Mistral: Voxtral TTS 3 vs Qwen: Qwen-Audio-3.0-TTS Plus
A side-by-side comparison of Mistral: Voxtral TTS 3 ($45.50 / 1M characters) and Qwen: Qwen-Audio-3.0-TTS Plus ($70.00 / 1M characters) using current USD prices and capabilities from the api14 catalog. Both run through the same OpenAI-compatible API.
Specifications
| Mistral: Voxtral TTS 3 | Qwen: Qwen-Audio-3.0-TTS Plus | |
|---|---|---|
| Provider | Mistral | Qwen |
| Characters | $45.50 / 1M characters | $70.00 / 1M characters |
| Context window | 4,096 | - |
| Max output | 3,276 | - |
| Input | text | text |
| Output | speech | speech |
| Tool calling | ||
| Structured output | ||
| Reasoning control | ||
| Added | Oct 20, 2026 | Jul 23, 2026 |
Key differences
- Mistral: Voxtral TTS 3 is 35% cheaper on input tokens.
In depth
Mistral: Voxtral TTS 3 is a speech model from Mistral, released on 20 October 2026 under the model id mistralai/voxtral-mini-tts-3-0. Qwen: Qwen-Audio-3.0-TTS Plus is a speech model from Qwen, released on 23 July 2026 under the model id qwen/qwen-audio-3.0-tts-plus. Both sit in the speech category on api14, and both are text to speech systems: they take text in and return speech out. Neither is a general chat or reasoning model, so the comparison is really about which text to speech engine fits your pipeline.
On capabilities the two are close. Both accept text as their only input modality and produce speech as their only output modality, so you cannot feed either one audio or images, and you cannot get text back from either. Neither model exposes any supported parameters in the listing, which means you should not plan on tuning sampling options, voice controls or similar knobs through the API surface. The context window is where they visibly part ways in the data: Voxtral TTS 3 lists a context length of 4096 tokens, while Qwen-Audio-3.0-TTS Plus has no context length listed at all. A missing value is not a claim that the context is unlimited, so treat it as unknown rather than as an advantage. The qualitative comparison marks Voxtral TTS 3 as the cheaper input side, while output pricing is about the same between the two. There is no meaningful difference recorded for context size, tool use, structured output or reasoning, and none of those features are listed for either model anyway.
For practical selection, start with the input side of your workload. If you are synthesising large volumes of short prompts, notifications, interface strings or other text that you send repeatedly, Voxtral TTS 3 is the cheaper input option and that difference compounds across calls. If your text inputs are long, remember that Voxtral TTS 3 documents a 4096 token context window, so you need to chunk anything longer before sending it. Qwen-Audio-3.0-TTS Plus does not publish a context length, so you have no documented ceiling to design against; if your inputs are long and you want a stated limit to plan around, Voxtral TTS 3 at least gives you one. If input cost is not the deciding factor and you simply want a second speech vendor in your stack, either works, since output pricing is about the same.
Calling either model through api14 uses the same OpenAI-compatible interface. You point your existing client at the api14 base URL, send a request to the chat completions endpoint with your text as the user message, and read the speech back from the response. The only change between the two is the model id string: use mistralai/voxtral-mini-tts-3-0 for Mistral's model and qwen/qwen-audio-3.0-tts-plus for Qwen's. Your authentication header, request shape and response handling stay identical, so switching is a one line edit and you can route different jobs to different models from the same code path.
There is a case for keeping Qwen-Audio-3.0-TTS Plus in the mix even though Voxtral TTS 3 is cheaper on input. Because Qwen's model has no documented context length, it may accept longer text than the 4096 token window Voxtral TTS 3 declares, though the listing does not confirm this, so verify with your own inputs before relying on it. If you find that your prompts exceed Voxtral TTS 3's window and chunking hurts the audio, Qwen is the reasonable alternative to test. Otherwise, for typical short to medium text to speech jobs, Voxtral TTS 3 is the straightforward default on price.
Switch with one string
Both models use the same endpoint and request shape. Change the model value from "mistralai/voxtral-mini-tts-3-0" to "qwen/qwen-audio-3.0-tts-plus" and prompts, streaming and tools keep working.
import { writeFile } from "node:fs/promises";
import OpenAI from "openai";
const client = new OpenAI({
baseURL: "https://api14.com/api/v1",
apiKey: process.env.API14_API_KEY,
});
const audio = await client.audio.speech.create({
"model": "qwen/qwen-audio-3.0-tts-plus",
"input": "Hello from api14! One API for every model.",
"voice": "alloy",
"response_format": "mp3"
});
await writeFile("speech.mp3", Buffer.from(await audio.arrayBuffer()));
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