Fish Audio: Transcribe 1 vs Microsoft AI: MAI-Transcribe 2
A side-by-side comparison of Fish Audio: Transcribe 1 ($0.02 / minute) and Microsoft AI: MAI-Transcribe 2 ($21.00 / minute) using current USD prices and capabilities from the api14 catalog. Both run through the same OpenAI-compatible API.
Specifications
| Fish Audio: Transcribe 1 | Microsoft AI: MAI-Transcribe 2 | |
|---|---|---|
| Provider | Fish Audio | Microsoft |
| Audio | $0.02 / minute | $21.00 / minute |
| Context window | - | - |
| Max output | - | - |
| Input | audio | audio |
| Output | transcription | transcription |
| Tool calling | ||
| Structured output | ||
| Reasoning control | ||
| Added | Jul 29, 2026 | Sep 3, 2026 |
Key differences
- Fish Audio: Transcribe 1 is 100% cheaper on input tokens.
In depth
Fish Audio: Transcribe 1 is a transcription model from Fish Audio, and Microsoft AI: MAI-Transcribe 2 is a transcription model from Microsoft. Both sit in the same category on api14, so neither is a general chat or reasoning model you would reach for to draft text or answer questions. They exist to take audio in and give you a transcription back. Fish Audio's model carries a provider release date of 2026-07-29, while Microsoft's carries 2026-09-03, so the Microsoft entry is the newer of the two on paper.
On capabilities the two are closer than the labels suggest. Both accept audio as their only input modality and both return transcription as their only output modality. Neither lists a published context length, so there is no documented figure to compare for how much audio or accompanying text each can handle in one call. Neither lists supported parameters, which means there is no documented set of knobs such as temperature, language hints or timestamps to tune on either side. The qualitative comparison marks no difference for context window, tool use, structured output or reasoning, so none of those separate them. The one clear difference is cost: Fish Audio: Transcribe 1 is the cheaper option on input. Output pricing is not marked as different, so treat the two as about the same there.
For picking between them, the practical split follows from that. If your workload is high volume transcription where input audio dominates the bill, Fish Audio: Transcribe 1 is the straightforward choice because it is cheaper on input and nothing in the listed capabilities holds it back. If you have no strong cost pressure and prefer the Microsoft model, or your team already standardizes on Microsoft tooling and wants to keep transcription in that family, MAI-Transcribe 2 is a reasonable default. Because the documented capability sets are identical, there is no task in the given facts that one can do and the other cannot, so the decision comes down to price and provider preference rather than features.
Calling either one through api14 works the same way, since the gateway exposes an OpenAI-compatible API. You send your audio to the transcription endpoint using the same request shape you would use for any OpenAI-compatible transcription call, and the only thing that changes between the two models is the model id. Use "fish-audio/transcribe-1" to route to the Fish Audio model, or "microsoft/mai-transcribe-2" to route to the Microsoft model. Everything else in your client code, your authentication and your response parsing stays as is, so switching providers is a one line change and you can benchmark both against your own audio without rewriting an integration.
There is no case in the supplied facts where the more expensive model is required. Since context window, tools, structured output and reasoning are all marked as no different, and output pricing is not distinguished, nothing forces you onto MAI-Transcribe 2 for a capability reason. The only honest reason to pick it over the cheaper Fish Audio model is preference for the provider or a deliberate choice to pay more, not a feature gap.
Switch with one string
Both models use the same endpoint and request shape. Change the model value from "fish-audio/transcribe-1" to "microsoft/mai-transcribe-2" 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: "microsoft/mai-transcribe-2",
file: fs.createReadStream("audio.mp3"),
});
console.log(result.text);
More comparisons
- AssemblyAI: Universal-3.6 Pro vs Mistral: Voxtral Mini Transcribe 3
- AssemblyAI: Universal-3.6 Pro vs Mistral: Voxtral Small Transcribe 3
- AssemblyAI: Universal-3.6 Pro vs Moondream: Parakeet Ultra
- AssemblyAI: Universal-3.6 Pro vs NVIDIA: Nemotron 3.5 Transcribe
- Mistral: Voxtral Mini Transcribe 3 vs Mistral: Voxtral Small Transcribe 3
- Mistral: Voxtral Mini Transcribe 3 vs Moondream: Parakeet Ultra
- Mistral: Voxtral Mini Transcribe 3 vs NVIDIA: Nemotron 3.5 Transcribe
- Mistral: Voxtral Small Transcribe 3 vs Moondream: Parakeet Ultra