Krea: K3 Edit vs Tencent: Hy Image 3.5 Preview
A side-by-side comparison of Krea: K3 Edit ($0.11 / image) and Tencent: Hy Image 3.5 Preview ($5.60 / 1M tokens) using current USD prices and capabilities from the api14 catalog. Both run through the same OpenAI-compatible API.
Specifications
| Krea: K3 Edit | Tencent: Hy Image 3.5 Preview | |
|---|---|---|
| Provider | Krea | Tencent |
| Image output | $0.11 / image | $5.60 / 1M tokens |
| Image input | $0.04 / image | $5.60 / 1M tokens |
| Context window | 65,536 | 100,000 |
| Max output | 58,982 | 90,000 |
| Input | text, image | text, image |
| Output | image | image |
| Tool calling | ||
| Structured output | ||
| Reasoning control | ||
| Added | Oct 15, 2026 | Oct 5, 2026 |
Key differences
- Tencent: Hy Image 3.5 Preview reads 1.5× more context (100,000 tokens).
In depth
Krea: K3 Edit is an image model from Krea, and Tencent: Hy Image 3.5 Preview is an image model from Tencent. Both sit in the image category, both take text and image input, and both return image output only. Neither exposes any supported parameters in the data api14 has, so you are not choosing between them on the basis of tunable knobs such as temperature or top_p. The two provider release dates are close together, with Hy Image 3.5 Preview listed on 2026-10-05 and K3 Edit on 2026-10-15, so neither is a legacy option relative to the other.
The clearest measurable difference is context length. Hy Image 3.5 Preview accepts up to 100000 tokens, while K3 Edit accepts up to 65536 tokens. That makes Tencent the model with the bigger context window, which matters when your prompt includes long instructions, several reference images, or a large amount of supporting text alongside the image input. On modalities the two are identical: text plus image in, image out. The qualitative comparison flags no difference for tool use, structured output, or reasoning, and it does not identify either side as cheaper on input or output, so treat pricing as roughly comparable and check the live price table on this page for the current numbers rather than assuming one is the budget choice.
For day to day work, the decision usually comes down to how much you are feeding the model at once. If your requests are short prompts with one or two reference images, K3 Edit is a reasonable default and its smaller context ceiling will rarely be the binding constraint. If you are sending long briefs, many reference images, or extended style guidance in a single call, Hy Image 3.5 Preview gives you more room before you have to trim or split the request. Because neither model advertises extra capabilities such as tool calling or structured output, there is no feature based reason to prefer one over the other; the context window is the main axis of difference the data supports.
Calling either model through api14 works the same way, because the gateway exposes an OpenAI compatible API. You send your request to the same endpoint with the same request shape, and the only change is the model id string. Use "krea/k3-edit" when you want Krea's model and "tencent/hy-image-v3.5-preview" when you want Tencent's. Your text and image inputs go in the same fields either way, and the response comes back as image output in both cases. This makes switching cheap: you can keep one client implementation, swap the model id, and compare results on your own inputs without rewriting request handling.
There is a case for keeping both configured rather than committing to one. If you have standardized on Krea for most of your image generation and a particular job needs a much longer combined prompt and reference set, routing that single request to "tencent/hy-image-v3.5-preview" is a one line change and avoids splitting the work. The reverse also holds if you prefer Tencent by default but want to test Krea's output on the same inputs. Since the modalities and supported parameters match, nothing in your request pipeline needs to change beyond the model id.
Switch with one string
Both models use the same endpoint and request shape. Change the model value from "krea/k3-edit" to "tencent/hy-image-v3.5-preview" 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": "tencent/hy-image-v3.5-preview",
"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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