Krea: Krea 2 Medium Turbo vs Recraft: Recraft V4.1 Pro Vector
A side-by-side comparison of Krea: Krea 2 Medium Turbo ($0.05 / image) and Recraft: Recraft V4.1 Pro Vector ($1.05 / image) using current USD prices and capabilities from the api14 catalog. Both run through the same OpenAI-compatible API.
Specifications
| Krea: Krea 2 Medium Turbo | Recraft: Recraft V4.1 Pro Vector | |
|---|---|---|
| Provider | Krea | Recraft |
| Image output | $0.05 / image | $1.05 / image |
| Context window | 65,536 | 65,536 |
| Max output | 58,982 | 58,982 |
| Input | text, image | text, image |
| Output | image | image |
| Tool calling | ||
| Structured output | ||
| Reasoning control | ||
| Added | Jul 20, 2026 | May 13, 2026 |
In depth
Krea: Krea 2 Medium Turbo is an image model from Krea, released on 20 July 2026. Recraft: Recraft V4.1 Pro Vector is an image model from Recraft, released on 13 May 2026. Both are image generation models rather than chat or text models, so when you call either one you are asking for an image back, not a written answer. The naming is worth noting: the Recraft model carries "Vector" in its name, which tells you it is aimed at vector-style output, while the Krea model is positioned as a medium-sized turbo variant, which suggests a speed-oriented configuration. Both are offered through api14 alongside each other, so the choice between them is a routing decision rather than a platform decision.
On the technical facts that are actually recorded, the two models are remarkably close. Both accept text and image as input modalities, both return image as their only output modality, and both expose a context window of 65,536 tokens. Neither lists any supported parameters, so you should not expect to pass sampling controls, style knobs or similar options through the API for either one. The qualitative comparison fields do not separate them either: there is no recorded difference in input cost, output cost, context size, tool support, structured output support or reasoning support. In other words, nothing in the available data says one is cheaper, larger or more capable than the other on those axes. The practical difference comes down to the kind of image each model is built to produce and how each provider has tuned it, not to any documented gap in the interface.
For picking between them, the sensible approach is to match the model to the output you need rather than to a spec sheet, because the spec sheets match. If your task is generating vector artwork, logos, icons, illustrations that need to scale cleanly, or anything destined for a design tool where paths matter more than pixels, Recraft V4.1 Pro Vector is the natural first call given its explicit vector focus. If your task is raster image generation where turnaround matters and a turbo-tuned medium model fits your latency budget, Krea 2 Medium Turbo is the natural first call. Because both take image input as well as text, either can be used for image-to-image style work, so reference images, rough sketches or existing assets can be fed in with a text prompt on both sides. When the task is ambiguous, generate the same prompt on both and compare the outputs directly; that costs you one extra call and removes the guesswork.
Calling either model through api14 works the same way, because api14 exposes an OpenAI-compatible API. You point your existing client at the api14 base URL, send your request in the usual chat completions shape with your text prompt and any input images, and set the model field to the id you want. To use the Krea model, set the model id to "krea/krea-2-medium-turbo". To use the Recraft model, set the model id to "recraft/recraft-v4.1-pro-vector". Everything else in the request can stay identical, which means switching between the two is a one-line change and you can A/B them in the same code path without maintaining two integrations.
Switch with one string
Both models use the same endpoint and request shape. Change the model value from "krea/krea-2-medium-turbo" to "recraft/recraft-v4.1-pro-vector" and prompts, streaming and tools keep working.
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": "recraft/recraft-v4.1-pro-vector",
"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"));
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