How AI Translation Performs Across Languages: What to Expect and Where to Be Careful

But translation quality is not the same for every language. High-resource languages such as German, French, Spanish or Italian usually perform very well. Smaller or morphologically complex languages such as Slovenian, Latvian, Lithuanian, Macedonian or Albanian need more careful review. Even when the translation sounds fluent, AI can make subtle mistakes in terminology, grammar, register or meaning.

Below is a practical language-by-language overview.

---

BG – Bulgarian

Bulgarian generally performs reasonably well in AI translation, especially from and into English. Since it is an EU language with a fair amount of digital content, major AI systems usually produce usable first drafts. There is limited benchmark data for Bulgarian compared with languages such as Czech, Italian or German, so it is difficult to name one consistent winner. In practice, Gemini and ChatGPT are good candidates for testing, while DeepL can be useful for fast first drafts where the language pair is supported well.

The main risk is grammar and register: Bulgarian has specific verbal forms, aspect distinctions and formal style conventions that AI may simplify. Be careful with legal, medical and technical texts, where terminology must be checked by a native reviewer.

BS – Bosnian

Bosnian is more sensitive because it is often mixed up with Croatian or Serbian. AI systems may produce a translation that is understandable but not fully appropriate for Bosnia and Herzegovina. There is little direct public benchmark evidence comparing the major LLMs specifically for Bosnian. Based on related South Slavic performance, Gemini and ChatGPT should be tested first, but no system should be trusted without native review.

Watch for Serbian or Croatian variants, terminology, formal address and regional vocabulary. For public-facing texts, native Bosnian review is strongly recommended. Also, the client should specify whether they need Bosnian or perhaps ijekavian Serbian for the Republic of Srpska.

CS – Czech

Czech performs well in current AI translation systems. WMT25 showed strong results for Czech-related language pairs, with Gemini 2.5 Pro ranking first for English→Czech and Czech→German. GPT-4.1 was also highly competitive for Czech→German, and Claude-4 was close behind in that direction. (WMT25)

Still, Czech has complex declension, agreement and word order. AI output may look natural but contain case or terminology errors. Technical and legal Czech should always be reviewed carefully.

DA – Danish

Danish is a high-resource Nordic language and usually performs well in DeepL, ChatGPT, Claude and Gemini. There is less recent public WMT-style head-to-head data for Danish than for languages such as Czech or Italian. In practical use, DeepL is often a strong choice for fast Danish first drafts, while ChatGPT and Claude are useful for tone, style and rewriting.

AI handles general business, marketing and support texts quite reliably. The main issues are tone, idiomatic phrasing and overly English sentence structure. Be careful with compound terms, medical terminology and official Danish style.

DE – German

German is one of the strongest languages for AI translation. DeepL is especially well known for German, and LLMs also perform very well. In WMT25, Gemini 2.5 Pro ranked first for Czech→German, with GPT-4.1 and Claude-4 also close behind. (WMT25)

For general German texts, DeepL, Gemini and ChatGPT are all strong options. DeepL is often excellent for polished first drafts, while ChatGPT and Gemini are useful when detailed instructions, terminology or context are needed. The risks are terminology, sentence length, formal register and country variants: Germany, Austria and Switzerland may require different wording.

EL – Greek

Greek AI translation has improved, but it still needs careful review. General meaning is usually transferred correctly, but AI can struggle with formal register, natural syntax and specialized terminology. There is limited direct public benchmark evidence for Greek in the major recent WMT results, so no clear overall winner can be named. In practical workflows, ChatGPT and Gemini are good systems to compare, while DeepL can be useful for supported general-language pairs.

Greek inflection also means that errors in agreement or case can appear even in fluent sentences. For medical, legal and technical Greek, human review is important.

EN – English

English is the strongest language for almost all AI systems because it is the most represented language in training data. Translation into English is usually fluent and often very good. For English output, ChatGPT, Claude and Gemini are all very strong; Claude is often particularly good for natural long-form style, while ChatGPT is strong for controlled rewriting and terminology-sensitive instructions.

The risk is that AI may over-polish the text and remove nuance from the source. When translating into English, check whether the result preserves the original meaning, tone and level of certainty.

ES – Spanish

Spanish is a high-resource language and performs very well. For Spanish, DeepL is often excellent for fast, fluent first drafts, while ChatGPT, Claude and Gemini are strong for adaptation, tone and context. Recent broad LLM benchmarks generally show frontier models performing very strongly on high-resource language pairs, although the best system may depend on the exact direction and domain.

The key issue is locale: Spain, Mexico, Latin America and neutral international Spanish may require different vocabulary and tone. Be careful with informal address, product terminology and regulatory language.

ET – Estonian

Estonian is smaller and more complex than many Western European languages, so AI quality is more variable. There is limited direct benchmark evidence comparing Claude, ChatGPT, Gemini and DeepL specifically for Estonian. In practice, Gemini and ChatGPT are useful candidates for testing because of their broader multilingual capabilities, but native review remains important.

The result may be understandable but not fully idiomatic. Watch for case endings, unnatural word order and literal translations from English. Human review is recommended for published or specialized content.

FI – Finnish

Finnish is challenging because of its case system, long compounds and different sentence structure. AI can produce good general Finnish, but mistakes may appear in morphology, terminology and naturalness. There is no simple public ranking that makes one model the universal winner for Finnish. For practical use, DeepL can be strong for general first drafts, while ChatGPT and Gemini are useful when terminology and instructions matter.

Medical and technical Finnish require special attention, especially where established terms already exist. Always check compound words and inflected forms.

FR – French

French is one of the strongest AI translation languages. DeepL, ChatGPT, Claude and Gemini usually produce fluent results. For French, DeepL is often one of the strongest dedicated MT choices, while ChatGPT and Claude are very useful for tone, register and rewriting. Gemini should also be tested for larger multilingual workflows because of its strong recent benchmark performance.

The main risks are formality, gender-inclusive language, punctuation conventions and country variants such as France, Belgium, Switzerland and Canada. Marketing texts may need human adaptation to avoid sounding generic.

HR – Croatian

Croatian AI translation is often usable, but it must be reviewed carefully. There is limited direct public benchmark data for Croatian compared with Serbian or Czech. Because of related-language interference, no model should be treated as automatically safe. Gemini and ChatGPT are good candidates for first testing, while DeepL can be useful depending on the language pair.

One frequent issue is interference from Serbian or Bosnian. AI may choose words that are understandable but not standard Croatian. Check terminology, case endings, formal address and official style. For legal, public-sector or technical Croatian, native review is essential.

HU – Hungarian

Hungarian is difficult for AI because its structure differs strongly from English and many other European languages. General translations can be good, but word order, suffixes, possessive forms and terminology may be problematic. There is no clear recent public winner across all Hungarian translation directions. In practice, ChatGPT and Gemini are useful for controlled translation and QA, while DeepL can provide good general first drafts.

Be especially careful with technical instructions, medical texts and legal obligations. A fluent Hungarian AI translation may still need substantial editing.

IT – Italian

Italian performs very well in AI translation. WMT25 showed top systems such as Gemini 2.5 Pro and GPT-4.1 clustered very closely for English→Italian, with Gemini 2.5 Pro scoring 79.4 and GPT-4.1 scoring 79.0. Claude-4 was lower in that specific ranking. (WMT25)

For Italian, Gemini and GPT-4.1/ChatGPT have strong benchmark support, while DeepL remains a very good practical first-draft engine. The main risks are tone, elegance, legal precision and terminology. Italian often needs stylistic adaptation rather than literal translation.

LT – Lithuanian

Lithuanian is a smaller and morphologically complex language. AI can provide a useful draft, but the risk of grammar and terminology errors is higher than in major Western European languages. There is limited direct public benchmark evidence for Lithuanian among the major LLMs, so it is best to compare outputs. Gemini and ChatGPT are good candidates for testing, especially when context and instructions are important.

Watch for case endings, agreement, word order and specialized terminology. Native review is strongly recommended for publication.

LV – Latvian

Latvian AI translation is improving, but quality can vary depending on domain. General meaning is usually understandable, but inflection, terminology and natural phrasing may need correction. There is no clear public ranking that identifies one best LLM for Latvian. In practical workflows, Gemini and ChatGPT are useful to compare, while DeepL may be suitable for supported general-language translation.

Be careful with formal texts, public communication and technical manuals. Latvian should not be published without native review.

MK – Macedonian

Macedonian is a lower-resource European language, so AI translation needs caution. Output may be understandable but less idiomatic, and terminology may be inconsistent. There is very limited direct public benchmark data for Macedonian. Gemini and ChatGPT are likely the most useful systems to test first because of their broader multilingual abilities, but native review is essential.

AI may also be influenced by Bulgarian or Serbian patterns. For official, legal, medical or technical Macedonian, native expert review is strongly recommended.

NL – Dutch

Dutch performs well in AI translation. DeepL and the major LLMs usually produce fluent Dutch for business, marketing and general texts. For practical workflows, DeepL is often a strong fast first-draft option, while ChatGPT, Claude and Gemini are useful for tone, context and terminology.

The main risks are tone, compound terms, Anglicisms and the difference between Dutch for the Netherlands and Flemish usage in Belgium. Review is needed for brand voice and specialized terminology.

NO – Norwegian

Norwegian performs well, but users must specify whether they need Bokmål or Nynorsk. AI usually defaults to Bokmål. There is limited recent public head-to-head data for Norwegian among the major LLMs. In practice, DeepL can be strong for general Bokmål first drafts, while ChatGPT and Claude are useful for adapting tone and improving naturalness.

General translation quality is good, but terminology, tone and official style should be checked. For public texts, healthcare, finance or technical documentation, native review is recommended.

PL – Polish

Polish is relatively well supported and AI translation can be strong. DeepL is widely used for Polish, and LLMs such as ChatGPT and Gemini are also strong when context and instructions are needed. There is no single public benchmark result that makes one model the clear winner for all Polish translation tasks.

However, Polish grammar is complex, especially case, gender and aspect. AI can produce fluent sentences that still contain agreement or terminology errors. Be careful with legal, medical and technical content. Marketing Polish often needs human polishing to sound natural.

PT – Portuguese

Portuguese performs very well in AI translation, but locale is critical. For Portuguese, DeepL is often strong for fast first drafts, while ChatGPT, Claude and Gemini are useful for adapting tone and specifying European vs Brazilian usage. Frontier LLMs generally perform very well on high-resource language pairs, but the best system depends on whether the target is European Portuguese or Brazilian Portuguese.

AI may default to Brazilian Portuguese unless instructed otherwise. For Portugal-specific communication, always specify European Portuguese and review the output for local usage.

RO – Romanian

Romanian is moderately well supported. AI usually handles general Romanian texts well, but specialized terminology and formal style require review. The EU20 automated QA study included Romanian among the European benchmark languages used to compare translation quality signals across systems including DeepL, ChatGPT and Google/human-edited data. (EU20 QA study)

There is no simple winner for Romanian, but ChatGPT and Gemini are good choices where context and instructions matter, while DeepL can be useful for quick first drafts. Be careful with legal and medical wording, gender agreement and literal phrasing from English.

RU – Russian

Russian is a high-resource language, and AI systems generally perform well. ChatGPT, Gemini and DeepL can all produce strong Russian first drafts, depending on the domain and direction. Claude is also useful for naturalness and rewriting. Public benchmark leadership varies by test and direction, so system choice should be validated on a sample.

The main risks are register, aspect, case government and politically or culturally sensitive wording. For technical and legal texts, terminology must be checked carefully. AI may also choose wording that is grammatically correct but not the preferred professional term.

SK – Slovak

Slovak is related to Czech, but it should not be treated as interchangeable. AI can produce good Slovak drafts, but Czech interference is a risk. There is less direct benchmark evidence for Slovak than for Czech. In practice, ChatGPT and Gemini are good systems to test, while DeepL can be useful for general translation.

Check terminology, declension, official wording and natural word order. For formal or technical Slovak, human review is important.

SL – Slovenian

Slovenian needs careful handling. AI can produce fluent Slovenian, but errors often appear in case, dual forms, agreement, terminology and idiomatic phrasing. There is limited direct public benchmark evidence for Slovenian among the major LLMs. In practical workflows, ChatGPT and Gemini are usually worth testing first because they can follow detailed terminology and formatting instructions; DeepL can also be useful for general first drafts.

Because Slovenian is smaller than German, French or Spanish, AI output is less predictable. For marketing, AI can be a good starting point; for legal, medical, technical or public-sector texts, professional review is essential.

SQ – Albanian

Albanian is a lower-resource language in AI translation. The output may transfer the general meaning, but terminology, grammar and natural style can be unreliable. There is very limited direct benchmark evidence for Albanian, so no clear best model can be named. Gemini and ChatGPT are good first systems to compare, but native review is necessary.

AI may also struggle with formal register and domain-specific wording. Use AI as a draft only and always involve a native reviewer for publication.

SR – Serbian

Serbian performed very strongly in WMT25 for English→Serbian Cyrillic. Gemini 2.5 Pro ranked first, GPT-4.1 was also very strong, and Claude-4 scored highly as well. (WMT25)

For Serbian, Gemini currently has the strongest benchmark evidence, with ChatGPT/GPT-4.1 also close behind. Still, Serbian requires careful control of script, region and standard: Cyrillic or Latin script must be specified, and Serbian should not be mixed with Croatian or Bosnian. Check terminology and formal style before publication.

SV – Swedish

Swedish is a high-resource Nordic language and AI translation quality is generally strong. DeepL is often a reliable first-draft option for Swedish, while ChatGPT and Claude are useful for tone, rewriting and controlled terminology. Gemini should also be considered in multilingual workflows because of its strong recent benchmark performance.

General business and marketing texts often need only moderate editing. The main risks are terminology, overly English syntax, tone and consistency in technical or medical documents. Swedish also requires careful handling of compounds and established product terms.

ZH – Chinese

AI translation into Chinese can be strong, especially for general, business and technical content. In WMT25 for English→Chinese, the ranking was led by Algharb with a score of 88.4, followed by Claude-4 with 86.9. DeepSeek-V3 scored 85.0 and was placed in the 3–6 rank range, ahead of GPT-4.1 at 84.0 and Gemini 2.5 Pro at 83.8 in that specific test. WMT25

This means DeepSeek-V3 is a strong candidate for Chinese translation, but not the top-scoring system in that WMT25 English→Chinese ranking. Claude-4 performed better in that specific test, while GPT-4.1 and Gemini 2.5 Pro were slightly lower. As always, the best system should still be tested on a real project sample. Locale and script must also be specified: Simplified Chinese or Traditional Chinese. Be careful with marketing tone, cultural adaptation, technical terminology and legal wording.

When translating between Chinese and other European languages, the translation tends to go over English, reproducing common errors from Chinese-English translations.

Final recommendation

AI translation works best when it is used as part of a controlled workflow. For high-resource languages, it can save significant time and produce strong results. For smaller or more complex languages, it is still useful, but it must be reviewed more carefully.

A safe multilingual workflow is:

1. Choose the right engine for the language pair.
2. Provide terminology and style instructions.
3. Specify locale, script and formal/informal address.
4. Review the output with a native linguist.
5. Use extra checks for legal, medical, technical and safety-related content.

AI translation is no longer just an experimental tool. It is now a serious productivity layer for multilingual communication. But the final quality still depends on knowing where each language is strong, where it is risky and when human expertise is needed.