Mistral: Voxtral Mini Transcribe vs OpenAI: GPT Transcribe
A side-by-side comparison of Mistral: Voxtral Mini Transcribe ($0.01 / minute) and OpenAI: GPT Transcribe ($0.02 / minute) using current USD prices and capabilities from the api14 catalog. Both run through the same OpenAI-compatible API.
Specifications
| Mistral: Voxtral Mini Transcribe | OpenAI: GPT Transcribe | |
|---|---|---|
| Provider | Mistral | OpenAI |
| Audio | $0.01 / minute | $0.02 / minute |
| Context window | 16,384 | - |
| Max output | 13,107 | - |
| Input | audio | audio |
| Output | transcription | transcription |
| Tool calling | ||
| Structured output | ||
| Reasoning control | ||
| Added | May 15, 2026 | Aug 5, 2026 |
Key differences
- Mistral: Voxtral Mini Transcribe is 33% cheaper on input tokens.
In depth
Mistral: Voxtral Mini Transcribe is a transcription model from Mistral, and OpenAI: GPT Transcribe is a transcription model from OpenAI. Both sit in the same category on api14, so neither is a general chat or reasoning model that happens to accept audio. You call one or the other when the job is turning speech into text, and the choice comes down to provider, context, and price rather than to a difference in what kind of product each one is.
On capabilities the two are close. Both take audio as input and return a transcription as output, and neither exposes any supported parameters, so you will not find tool calling, structured output, or reasoning controls on either side. The context windows are not meaningfully different for comparison purposes, since the OpenAI entry does not list a context length and the qualitative field marks bigger context as a tie. In practice that means you should not expect one model to swallow dramatically longer audio than the other on the strength of the published numbers alone. Where they do separate is price: Voxtral Mini Transcribe is the cheaper of the two on input, while output pricing is about the same, so the cost gap shows up mainly in what you send rather than in what you get back.
For most transcription work either model will do the job, so pick on the axis that actually differs. If you are pushing a lot of audio through and input cost dominates your bill, Voxtral Mini Transcribe is the natural default because it is cheaper on input. If you are already standardized on OpenAI across the rest of your stack and want one vendor relationship, GPT Transcribe is a reasonable pick even though it costs more to feed. Because output pricing is about the same, the decision rarely turns on the length of the transcripts themselves; it turns on how many minutes of audio you are uploading and how much you care about staying within a single provider's ecosystem.
Calling either one through api14 works the same way, because the gateway speaks the OpenAI-compatible API. You point your client at api14, send your audio to the transcription endpoint, and set the model field to the id you want. Switching providers is a one line change: use mistralai/voxtral-mini-transcribe for the Mistral model, or openai/gpt-transcribe for the OpenAI model. Your request shape, authentication, and response handling stay as they are, so you can move a workload from one to the other without rewriting the integration, and you can route different jobs to different ids from the same codebase.
There is no task in the facts given where one model is clearly the better pick on capability grounds, since both are audio in and transcription out with no extra features listed. The only concrete reason to prefer GPT Transcribe over the cheaper Mistral option is provider preference rather than a functional advantage, and the only concrete reason to prefer Voxtral Mini Transcribe is the lower input price. If neither of those matters to you, treat them as interchangeable and let the live price table on this page settle it.
Switch with one string
Both models use the same endpoint and request shape. Change the model value from "mistralai/voxtral-mini-transcribe" to "openai/gpt-transcribe" and prompts, streaming and tools keep working.
import fs from "node:fs";
import OpenAI from "openai";
const client = new OpenAI({
baseURL: "https://api14.com/api/v1",
apiKey: process.env.API14_API_KEY,
});
const result = await client.audio.transcriptions.create({
model: "openai/gpt-transcribe",
file: fs.createReadStream("audio.mp3"),
});
console.log(result.text);
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