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K3 Edit vs GPT-5.4 Image 2: API price, context & features · api14

Krea: K3 Edit vs OpenAI: GPT-5.4 Image 2

A side-by-side comparison of Krea: K3 Edit ($0.11 / image) and OpenAI: GPT-5.4 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-5.4 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	-	$52.50 / 1M tokens
Cache read	-	$7.00 / 1M tokens
Web search	-	$35.00 / 1K searches
Context window	65,536	272,000
Max output	58,982	128,000
Input	text, image	image, text, file
Output	image	image, text
Tool calling
Structured output
Reasoning control
Added	Oct 15, 2026	Apr 21, 2026

Key differences

OpenAI: GPT-5.4 Image 2 reads 4.2× more context (272,000 tokens).
Only OpenAI: GPT-5.4 Image 2 supports structured JSON output.
Only OpenAI: GPT-5.4 Image 2 supports reasoning effort control.

In depth

Krea: K3 Edit is an image model from Krea, released on 2026-10-15. OpenAI: GPT-5.4 Image 2 is an image model from OpenAI, released on 2026-04-21. Both sit in the image category on api14, so you are choosing between two vendors' approaches to image generation and editing rather than between an image model and a text model.

The clearest split is context and modality. GPT-5.4 Image 2 has the bigger context window at 272000 tokens against 65536 for K3 Edit, so it can hold far more input in a single call. On input, K3 Edit accepts text and image, while GPT-5.4 Image 2 accepts image, text and file, which means you can feed it documents directly rather than converting them first. On output, K3 Edit returns images only, whereas GPT-5.4 Image 2 returns both image and text, so it can explain or describe alongside the image it produces. GPT-5.4 Image 2 also exposes a wide set of supported parameters, including reasoning, reasoning_effort, include_reasoning, structured_outputs, response_format, seed, max_tokens, logprobs, top_logprobs and verbosity. K3 Edit lists no supported parameters. The qualitative comparison marks GPT-5.4 Image 2 as the only one of the two with structured output support and the only one with reasoning support. The price comparison fields are not meaningfully different or unknown, so treat the two as broadly comparable on cost and check the live price table on the page for current numbers.

For practical selection, reach for K3 Edit when the job is straightforward image editing or generation driven by a prompt plus a reference image, and you do not need the model to return text or reason through a problem before drawing. Its 65536 token window is ample for typical prompt and image payloads. Reach for GPT-5.4 Image 2 when your input includes files, when you need a text answer next to the image, when you want structured output you can parse programmatically, or when you want to control reasoning effort and other generation parameters. The larger context also helps when you are passing long documents or many reference images in one request. If your pipeline depends on seeds for reproducibility or on logprobs, only GPT-5.4 Image 2 offers those here.

Calling either model through api14 works the same way because the API is OpenAI-compatible. You point your client at the api14 base URL, send your request in the usual chat completions shape, and set the model field to the id you want. To use Krea's model, set model to "krea/k3-edit". To use OpenAI's model, set model to "openai/gpt-5.4-image-2". Everything else about the request structure stays the same, so switching between them is a one line change in your code or config. Note that the parameters you can send differ: GPT-5.4 Image 2 accepts the reasoning, structured output and sampling parameters listed above, while K3 Edit accepts none of them, so guard or strip those fields when you route to K3 Edit.

There are still cases where K3 Edit is the better pick even though GPT-5.4 Image 2 is more capable on paper. If your task is pure image editing with a text prompt and an input image, and you have no use for text output, file input, reasoning or structured responses, K3 Edit covers it without the extra surface area. Since the qualitative pricing fields do not show a meaningful difference, there is no cost argument pulling you either way, so the decision comes down to whether you actually need the extra modalities and parameters. If you do not, the simpler model is a reasonable default.

Switch with one string

Both models use the same endpoint and request shape. Change the model value from "krea/k3-edit" to "openai/gpt-5.4-image-2" and prompts, streaming and tools keep working.

Krea: K3 Edit details & playground →OpenAI: GPT-5.4 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-5.4-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-5.4 Image 2

Specifications

Key differences

In depth

Switch with one string

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