Dots Studio: Dots3-Note Preview (free) vs XingChen: Xing4.0 29B A4B (free)
A side-by-side comparison of Dots Studio: Dots3-Note Preview (free) (Free) and XingChen: Xing4.0 29B A4B (free) (Free) using current USD prices and capabilities from the api14 catalog. Both run through the same OpenAI-compatible API.
Specifications
| Dots Studio: Dots3-Note Preview (free) | XingChen: Xing4.0 29B A4B (free) | |
|---|---|---|
| Provider | Dots Studio | XingChen |
| Context window | 512,000 | 262,144 |
| Max output | 460,800 | 235,929 |
| Input | text, image | text |
| Output | text | text |
| Tool calling | ||
| Structured output | ||
| Reasoning control | ||
| Added | Aug 14, 2026 | Oct 16, 2026 |
Key differences
- Dots Studio: Dots3-Note Preview (free) reads 2.0× more context (512,000 tokens).
In depth
Dots Studio: Dots3-Note Preview (free) is a text generation model from Dots Studio, released as a preview under the Dots3-Note line. XingChen: Xing4.0 29B A4B (free) comes from XingChen and is a 29B parameter model in the Xing4.0 family, tagged A4B. Both are served on api14 as free endpoints in the text category, so the choice between them is about fit rather than access or budget tier.
The clearest split is context length. Dots3-Note Preview accepts up to 512000 tokens, roughly double the 262144 token window of Xing4.0 29B A4B, so it is the stronger option when you need to keep very long documents, large codebases or extended conversation history in a single call. Dots3-Note Preview also accepts image input alongside text, while Xing4.0 29B A4B is text in and text out only. On the parameter side the two overlap on the essentials: both support tools, tool_choice, structured_outputs, response_format, reasoning, include_reasoning, max_tokens, temperature and top_p. Xing4.0 29B A4B exposes a wider set of sampling and control knobs, including frequency_penalty, presence_penalty, repetition_penalty, min_p, top_k, seed and stop, which gives you more ways to steer or reproduce its output. The qualitative comparison marks Dots3-Note Preview as the larger context model, and does not flag either model as uniquely offering tools, structured output or reasoning.
For day to day work, pick Dots3-Note Preview when the task involves long inputs or mixed media: reviewing a large file tree, summarizing a stack of documents, or answering questions about a screenshot together with accompanying text. Pick Xing4.0 29B A4B when the input is plain text and you want finer control over generation behavior, for example when you need seed based reproducibility, stop sequences, or penalty tuning to keep outputs on track across many runs. If your prompts are short and text only, either model will do the job, and the extra sampling parameters on Xing4.0 29B A4B may be the deciding factor.
Calling either model through api14 works the same way because the gateway is OpenAI compatible. You point your client at the api14 base URL, send your request to the chat completions endpoint with your api14 key, and set the model field to the id you want. Switching between the two is a one line change: use "dots-studio/dots-3-note-preview:free" for Dots3-Note Preview or "xingchen-agi/xing4.0-29b-a4b:free" for Xing4.0 29B A4B. The request and response shapes stay the same, so existing code, SDKs and tool definitions carry over without modification.
There is one case where the smaller model still wins even with a long context option available. If your task is pure text and you rely on sampling controls that Dots3-Note Preview does not list, such as seed, stop, top_k or the penalty parameters, Xing4.0 29B A4B is the better pick regardless of context size, because those controls are part of how you get consistent results. Check the live price table on the page before committing, since both endpoints are listed as free but pricing can change.
Switch with one string
Both models use the same endpoint and request shape. Change the model value from "dots-studio/dots-3-note-preview:free" to "xingchen-agi/xing4.0-29b-a4b:free" 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.chat.completions.create({
"model": "xingchen-agi/xing4.0-29b-a4b:free",
"messages": [
{
"role": "user",
"content": "Explain vector databases in two sentences."
}
]
});
console.log(result.choices[0].message.content);
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