Localize your product into Traditional + Simplified Chinese with AI

If you're an English-first product trying to reach the 1.4 billion Chinese-reading market, you've probably been quoted $0.10-0.20 per word by a translation agency, looked at your 50,000-word product copy, and quietly closed the tab. Or you've used Google Translate, shipped it, and gotten emails saying your 'Pro plan' menu reads like a stroke happened.

This is the middle path. You can do good Traditional Chinese (zh-TW) and Simplified Chinese (zh-CN) localization with an LLM as the translator, a glossary, and a couple hours of human review per major product surface. It won't match a top-tier human team, but it'll be 80-90% there for 5% of the cost — and good enough for most B2B SaaS, consumer apps, and content sites.

Before you touch any tool: understand the two markets

zh-TW (Taiwan, Hong Kong, Macau, overseas Chinese) and zh-CN (mainland China, Singapore) are not the same language with different characters. They're closer than US English vs UK English but further apart than people assume. Examples:

Software — zh-TW: 軟體 / zh-CN: 软件
Video — zh-TW: 影片 / zh-CN: 视频
Default — zh-TW: 預設 / zh-CN: 默认
Network — zh-TW: 網路 / zh-CN: 网络
File — zh-TW: 檔案 / zh-CN: 文件 (note: 文件 in zh-TW means 'document', a different concept)

If you only do one — pick the one that matches your real audience. If your customers are in Taiwan, zh-CN copy reads as imported and slightly off-putting. If they're in mainland China, zh-TW reads as old-fashioned. Don't auto-convert simplified to traditional with a character mapper and call it done.

The actual workflow that works

Step 1: build a glossary first. Before translating anything, list 30-50 of your product's key terms — feature names, plan names, action verbs, navigation items. Decide each in both zh-TW and zh-CN. 'Workspace' is 工作區 in TW but 工作区 in CN. 'Onboarding' has no clean single-word translation; pick one and commit. This glossary becomes the most important asset in your whole localization process.

Step 2: pick the right model. Claude 4.5 / 4.6 Sonnet, GPT-5, and Gemini 2.5 Pro all do good Chinese. For zh-TW specifically, Claude has a slight edge in Taiwan-natural phrasing in our testing — others sometimes leak mainland word choices in. For zh-CN, all three are comparable. DeepSeek V3.5 and Qwen 3 are great cheap options for high-volume bulk translation.

Step 3: structure your prompt. A prompt that consistently gets you native-feeling Chinese has four parts: (1) explicit locale ('Translate to Traditional Chinese as used in Taiwan, NOT mainland China'), (2) the glossary, (3) tone notes ('product UI strings, concise and friendly, ≤6 chars when possible'), (4) the source. Bad prompt: 'Translate to Chinese.' Good prompt: a 200-word system prompt + your strings.

Step 4: translate in batches with context. Don't feed a UI string in isolation. Group related strings (whole settings page, whole onboarding flow) and translate together so the model can pick consistent vocabulary. UI strings benefit from including the screen they appear on. Marketing copy benefits from including the page heading and intent.

Step 5: run a glossary check. Programmatically check that all glossary terms in the source were translated to the agreed term. Mismatches go back through a re-translate pass with the glossary re-emphasized.

Step 6: get one native speaker review per locale. Two hours from one fluent reviewer per locale catches 90% of remaining issues. Have them rank issues by severity: 'will confuse a user' > 'unnatural but understandable' > 'minor preference'. Fix the first two, ship the third.

What AI translation handles well

UI strings, button labels, navigation
Documentation and help center articles
Marketing landing copy if you give it tone direction
Email templates
Error messages (give the model the user context)
Long-form blog posts (with one human review pass)

What it still struggles with

Legal copy. Don't auto-translate your terms of service. Get a lawyer or licensed legal translator.
Brand voice that's intentionally weird. If your English copy uses inside jokes, references, or unusual rhythm, AI will smooth it into generic SaaS Chinese. You need a human who understands your voice.
Anything with cultural sensitivity (humor about politics, religion, history). Mistakes here can land you in actual trouble in mainland China specifically.
Pricing and plan names. Direct translation of '$9/mo Pro plan' into Chinese works fine; cleverly named tiers ('Hobbyist' / 'Hacker' / 'Hero') usually don't. Decide whether to keep English names or rename for the locale.

When NOT to use this approach

If your product copy is under 5,000 words total, just hire a freelance native translator on Upwork for $400-800. The setup overhead of doing AI localization right (glossary, prompts, review) only pays off at scale.

If you're an enterprise product where copy mistakes can cost a deal — financial services, healthcare, regulated industries — get human translators for the customer-facing surfaces. Use AI for the internal admin panel where 'good enough' is genuinely fine.

If your customers will see the language switcher and judge your product based on how 'Chinese-feeling' the experience is, do not skimp. The first impression of a half-translated app with mainland word choices on a Taiwanese audience tells them you don't take their market seriously.