 (taste), FLUX (open photoreal), Stable Diffusion (ecosystem), Imagen 4 (enterprise). 'Best'는 task별로 다름.

Choosing an image model is like choosing a camera. A DSLR, a smartphone camera, a medium-format film camera, and an instant Polaroid can all "take a picture," but each one excels at different things and fails at others. No single camera is "the best" — it depends on what you're shooting, how fast you need it, and what you'll do with the result. Image models work the same way.

As of early 2026, the landscape has several strong contenders, each with distinct personalities:

GPT-Image 1.5 (OpenAI)

OpenAI's image generation through GPT-4o — and the dedicated GPT-Image 1.5 API model — represents a fundamentally different approach. Because it lives inside a conversational AI, it can use context from your chat. Tell it "make that background warmer" and it remembers what "that" refers to. It's also the current leader in text rendering inside images: signs, labels, UI mockups, and memes where the words need to be pixel-perfect. It's four times faster and cheaper than its predecessor, with API pricing from $0.009 to $0.133 per image depending on quality and resolution.

Midjourney v7

Midjourney v7, which became the default model in mid-2025, is the taste engine. It produces images with a distinctive warmth, richness, and compositional elegance that many creators describe as "the model with opinions." It excels at campaign concepts, mood boards, editorial illustrations, and anything where aesthetic vibe matters more than photographic accuracy. Draft Mode generates at 10x speed and half cost — perfect for rapid exploration. Its Omni Reference feature lets you feed in visual references for identity, style, or composition preservation.

FLUX (Black Forest Labs)

FLUX has become the open-source benchmark leader. FLUX.1 Schnell (Apache 2.0 licensed) can generate photorealistic images in seconds with just 4 inference steps. FLUX.2 Dev (32B parameters) pushes quality further for local deployment. The model family leads benchmarks in photorealism, hand accuracy, and prompt adherence. Because it's open, you can run it locally, fine-tune it, build products on top of it, and never worry about API rate limits or sudden policy changes.

Stable Diffusion (Stability AI)

Stable Diffusion may not top the benchmarks anymore, but its ecosystem is unmatched. Thousands of fine-tuned model variants, LoRA adapters for specific styles, and tools like ComfyUI and InvokeAI create the deepest customization pipeline in the industry. If you need a hyper-specific anime art style, a particular architectural rendering look, or a niche illustration approach, the SD ecosystem probably has a community-trained model for it.

Imagen 4 (Google)

Google's Imagen 4 comes in three tiers — Fast ($0.02/image), Standard, and Ultra — offering a clear quality-cost ladder. It supports up to 2K resolution and is tightly integrated with Google's AI Studio and Vertex AI. Imagen 4 Ultra is particularly strong for detail-heavy scenes with strict prompt adherence.

Key Takeaways
  • Image models have distinct personalities — taste, text accuracy, openness, ecosystem, or enterprise integration.
  • The landscape changes every few months, but the categories of strength remain stable: realism, style, text, control, cost, and openness.
  • Pick the model that matches your specific output need, not the one with the most Twitter hype.

External links

Exercise

현재 가장 많이 쓰는 image 모델 골라. Model card 전부 읽기. 몰랐던 limitation 3개·사용 안 하던 capability 1개 list.

Progress

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