We use cookies. Cookies and browser storage keep you signed in and remember your preferences. With your permission we also measure how the site is used. You can any time. See our cookie policy.

New here? See how it works A 1-minute tour of the playground, models and your API key.

K3 Edit vs GPT Image 1: API price, context & features · api14

Krea: K3 Edit vs OpenAI: GPT Image 1

A side-by-side comparison of Krea: K3 Edit ($0.11 / image) and OpenAI: GPT Image 1 ($35.00 / 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 1
Provider	Krea	OpenAI
Image output	$0.11 / image	$140.00 / 1M tokens
Image input	$0.04 / image	-
Input	-	$35.00 / 1M tokens
Output	-	$35.00 / 1M tokens
Cache read	-	$4.38 / 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 1 reads 6.1× more context (400,000 tokens).
Only OpenAI: GPT Image 1 supports structured JSON output.

In depth

Krea: K3 Edit is an image model from Krea, released on 2026-10-15. OpenAI: GPT Image 1 is an image model from OpenAI, released on 2026-06-24. Both sit in the same category on api14, so the choice between them is not about one being an image tool and the other something else. It is about which one fits the shape of the job you are handing it.

The clearest split is context. GPT Image 1 takes up to 400000 tokens of input, while K3 Edit takes 65536. If your prompt includes long documents, many reference images, or a large amount of surrounding text, GPT Image 1 has far more room before you have to trim anything. On modalities they match: both accept text and image as input and both return image as output, so neither gives you an extra input or output type the other lacks. The other difference is parameters. GPT Image 1 supports max_tokens, response_format, seed and structured_outputs. K3 Edit lists no supported parameters, which means you send your request and take what comes back, with no seed to pin a result and no structured output to constrain the response. The qualitative notes mark GPT Image 1 as the one with structured outputs and the bigger context, and leave pricing, tool use and reasoning as not meaningfully different or unknown, so cost is not a reliable tiebreaker here beyond what the live price table shows.

For day to day editing work, K3 Edit is the straightforward pick. If you are doing instruction based edits on an image, iterating on a visual, or running a pipeline where the prompt is short and the input is one or two images, the smaller context is not a constraint and the missing parameters do not matter. Reach for GPT Image 1 when the request itself is large or when you need control over the call. Long briefs with several reference images, batches where you want a seed so runs are reproducible, or systems that expect a structured response all point to GPT Image 1. If you are unsure, start with K3 Edit for simple edits and move up when you hit a context limit or need a parameter it does not expose.

Calling either one through api14 works the same way. Both are served behind an OpenAI compatible API, so your request body, your authentication and your client code stay as they are. The only thing that changes is the model id. Send "krea/k3-edit" for Krea and "openai/gpt-image-1" for OpenAI. You can keep one code path and switch between them by swapping that string, which makes it cheap to test both against your actual inputs rather than guessing from a description.

There is a case where the smaller model still wins even though the other is more capable on paper. If your prompts are short and your inputs are a single image, K3 Edit covers the task, and the extra context and parameters on GPT Image 1 go unused. In that situation the simpler model is the better fit, and you avoid building around features you do not need.

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-1" and prompts, streaming and tools keep working.

Krea: K3 Edit details & playground →OpenAI: GPT Image 1 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-1",
  "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 1

Specifications

Key differences

In depth

Switch with one string

More comparisons