Free Models Router vs XingChen: Xing4.0 29B A4B (free)
A side-by-side comparison of Free Models Router (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
| Free Models Router | XingChen: Xing4.0 29B A4B (free) | |
|---|---|---|
| Provider | OpenRouter | XingChen |
| Context window | 200,000 | 262,144 |
| Max output | - | 235,929 |
| Input | text, image | text |
| Output | text | text |
| Tool calling | ||
| Structured output | ||
| Reasoning control | ||
| Added | Feb 1, 2026 | Oct 16, 2026 |
Key differences
- XingChen: Xing4.0 29B A4B (free) reads 1.3× more context (262,144 tokens).
In depth
Free Models Router is a text model offered by OpenRouter, and XingChen: Xing4.0 29B A4B (free) is a text model from XingChen. Both are listed on api14 under the free tier, and both are reachable through the same OpenAI-compatible endpoint, so the choice between them comes down to capability fit rather than access. The two providers are different organisations, and the model ids reflect that: openrouter/free routes to OpenRouter's free pool, while xingchen-agi/xing4.0-29b-a4b:free points at XingChen's own free offering.
The clearest difference is context length. Xing4.0 29B A4B supports a larger context window than Free Models Router, which makes it the better choice when you need to fit long documents, large code files or extended conversation history into a single request. Free Models Router accepts both text and image input, while Xing4.0 29B A4B accepts text only, so any task that involves reading a screenshot, diagram or scanned page has to go to Free Models Router. On the parameter side the two are close: both expose tools, tool_choice, structured_outputs, response_format, reasoning, temperature, top_p, top_k, min_p, repetition_penalty, frequency_penalty, presence_penalty, seed and stop. Free Models Router additionally lists logprobs, top_logprobs, max_completion_tokens and reasoning_effort, which matters if you want token-level probabilities or finer control over how much reasoning effort the model spends.
For day to day work, pick based on the input you have and the length you need. If your prompt is text only and runs long, Xing4.0 29B A4B gives you more room before you have to truncate or chunk, which usually means fewer round trips and simpler code. If your prompt includes an image, or if you need logprobs for classification, confidence scoring or debugging, Free Models Router is the one to call. Tool calling and structured output are available on both, so an agent or JSON-schema workflow can be built on either without changing your parsing layer. When the task is short, text only and does not need probabilities, either model will do, and the deciding factor is likely to be which one behaves better on your particular prompts.
Calling either model through api14 is the same operation. You send a request to the OpenAI-compatible chat completions endpoint with your api14 key, and the only thing that changes between the two is the model field. Set it to "openrouter/free" to use Free Models Router, or to "xingchen-agi/xing4.0-29b-a4b:free" to use Xing4.0 29B A4B. Your messages array, system prompt, tool definitions and response handling stay identical, so you can switch models with a one line change, or route between them at runtime based on whether the request contains an image or exceeds a length threshold you set.
There are still cases where the other model wins. If you have already tuned prompts against Free Models Router and they rely on image input, switching to Xing4.0 29B A4B will break those calls, so keep Free Models Router for anything multimodal. Conversely, if you are processing a long text corpus and hitting context limits on Free Models Router, Xing4.0 29B A4B is the better pick even though it cannot see images, because the extra context is what unblocks the job.
Switch with one string
Both models use the same endpoint and request shape. Change the model value from "openrouter/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);
More comparisons
- LiquidAI: LFM3-1.7B vs Ricursive: Ripple 65B Preview
- LiquidAI: LFM3-1.7B vs Crouton Alpha
- LiquidAI: LFM3-1.7B vs Tencent: Hy4
- LiquidAI: LFM3-1.7B vs Z.ai: GLM 5.3 FlashX Legal
- Ricursive: Ripple 65B Preview vs Crouton Alpha
- Ricursive: Ripple 65B Preview vs Tencent: Hy4
- Ricursive: Ripple 65B Preview vs Z.ai: GLM 5.3 FlashX Legal
- Crouton Alpha vs Tencent: Hy4