Qwen: Qwen Image 3 vs Recraft: Recraft V4.1 Flash
A side-by-side comparison of Qwen: Qwen Image 3 ($0.11 / image) and Recraft: Recraft V4.1 Flash ($0.02 / image) using current USD prices and capabilities from the api14 catalog. Both run through the same OpenAI-compatible API.
Specifications
| Qwen: Qwen Image 3 | Recraft: Recraft V4.1 Flash | |
|---|---|---|
| Provider | Qwen | Recraft |
| Image output | $0.11 / image | $0.02 / image |
| Image input | $0.01 / image | - |
| Context window | 65,536 | 65,536 |
| Max output | 58,982 | 58,982 |
| Input | text, image | text |
| Output | image | image |
| Tool calling | ||
| Structured output | ||
| Reasoning control | ||
| Added | Aug 5, 2026 | Sep 23, 2026 |
In depth
Qwen Image 3 is an image generation model from Qwen, listed under the model id qwen/qwen-image-3. Recraft V4.1 Flash is an image generation model from Recraft, listed under the model id recraft/recraft-v4.1-flash. Both sit in the image category on api14, so you are choosing between two hosted image models rather than between an image model and a text or video one. Qwen released its model on 2026-08-05, and Recraft released its model on 2026-09-23, so Recraft V4.1 Flash is the newer of the two entries in the catalogue.
The most concrete difference between them is input modality. Qwen Image 3 accepts both text and image as input and returns image output, so it can be driven by a prompt alone or by a prompt plus a reference image. Recraft V4.1 Flash accepts text input only and returns image output, so it works from a written prompt without an image input path. Both list a context length of 65536 tokens, so there is no meaningful difference in how much input they can hold. They also differ in parameter support: Qwen Image 3 exposes max_tokens, presence_penalty, response_format, seed, temperature and top_p, while Recraft V4.1 Flash lists no supported parameters. If you need to set a seed for repeatable output, tune temperature or top_p, or control the response format, Qwen Image 3 gives you those knobs and Recraft V4.1 Flash does not.
For practical selection, start with the input type your pipeline already produces. If your task is text to image only, both models fit, and the deciding factors become parameter control and price, which you can read from the live table on this page. If your task involves an existing image, such as using a reference, a draft or a source picture alongside a written instruction, Qwen Image 3 is the one that accepts that image input, because Recraft V4.1 Flash takes text only. If you want deterministic reruns or fine control over sampling behaviour, Qwen Image 3 is again the fit because of its seed and sampling parameters. If you want the simplest call with no parameters to reason about, Recraft V4.1 Flash keeps the request surface minimal.
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 between the two is the model id: use qwen/qwen-image-3 for Qwen Image 3 and recraft/recraft-v4.1-flash for Recraft V4.1 Flash. Your prompt goes in the same place in both cases, and the response comes back as image output in both cases. That means you can build one code path, keep the model id as a configuration value, and switch between the two without rewriting your client. When you switch to Recraft V4.1 Flash, drop any parameters you were passing, since it lists none as supported, and when you switch to Qwen Image 3 you can add seed, temperature, top_p, presence_penalty, max_tokens or response_format as needed.
There is one case where Recraft V4.1 Flash is still the better pick even though Qwen Image 3 is more flexible. If your prompts are text only and you do not want to set or manage any generation parameters, Recraft V4.1 Flash matches that workflow directly, with a text in, image out contract and nothing else to configure. It is also the more recently released of the two models, which may matter if you prefer the newer entry. Neither model is listed as cheaper on input or output in the qualitative data, and neither has a larger context, so those fields do not decide the choice for you. Check the live price table for the current numbers before you commit, then pick based on whether you need image input and parameter control (Qwen Image 3) or a plain text to image call (Recraft V4.1 Flash).
Switch with one string
Both models use the same endpoint and request shape. Change the model value from "qwen/qwen-image-3" to "recraft/recraft-v4.1-flash" 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-flash",
"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"));
More comparisons
- OpenAI: GPT Image 2.6 Flare vs OpenAI: GPT Image 2.6 Sunburst
- OpenAI: GPT Image 2.6 Flare vs Auto Router
- OpenAI: GPT Image 2.6 Flare vs Auto Code
- OpenAI: GPT Image 2.6 Flare vs Sourceful: Riverflow V2.6 Pro
- OpenAI: GPT Image 2.6 Sunburst vs Auto Router
- OpenAI: GPT Image 2.6 Sunburst vs Auto Code
- OpenAI: GPT Image 2.6 Sunburst vs Sourceful: Riverflow V2.6 Pro
- Auto Router vs Auto Code