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K3 Edit vs GPT Image 2: API price, context & features · api14

Krea: K3 Edit vs OpenAI: GPT Image 2

A side-by-side comparison of Krea: K3 Edit ($0.11 / image) and OpenAI: GPT Image 2 ($28.00 / 1M tokens) using current USD prices and capabilities from the api14 catalog. Both run through the same OpenAI-compatible API.

Specifications

	Krea: K3 Edit	OpenAI: GPT Image 2
Provider	Krea	OpenAI
Image output	$0.11 / image	$105.00 / 1M tokens
Image input	$0.04 / image	-
Input	-	$28.00 / 1M tokens
Output	-	$28.00 / 1M tokens
Cache read	-	$7.00 / 1M tokens
Web search	-	$35.00 / 1K searches
Context window	65,536	400,000
Max output	58,982	360,000
Input	text, image	text, image
Output	image	image
Tool calling
Structured output
Reasoning control
Added	Oct 15, 2026	Jun 24, 2026

Key differences

OpenAI: GPT Image 2 reads 6.1× more context (400,000 tokens).
Only OpenAI: GPT Image 2 supports structured JSON output.

In depth

Krea: K3 Edit is an image model from Krea, released on 2026-10-15. OpenAI: GPT Image 2 is an image model from OpenAI, released on 2026-06-24. Both sit in the image category on api14, and both take text and images as input and return images as output. If you are choosing between them, the practical difference is not what they produce at the top level but how much they let you control the call and how much input they can hold at once.

The clearest split is context length. GPT Image 2 supports 400000 tokens of context, while K3 Edit supports 65536, so GPT Image 2 is the one to reach for when your prompt, reference images or surrounding instructions are long or numerous. GPT Image 2 also exposes supported parameters that K3 Edit does not list: max_tokens, response_format, seed and structured_outputs. That means GPT Image 2 is the only one of the two where you can pin a seed for repeatable output, request a particular response format, cap generated tokens, or ask for structured outputs. K3 Edit lists no supported parameters, so treat it as a simpler call surface. Neither model is flagged as the only one with tools or the only one with reasoning, and the qualitative notes do not mark either as cheaper on input or output, so cost is not a deciding factor between them at this level.

For day to day work, pick based on how much you need to steer the call. If you are generating an image from a short text prompt, or editing a single reference image with a brief instruction, K3 Edit is a reasonable fit and its smaller context is unlikely to matter. If your prompt is long, if you are passing several reference images, or if your pipeline depends on a fixed seed, a declared response format or structured outputs, GPT Image 2 is the better pick because those are the parameters it supports. The same applies when you need to keep a large amount of context in one request rather than splitting it across calls.

Calling either model through api14 works the same way, because the API is OpenAI compatible. You send your request to the same endpoint with the same request shape, and the only thing you change is the model id: use "krea/k3-edit" for Krea's model and "openai/gpt-image-2" for OpenAI's. Your text and image inputs go in as usual, and the image comes back in the response. If you later need a parameter that only one side supports, such as seed or structured_outputs, switch the model id to "openai/gpt-image-2" and add it; there is no separate SDK or auth flow to learn.

There is one case where K3 Edit remains the better pick even though GPT Image 2 has the larger context and more parameters: when your task is a straightforward generation or edit with a short prompt and a single reference image, and you do not need seeds, response formats or structured outputs. In that situation the extra context and parameters on GPT Image 2 buy you nothing, and the simpler call surface of K3 Edit is enough.

Switch with one string

Both models use the same endpoint and request shape. Change the model value from "krea/k3-edit" to "openai/gpt-image-2" and prompts, streaming and tools keep working.

Krea: K3 Edit details & playground →OpenAI: GPT Image 2 details & playground →

import OpenAI from "openai";

const client = new OpenAI({
  baseURL: "https://api14.com/api/v1",
  apiKey: process.env.API14_API_KEY,
});

const result = await client.images.generate({
  "model": "openai/gpt-image-2",
  "prompt": "A minimalist product photo of a ceramic mug on a wooden table",
  "n": 1,
  "aspect_ratio": "1:1"
});
import { writeFile } from "node:fs/promises";
await writeFile("image.png", Buffer.from(result.data[0].b64_json, "base64"));

Krea: K3 Edit vs OpenAI: GPT Image 2

Specifications

Key differences

In depth

Switch with one string

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