ElevenLabs: Eleven Flash v2.5 vs Microsoft AI: MAI-Voice-2.1
A side-by-side comparison of ElevenLabs: Eleven Flash v2.5 ($140.00 / 1M characters) and Microsoft AI: MAI-Voice-2.1 ($77.00 / 1M characters) using current USD prices and capabilities from the api14 catalog. Both run through the same OpenAI-compatible API.
Specifications
| ElevenLabs: Eleven Flash v2.5 | Microsoft AI: MAI-Voice-2.1 | |
|---|---|---|
| Provider | ElevenLabs | Microsoft |
| Characters | $140.00 / 1M characters | $77.00 / 1M characters |
| Context window | - | - |
| Max output | - | - |
| Input | text | text |
| Output | speech | speech |
| Tool calling | ||
| Structured output | ||
| Reasoning control | ||
| Added | Oct 7, 2026 | Oct 1, 2026 |
Key differences
- Microsoft AI: MAI-Voice-2.1 is 45% cheaper on input tokens.
In depth
ElevenLabs: Eleven Flash v2.5 is a speech model from ElevenLabs, and Microsoft AI: MAI-Voice-2.1 is a speech model from Microsoft. Both sit in the same category on api14, meaning both take text in and produce speech out. They were released close together, with MAI-Voice-2.1 arriving on 2026-10-01 and Eleven Flash v2.5 on 2026-10-07. Neither is a general purpose text model, so the comparison is really about which text to speech engine to wire into your application.
On the surface the two models look almost identical in shape. Both accept text as their only input modality and both return speech as their only output modality. Neither lists a context length, so there is no published token window to compare, and neither lists supported parameters, so there is no documented knob set that separates them. The qualitative comparison shows no difference in tools, structured output, or reasoning support, which fits the fact that these are speech models rather than chat models. The one clear difference given is price: MAI-Voice-2.1 is the cheaper model on input. Output pricing is not marked as different, so treat the two as about the same on that side.
For practical selection, the input price gap is the main lever. If your workload sends a lot of text into the model, for example long scripts, article narration, or bulk generation of audio from large text corpora, MAI-Voice-2.1 is the cheaper option on input and is the natural default. If your workload is dominated by short prompts and you care about the voice character or the specific ElevenLabs output style, Eleven Flash v2.5 remains a reasonable choice, since the two are otherwise close in capability and the output side is not flagged as cheaper for either. Because no context length is published for either model, do not assume one can swallow longer input than the other; chunk your text yourself if you are near any practical limit.
Calling either model through api14 works the same way, because the gateway exposes an OpenAI-compatible API. You send a request to the same endpoint with the same request shape, and the only thing you change is the model id. Use "elevenlabs/eleven-flash-v2.5" to route to ElevenLabs and "microsoft/mai-voice-2.1" to route to Microsoft. That means you can build one integration, keep your request body fixed, and switch providers by swapping a single string, which makes A/B testing the two voices on real traffic straightforward.
There is a case where the other model is still the better pick. If you have already tuned your pipeline around ElevenLabs output and your input volume is modest, the input price advantage of MAI-Voice-2.1 may not matter enough to justify changing, and Eleven Flash v2.5 stays the better fit. Conversely, if you are starting fresh and your text volume is high, MAI-Voice-2.1 is the cheaper input choice and the sensible default. Since output pricing is not differentiated and neither model exposes extra capabilities, the decision comes down to input cost and which voice you prefer.
Switch with one string
Both models use the same endpoint and request shape. Change the model value from "elevenlabs/eleven-flash-v2.5" to "microsoft/mai-voice-2.1" 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": "microsoft/mai-voice-2.1",
"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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