Deepgram: Flux TTS vs ElevenLabs: Eleven Flash v2.5
A side-by-side comparison of Deepgram: Flux TTS ($157.50 / 1M characters) and ElevenLabs: Eleven Flash v2.5 ($140.00 / 1M characters) using current USD prices and capabilities from the api14 catalog. Both run through the same OpenAI-compatible API.
Specifications
| Deepgram: Flux TTS | ElevenLabs: Eleven Flash v2.5 | |
|---|---|---|
| Provider | Deepgram | ElevenLabs |
| Characters | $157.50 / 1M characters | $140.00 / 1M characters |
| Context window | - | - |
| Max output | - | - |
| Input | text | text |
| Output | speech | speech |
| Tool calling | ||
| Structured output | ||
| Reasoning control | ||
| Added | Aug 12, 2026 | Oct 7, 2026 |
Key differences
- ElevenLabs: Eleven Flash v2.5 is 11% cheaper on input tokens.
In depth
Deepgram: Flux TTS is a text to speech model from Deepgram, and ElevenLabs: Eleven Flash v2.5 is a text to speech model from ElevenLabs. Both sit in the speech category, both take text as input and both return speech as output. They are direct alternatives to each other in the sense that either one can serve as the voice layer of an application, and the choice between them comes down to provider, price and the small set of differences listed below rather than to any difference in what kind of job they do.
On capabilities the two are close. Neither model exposes a context length figure, so there is no basis for saying one handles longer inputs than the other. Neither lists supported parameters, so there is no tool calling, structured output or reasoning mode to separate them on. Input and output modalities are identical: text in, speech out. The one qualitative difference given is on price, where ElevenLabs: Eleven Flash v2.5 is the cheaper option for input. Output pricing is not differentiated in the data, so treat the two as about the same on that side. In short, this is not a case of one model being more capable than the other; it is a case of one being cheaper to feed.
For practical selection, start from the fact that the models are functionally interchangeable. If your workload is dominated by input volume, meaning long scripts, documents or transcripts that get synthesized, the cheaper input pricing on ElevenLabs: Eleven Flash v2.5 is the reason to pick it. If your workload is short prompts with heavy output, the input price advantage matters less and either model is a reasonable default. Because there is no measured difference in context handling or parameter support, you should not pick one over the other on the assumption that it accepts longer text or offers features the other lacks. Test both on your own audio and let the result decide, since the data here gives no quality ranking.
Calling either model through api14 works the same way. The API is OpenAI compatible, so you point your existing client at the api14 base URL, send your text in the usual chat or completion style request, and set the model field to the id you want. The only change between the two is that string: use "deepgram/flux-tts" for the Deepgram model and "elevenlabs/eleven-flash-v2.5" for the ElevenLabs model. Your request shape, authentication and response handling stay identical, which means you can switch providers by editing one line or by reading the model id from configuration, and you can route different requests to different models inside the same application without maintaining two integrations.
There is one case where the other model is still the better pick. If your priority is the Deepgram voice or you are already standardized on Deepgram elsewhere in your stack, Deepgram: Flux TTS remains a valid choice even though ElevenLabs: Eleven Flash v2.5 is cheaper on input, because the price gap applies only to input and output pricing is not differentiated. Nothing in the data says the Deepgram model is worse at the task, so consistency with an existing provider is a legitimate reason to stay with it.
Switch with one string
Both models use the same endpoint and request shape. Change the model value from "deepgram/flux-tts" to "elevenlabs/eleven-flash-v2.5" 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": "elevenlabs/eleven-flash-v2.5",
"input": "Hello from api14! One API for every model.",
"voice": "alloy",
"response_format": "mp3"
});
await writeFile("speech.mp3", Buffer.from(await audio.arrayBuffer()));
More comparisons
- AssemblyAI: TTS 1 vs Fish Audio: Drama 3
- AssemblyAI: TTS 1 vs HeyGen: HeyGen Voice
- AssemblyAI: TTS 1 vs HeyGen: HeyGen Voice Turbo
- AssemblyAI: TTS 1 vs Mistral: Voxtral TTS 3
- Fish Audio: Drama 3 vs HeyGen: HeyGen Voice
- Fish Audio: Drama 3 vs HeyGen: HeyGen Voice Turbo
- Fish Audio: Drama 3 vs Mistral: Voxtral TTS 3
- HeyGen: HeyGen Voice vs HeyGen: HeyGen Voice Turbo