Picture the pitch that gets a lot of small business owners and marketers to sign up for HeyGen or Synthesia in the first place: upload a script once, pick a language, and get a polished spokesperson video for a market you don't speak the language of.
175+
languages HeyGen advertises
140+
languages Synthesia lists
Neither number is fabricated. But a meaningful share of the disappointment reviewers describe shows up exactly at the point where someone actually generates that Mandarin, Thai, or Arabic version and watches it back.
I haven't used either platform myself, so this is built from third-party testing reports, user reviews, and both companies' own published feature pages, not from generating these videos personally. What's worth understanding isn't a vague "it's worse in other languages" — it's specifically which languages, why, and which of the two tools handles which better, because the honest answer is genuinely different depending on where your audience is.
It's Not "Non-English." It's Specifically Tonal Languages
Testing across both platforms consistently turns up a particular pattern: the languages that give these avatars the most trouble aren't just "not English" — they're tonal and rhythmically different languages like Mandarin, Thai, Vietnamese, and Arabic.
One detailed test described the failure mode precisely: on these languages, the voice track moves ahead of the avatar's mouth, the jaw reacts a beat late, and the sentence looks technically correct but rhythmically borrowed — like watching someone enthusiastically mimic a language they don't actually speak.
That's a meaningfully different problem than "the AI is bad at foreign languages" as a blanket statement. A well-executed French or German video from the same tools can look genuinely clean. The gap opens specifically around languages where pitch and tone carry meaning in ways that don't map neatly onto the mouth-shape patterns these lip-sync models were primarily trained on.
Why This Happens
Lip-sync models work by matching phonemes — individual speech sounds — to corresponding mouth shapes, trained on enormous datasets of recorded speech paired with video. Most of that foundational training data skews toward languages with relatively steady rhythm and clearly separable sounds. Tonal languages layer meaning onto pitch contour in a way that doesn't correspond to a simple one-to-one phoneme-to-mouth-shape mapping, and languages like Arabic carry distinctive jaw and throat articulation patterns that differ substantially from the training-heavy languages. The models can still process and translate the words correctly; what breaks down is the physical performance of saying them convincingly.
Screenshot: independent HeyGen multilingual testing review
Which Tool You Pick Actually Depends on Your Target Market
Here's the part that most "which is better" comparisons flatten into a single verdict, when the actual testing data says otherwise. Independent side-by-side testing scored both platforms across language groups, and the results split by region rather than one tool simply winning everywhere:
| Category |
HeyGen |
Synthesia |
| Lip sync (English) |
4.2 / 5 |
4.0 / 5 |
| Lip sync (European languages) |
3.7 / 5 |
4.1 / 5 |
| Lip sync (Mandarin, Japanese) |
Rated notably stronger |
Rated notably weaker |
HeyGen has clearly invested more heavily in Asian-language training data, and it shows in testing — Mandarin and Japanese output came out ahead of Synthesia's in the same comparisons. Synthesia, on the other hand, tested more consistently on French and German, with cleaner consonant shaping and what testers described as more polished voice quality in those languages specifically.
In practical terms: if your target audience is in East Asia, the testing data points toward HeyGen. If it's in Western Europe, it points toward Synthesia. Neither platform is simply "the better one" for multilingual work in general — the honest answer depends entirely on which market you're actually trying to reach, which is a detail most marketing pages (and a lot of comparison articles) don't spell out.
A Separate Problem: Accent and Tone Don't Always Translate Even Within English
There's a related issue that has nothing to do with lip-sync mechanics at all, and it shows up even without crossing into a different language. Testing that pushed these tools across regional English accents found that the performance itself can feel culturally mismatched.
British script + American accent
Came across as oddly over-enthusiastic, almost like a supermarket commercial.
American script + British tone
Read as unintentionally sarcastic despite polite delivery.
That's worth separating clearly from the tonal-language lip-sync issue above, because it's a different kind of failure. The words are correct, the mouth movements can even be accurate, but the performance — the emotional register a native speaker would expect for that script — doesn't transfer automatically just because the platform supports the accent. For a small business trying to sound trustworthy or professional to an unfamiliar market, this is the kind of mismatch that's easy to miss until a native speaker actually reviews the output.
The Cost Wrinkle Worth Knowing Before You Budget
There's also a billing detail that catches people out specifically on this feature: on both platforms, translation and lip-sync are metered through credits, and lip-sync is where the meter runs fastest.
~10 min
dubbing per month on Synthesia Starter, without lip-sync
→
~5 min
the same plan with lip-sync switched on
Synthesia's entry-level Starter plan (roughly $29 a month, or about $18 on annual billing) includes AI dubbing, but its monthly credit allowance is small, and third-party breakdowns of the credit system report that lip-synced dubbing consumes twice the credits per minute of dubbing without lip-sync. Run the math on a 1,200-credit monthly allowance and lip-sync cuts your usable dubbing time roughly in half. HeyGen's own documentation is similarly direct that lip-synced video translation draws from its premium credits rather than its standard allowance — and since May 15, 2026, new HeyGen customers are on credit-based plans rather than the older unlimited structure that a lot of still-ranking comparison articles describe.
Neither of these is a hidden gate. Both are things you can find if you go looking. But a headline like "175+ languages" or "140+ languages" says nothing about how many actual minutes of lip-synced, translated video your plan will produce before the credits run out, which is the number that determines whether the tool is practical for a real campaign.
What Actually Helps
Given all of the above, a few concrete steps are more useful than a blanket recommendation:
Generate a short test clip in your actual target language before committing a full script or budget to either platform — a 30-second sample will surface tonal-language jaw lag or an accent mismatch far more cheaply than discovering it in a finished campaign video.
If your target language is one of the tonal or rhythmically distinct ones prone to this issue, weigh whether burned-in subtitles are worth adding regardless of lip-sync quality; several reviewers note that strong auto-captions meaningfully reduce how much a slightly-off lip-sync bothers a viewer, since attention shifts to reading rather than lip-reading.
Before subscribing specifically for multilingual output, work out how many minutes of lip-synced translation your plan's credits actually cover on the platform you're considering — the gap between the headline language count and the real minutes you can produce can be substantial, and it isn't always obvious from the pricing page.
The Broader Point
"Support for 175+ languages" is a true statement and also an incomplete one. It describes translation and voice coverage, not uniform lip-sync and performance quality across every one of those languages — and the gap between the two is exactly where a lot of buyers get burned after the fact rather than before. For anyone building content for a market outside their own language, the useful question isn't "does this tool support my language" — it's "how well does this specific tool perform in this specific language family."
This account draws on independent multilingual testing reports for HeyGen and Synthesia, both companies' published pricing and feature pages, and user reviews from G2, PeerSpot, and ProductHunt through 2026. Avatar video platforms update their language models frequently, so a language pairing that struggled in these reports may have improved by the time you're reading this — testing your specific target language directly is still the most reliable check.
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