Voxtral TTS vs. ElevenLabs: Voice Cloning and TTS

If you're choosing between Voxtral TTS and ElevenLabs, it comes down to whose voice you need. With stock voices, ElevenLabs won every test I ran. It sounded human, followed every emotion tag, and got the name, date and order number right where Voxtral didn't. Voxtral sounded rushed and flat, like text-to-speech from a couple of years ago. Cloning my own voice went the other way: Voxtral kept my South African accent, even from five seconds of audio, while ElevenLabs gave me a thick British accent.

Mistral released Voxtral 3 on 20 October 2026, and the TTS model is in public preview. I tested the things Mistral says are new against Eleven v4, using the same scripts I used in my Fish Audio and Gemini comparisons, so you can compare ElevenLabs across all three, and every clip is below to listen to.

What this tests: Mistral's headline claim that Voxtral 3 voices "adjust their emotion, pace, and emphasis based on conversational context" with no instructions. The script is someone getting good news at work, then remembering it isn't public yet, read as plain text with no tags.

I wasn't going to tell anyone. We got the Lisbon project! I read the email three times before I believed it. Anyway, don't tell anyone yet. It's not official until Friday. Right. Now I just have to work out how to tell the team without grinning like an idiot.

ListenRushed; excitement sounds forced

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ListenConversational, shifts emotion on its own

ElevenLabs sounded more natural and more conversational. At 0:02 it puts secrecy into "I wasn't going to tell anyone" and then switches to excitement, all inferred from the text.

Voxtral found the same moments: the excitement, the change at "Anyway" and the pause at "Right." But it read the whole thing as if it were in a hurry, and the excitement on "Lisbon project" at 0:02 sounds forced. It sounded like someone reading from a sheet of paper. Its clip is 15 seconds against ElevenLabs' 17, and you can hear the difference. I'd use the ElevenLabs take as it is.

What this tests: Voxtral 3's new inline tags. Mistral documents 34 emotions, pace control, and sounds like [laugh] and [sigh]. Voxtral has no whisper tag, so I swapped the whisper from my Fish Audio test for directions both tools support, and kept the same words and voices as before.

Voxtral tags last until the next tag of the same kind, so its script needs [pace=moderate] after "Friday" to get back to normal speed. ElevenLabs tags don't need resetting.

ListenIgnored 'anxious', overdid 'slow'

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ListenEvery tag landed; the laugh carries over

ElevenLabs followed every direction and still inferred emotion where there was no tag, like the first sentence at 0:01. At 0:13 it moves from the sigh into the laugh naturally, and the laugh carries into the next sentence instead of stopping dead before it.

Voxtral's emotions sounded read rather than acted. At 0:02 the [excited] sentence sounds the same as the untagged sentence before it. "Anyway, don't tell anyone yet" has no emotion at all, so [anxious] was ignored. Then at 0:09 it overdoes the slow line so much that I was waiting for it to finish, and against the rushed pace of everything else the change is very obvious. The sigh and the laugh both happen, but they sound like the model was told to do them. The pace reset did work: it went back to normal speed after "Friday".

Direction improved both tools compared with their natural reads, but Voxtral still felt rushed. ElevenLabs used the tags to colour the whole paragraph, while Voxtral applied each emotion to its own sentence and moved on. I didn't hear either tool read a tag aloud.

What this tests: the kind of appointment message a clinic might send. This is where I expected Voxtral to do best, because Mistral says it benchmarked Voxtral 3 on numbers and unusual names, and on local formats like dates and currencies. Neither script had tags.

Hi, it's Dr. Nkosi's office. Your appointment is on 3 April 2026 at 14:45. The total is R1,249.50. Your booking reference is A-7419-X. If you need to change it, call 0800 555 0147. For the video appointment, please use the 2.4 GHz network if the other connection drops. Thanks, and we'll see you on Friday.

ListenBetter amount and phone number, dropped a dash

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ListenConsistently correct

ItemVoxtralElevenLabsDr. Nkosi"nir-kow-see", wrongCorrect, "n-kaw-see"3 April 2026"on third April", which in that order should be "on the third of April""on April third", naturalR1,249.50"one thousand two hundred and forty-nine rand and fifty cents", the more natural phrasing"one thousand two hundred forty-nine rand and fifty cents", correctA-7419-XLeft out the second dashBoth dashes spoken0800 555 0147"zero eight hundred", which sounds more professional"oh eight oh oh", correct Both read 14:45 and 2.4 GHz correctly.

This was Voxtral's best test, and I didn't expect it to do this well after the first two. It read the rand amount and the phone number better than ElevenLabs. In my Fish comparison I wished ElevenLabs would say "oh-eight-hundred" for 0800, and Voxtral's "zero eight hundred" is close to that. It was also less rushed here, at a perfectly reasonable speed.

But ElevenLabs was more consistently correct, and the error I care about most is Voxtral's. Leaving out a dash in a booking reference is a problem when someone has to read it back. ElevenLabs' take needs less editing before I'd use it.

Voxtral lets you tell it exactly how to say a word with phoneme_hints, which maps a word to IPA phonemes. Studio also has a Pronunciations panel. I gave "Nkosi's" the sounds ŋ k ɔ s i z and regenerated the same message once.

It didn't work: the name changed from "nir-kow-see" to "nin-kaw-see": the vowel is right now, but there's an extra sound at the start. And because the fix regenerates the whole message, everything else changed too. The rand amount lost the "and" that I liked, and the booking reference lost both dashes this time. I couldn't get the name right, and the takes were very inconsistent between generations, so for me it wasn't worth the effort. You also have to write the hint in IPA, which most people won't know.

What this tests: whether each tool sounds like me from a short recording, and keeps sounding like me when the mood changes. Mistral says Voxtral can clone a voice "from as little as 2–3 seconds of audio, capturing emotion, speaking style, and accent". I'm South African, so accent drift is easy for me to hear.

I used the same recording of my voice as in my Fish and Gemini comparisons, but Voxtral rejected it:

Reference audio duration 33.90s exceeds the maximum allowed duration of 30.0s

Mistral's docs say a reference can be "a few seconds to a few minutes", so that limit came as a surprise. I cut the recording at a natural pause to 29.8 seconds and gave that file to both tools, so ElevenLabs had about four seconds less of my voice than in the earlier articles.

On Voxtral the recording is sent with each request and nothing is saved. On ElevenLabs I made a temporary instant clone with background noise removal off, then deleted it after the tests. Both clones read a passage I never recorded:

I left my keys next to the kettle again. If you're heading out, could you check whether the back door is locked? I should be home before the rain starts. Oh, and the good news: they finally approved the project! I can stop refreshing my inbox every five minutes. Let's get dinner somewhere nice tonight.

ListenKeeps my accent and tone

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ListenCleaner audio, British accent over mine

Voxtral wins clearly, because it kept my accent and tone. At 0:09 the word "finally" sounds very close to how I say it, and "They finally approved the project!" still sounded like me, without the rushed pace of its stock voice.

The ElevenLabs clone is the cleaner recording, but it doesn't sound much like me. There's a thick British accent laid over my own, and the expressive parts sound nothing like me. It's the same thing I heard in my Gemini comparison. My impression is that ElevenLabs gives up a lot of the original voice to make the clone expressive, and the result sounds more like a stock voice. Voxtral struggles with expression, but it keeps what makes the voice mine.

If I had to use one of these clones, I'd use Voxtral.

To test Mistral's short-reference claim, I also cloned on Voxtral from just the first 4.9 seconds of the same recording. ElevenLabs needs at least 10 seconds, so this one is Voxtral only.

It was surprisingly good, almost as good as the 29.8-second clone. It sounds a little flatter, but it still sounded more like me than ElevenLabs' clone from six times as much audio. That's one voice, mine, but it backs up Mistral's claim.

Only clone a voice you own or have permission to use.

Voxtral 3 supports 35 languages, with stock voices in 22 of them, so I generated a short French version of the Lisbon scene on both. It includes a date, a time and a euro amount written the French way. I don't speak French well enough to judge accent or pronunciation, so there's no verdict here, and you can listen and decide for yourself.

Je ne voulais le dire à personne. On a décroché le projet de Lisbonne ! J'ai relu l'e-mail trois fois avant d'y croire. La réunion de lancement est le 3 avril à 14 h 45, et le budget est de 1 249,50 €. Bon, n'en parle à personne avant vendredi.

The stock voices are Voxtral's Marie and ElevenLabs' Claire, a native French library voice:

Listen

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Listen

Mistral also says a cloned voice can speak languages other than the one it was recorded in. These are my two clones from the English recording, speaking French:

Listen

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Listen

The one thing I can judge is likeness: the Voxtral clone sounds like English-speaking me reading French from a piece of paper. I'm not sure that's a good thing, but for a clone made from an English recording it's more accurate than the ElevenLabs one.

I can't say for sure: Mistral doesn't publish what its free plan includes for Voxtral, and I tested on an API account with prepaid credits, so my results don't show what works for free. In the Studio website, I could generate speech with preset voices but saw no cloning option. Prices below were checked on 26 October 2026, in US dollars.

On paper, Voxtral is about six times cheaper than Eleven v4, but in practice I don't think the gap is that big. Most of the ElevenLabs takes in this article were usable as they were, and none of the Voxtral stock-voice takes were, so you'd spend more generations getting a usable Voxtral clip. The cost per usable clip ends up closer than the list prices suggest.

For scale, these tests used 1,938 characters on my ElevenLabs account, about $0.16 at API rates. The Voxtral requests, including three short samples I used to pick a voice, came to about 2,600 characters, about $0.03 at list price.

Sources: Mistral API pricing, ElevenLabs API pricing, ElevenLabs plans.

Voxtral returns MP3s without the header that tells a player how long the file is. My player showed the first clip as 16 seconds long, stopped at 14, and wouldn't replay it. I fixed every Voxtral clip in this article by rewriting the header with ffmpeg -i in.mp3 -c:a copy -write_xing 1 out.mp3, which leaves the audio untouched. If you serve Voxtral MP3s directly to users, request WAV or fix the header first.

Voxtral TTS 3, the model I tested, isn't: Mistral hasn't published its weights, and self-hosting it means contacting Mistral's sales team. The older Voxtral TTS from March 2026 has open weights on Hugging Face, but under a non-commercial lice