Microsoft AI: MAI-Transcribe 2 vs OpenAI: Whisper 1
A side-by-side comparison of Microsoft AI: MAI-Transcribe 2 ($21.00 / minute) and OpenAI: Whisper 1 ($0.02 / minute) using current USD prices and capabilities from the api14 catalog. Both run through the same OpenAI-compatible API.
Specifications
| Microsoft AI: MAI-Transcribe 2 | OpenAI: Whisper 1 | |
|---|---|---|
| Provider | Microsoft | OpenAI |
| Audio | $21.00 / minute | $0.02 / minute |
| Context window | - | - |
| Max output | - | - |
| Input | audio | audio |
| Output | transcription | transcription |
| Tool calling | ||
| Structured output | ||
| Reasoning control | ||
| Added | Sep 3, 2026 | Apr 27, 2026 |
Key differences
- OpenAI: Whisper 1 is 100% cheaper on input tokens.
In depth
Microsoft AI: MAI-Transcribe 2 is a transcription model made by Microsoft. OpenAI: Whisper 1 is a transcription model made by OpenAI. Both fall into the same transcription category, so you are choosing between two speech-to-text systems rather than between a transcription model and something that does a different job. Each accepts audio as input and returns a transcription as output, and neither is a general purpose chat or reasoning model.
The two models look very similar once you line up their specs. Both take audio and both produce transcriptions, so the input and output modalities match. Context length is not listed for either, so there is no documented figure to compare, and the qualitative comparison marks bigger context as unknown rather than favoring one side. The same is true for tool support, structured output and reasoning: none of those are listed as exclusive to either model. The one clear difference given is price on input, where Whisper 1 is the cheaper model to feed audio into. Output pricing is not marked as different, so treat the two as close there. Supported parameters are empty for both, so there is no parameter level difference to plan around.
For most transcription tasks the choice comes down to cost and provider preference rather than capability. If you are sending a lot of audio through the model, the cheaper input pricing on Whisper 1 makes it the economical default, since the two are otherwise aligned on what they accept and return. If your stack is already built around Microsoft models, or you specifically want to evaluate Microsoft's transcription output against OpenAI's, MAI-Transcribe 2 is the one to call. Because neither model advertises tools, structured output or reasoning, do not pick either one expecting it to do more than turn audio into text; any downstream parsing, summarising or classification has to happen in your own code after the transcription comes back.
Calling either model through api14 works the same way because the API is OpenAI compatible. You send your audio to the transcription endpoint with the model id set to either "microsoft/mai-transcribe-2" or "openai/whisper-1", and the rest of your request shape stays identical. Switching between the two is a one line change to the model id, which makes it easy to run the same audio through both and compare the transcripts before committing to one for production.
There is a reasonable case for keeping the other model in your back pocket even after you pick one. If you standardise on Whisper 1 for cost reasons but later need to match an existing Microsoft pipeline, switching to MAI-Transcribe 2 is only that model id change away. Conversely, if you start on MAI-Transcribe 2 for provider alignment, Whisper 1 remains a cheaper input option to fall back to when volume grows.
Switch with one string
Both models use the same endpoint and request shape. Change the model value from "microsoft/mai-transcribe-2" to "openai/whisper-1" 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/whisper-1",
file: fs.createReadStream("audio.mp3"),
});
console.log(result.text);
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