Project Translated Unfinished Unfinished words Unfinished characters Untranslated Checks Suggestions Comments
Immersive Translate 0% 1 5 43 1 0 0 0
Immersive Translate Site 95% 122 2,716 19,605 25 480 0 0

Overview

Language code zh_Hans
Aliased language codes chinese, chinese_chs, schinese, chinese_zh, cn, zh, zhcn, zh_cn, zh_chs, cmn, zh_hans_cn, zh_cmn_hans, chs, chi
Text direction Left to right
Number of speakers 1,266,066,359
Plural: Default plural 7 translations
Number of plurals 1
Plural type None
Plurals
Plural formula 0
Plural: Qt Linguist plural 0 translations
Number of plurals 1
Plural type None
Plurals
Plural formula 0
12 hours ago

String statistics

Strings percent Hosted strings Words percent Hosted words Characters percent Hosted characters
Total 2,526 26,002 182,382
Approved 0% 0 0% 0 0% 0
Waiting for review 95% 2,403 89% 23,281 89% 162,734
Translated 95% 2,403 89% 23,281 89% 162,734
Needs editing 3% 97 8% 2,161 8% 15,160
Read-only 0% 0 0% 0 0% 0
Failing checks 19% 480 24% 6,408 23% 43,562
Strings with suggestions 0% 0 0% 0 0% 0
Untranslated strings 1% 26 2% 560 2% 4,488
Last 12 months Previous

Activity in last 12 months

0 changes 367 changes 0 changes 221 changes 0 changes 110 changes 0 changes 85 changes 0 changes 101 changes 0 changes 53 changes 0 changes 112 changes 0 changes 1,324 changes 0 changes 137 changes 0 changes 470 changes 1,612 changes 507 changes 0 changes 11 changes
May Jun Jul Aug Sep Oct Nov Dec Jan Feb Mar Apr

Quick numbers

26,005
Hosted words
2,526
Hosted strings
95%
Translated
2
Contributors
and previous 30 days

Trends of last 30 days

−34%
Hosted words
+100%
−46%
Hosted strings
+100%
+30%
Translated
+64%
—
Contributors
+100%
User avatar None

Resource updated

  1. Immersive Translate Site
  2. Global i18n
  3. Chinese (Simplified)
The “global-i18n/zh-CN.json” file was changed. 12 hours ago
User avatar None

String updated in the repository

  1. Immersive Translate Site
  2. Global i18n
  3. Chinese (Simplified)
Month
月
12 hours ago
User avatar None

String updated in the repository

  1. Immersive Translate Site
  2. Global i18n
  3. Chinese (Simplified)
Discounted plan price {displayedPrice}
最终实付优惠后套餐价格 {displayedPrice}
12 hours ago
User avatar None

Changes committed

  1. Immersive Translate
  2. Immersive Translate Glossary
  3. Chinese (Simplified)
Changes committed 3 days ago
User avatar alaa1hawak

String added

  1. Immersive Translate
  2. Immersive Translate Glossary
  3. Chinese (Simplified)
Translate entire page/Display original text
 
4 days ago
User avatar None

Resource updated

  1. Immersive Translate Site
  2. Immersive Translate Document App
  3. Chinese (Simplified)
The “app/src/i18n/zh-CN.json” file was changed. 2 weeks ago
User avatar None

String updated in the repository

  1. Immersive Translate Site
  2. Immersive Translate Document App
  3. Chinese (Simplified)
We currently use a "translation quota" based billing method, detailed as follows:<br/><br/><ul><li>Translation quotas are charged based on the number of <b>Tokens</b> used during the translation process.</li><li>The <b>GLM-4-Flash-250414</b> model is available to all users, and every BabelDOC user receives a monthly quota of 500,000 Tokens for free model translations within BabelDOC. (Actual availability depends on the supply from upstream providers, and quotas are dynamically adjusted based on server load)</li><li>The <b>Qwen3.5-Plus/DeepSeek-V4-Flash/doubao-seed-2-0-lite/Kimi+Qwen/Kimi+DeepSeek/GLM-4.7</b> models are exclusively for <b>Pro/Max</b> members, counted towards the members' general translation quota. Pro members enjoy up to <b>20 million Tokens</b> per month, while Max members enjoy up to <b>50 million Tokens</b> per month. Failed translations are not counted towards the quota.</li></ul><br/>At the start of a translation task, the system will deduct the general translation quota in advance based on "3000 Tokens × number of pages". Once the translation is complete, we will settle based on actual consumption, refunding any excess to your account or requesting additional tokens if there is a shortfall. If any system errors occur during the translation, all pre-deducted general translation quotas will be fully refunded to your account. When the automatic term extraction feature is not enabled, the pre-deduction per page is 3000 Tokens/page. When the automatic term extraction feature is enabled, the pre-deduction per page is 6000 Tokens/page.<br/><br/>From actual usage statistics, when automatic term extraction is enabled, the average consumption is about 7381.56 Tokens per page, with the P25–P75 range being 4215.42–9490.89 Tokens; when automatic term extraction is disabled, the average consumption is about 4702.98 Tokens per page, with the P25–P75 range being 2642.38–5797.40 Tokens. Here, P25 (the 25th percentile) indicates that 25% of the pages consume fewer Tokens than this value, and P75 (the 75th percentile) indicates that 75% of the pages consume fewer Tokens than this value. The P25–P75 range is used to describe the common consumption range for most pages, thereby reducing the impact of extreme samples on the overall assessment.
我们目前采用基于“翻译额度”的计费方式，具体说明如下：<br/><br/><ul><li>翻译额度按照翻译过程中使用的 <b> Token 数量 </b> 进行计费。</li><li><b> GLM-4-Flash-250414 </b> 模型所有用户可用，所有 BabelDOC 用户每月可获得 50 万 Token 额度，用来在 BabelDOC 中使用免费模型翻译文档。（实际可用性取决于上游供应商的供应情况，额度根据服务器负载动态调整）</li><li><b> Qwen3.5-Plus/DeepSeek-V3.24-Flash/doubao-seed-2-0-lite/Kimi+Qwen/Kimi+DeepSeek/GLM-4.7 </b> 模型仅限 <b> Pro/Max </b> 会员使用，计入会员通用翻译额度，Pro 会员每月可享受 <b> 高达 2000 万 Token </b> 的翻译额度，Max 会员每月可享受 <b> 高达 5000 万 Token </b> 的翻译额度。失败的翻译不计入翻译额度。</li></ul><br/>在翻译任务启动时，系统将根据"3000 Token × 翻译页数"的计算方式预先扣除相应的通用翻译额度。待翻译完成后，我们将按实际消耗进行结算，多余额度将退还至您的账户，不足部分则需补充。若翻译过程中遇到任何系统错误，所有预扣的通用翻译额度将自动全额返还至您的账户。当不启用自动提取术语时，单页预扣 Token 数为 3000 Token/页。当启用自动提取术语功能时，单页预扣 Token 数为 6000 Token/页。<br/><br/>从实际使用统计来看，启用自动术语提取时，平均每页约消耗 7381.56 Token，其中 P25–P75 区间为 4215.42–9490.89 Token；关闭自动术语提取时，平均每页约消耗 4702.98 Token，P25–P75 区间为 2642.38–5797.40 Token。其中，P25（第 25 百分位）表示有 25% 的页面 Token 消耗低于该值，P75（第 75 百分位）表示有 75% 的页面 Token 消耗低于该值，P25–P75 区间可用于描述大多数页面的常见消耗范围，从而减少极端样本对整体评估的干扰。
2 weeks ago
User avatar None

String updated in the repository

  1. Immersive Translate Site
  2. Immersive Translate Document App
  3. Chinese (Simplified)
We currently use a "translation quota" based billing method, detailed as follows:<br/><br/><ul><li>Translation quotas are charged based on the number of <b>Tokens</b> used during the translation process.</li><li>The <b>GLM-4-Flash-250414</b> model is available to all users, and every BabelDOC user receives a monthly quota of 500,000 Tokens for free model translations within BabelDOC. (Actual availability depends on the supply from upstream suppliers, and quotas are dynamically adjusted based on server load)</li><li>Models such as <b>Qwen3.5-Plus/DeepSeek-V4-Flash/doubao-seed-2-0-lite/GPT-5-mini/Gemini-3-Flash/Kimi+Qwen/Kimi+DeepSeek/GLM-4.7</b> are exclusively for <b>Pro/Max</b> members, counted towards the members' general translation quota. Pro members enjoy up to <b>20 million Tokens</b> per month, while Max members can enjoy up to <b>50 million Tokens</b> per month. Failed translations are not counted towards the translation quota.</li></ul><br/>At the start of a translation task, the system will deduct the general translation quota in advance based on the calculation of "3000 Tokens × number of pages". Once the translation is complete, we will settle based on actual consumption, refunding any excess to your account, or requiring additional if insufficient. If any system errors occur during the translation, all deducted general translation quotas will be fully refunded to your account. When the automatic term extraction feature is not enabled, the deduction per page is 3000 Tokens/page. When the automatic term extraction feature is enabled, the deduction per page is 6000 Tokens/page.<br/><br/>From actual usage statistics, when automatic term extraction is enabled, the average consumption is about 7381.56 Tokens per page, with the P25–P75 range being 4215.42–9490.89 Tokens; when automatic term extraction is disabled, the average consumption is about 4702.98 Tokens per page, with the P25–P75 range being 2642.38–5797.40 Tokens. Here, P25 (the 25th percentile) indicates that 25% of the pages consume fewer Tokens than this value, and P75 (the 75th percentile) indicates that 75% of the pages consume fewer Tokens than this value. The P25–P75 range is used to describe the common consumption range for most pages, thereby reducing the impact of extreme samples on the overall assessment.
我们目前采用基于“翻译额度”的计费方式，具体说明如下：<br/><br/><ul><li>翻译额度按照翻译过程中使用的 <b> Token 数量 </b> 进行计费。</li><li><b> GLM-4-Flash-250414 </b> 模型所有用户可用，所有 BabelDOC 用户每月可获得 50 万 Token 额度，用来在 BabelDOC 中使用免费模型翻译文档。（实际可用性取决于上游供应商的供应情况，额度根据服务器负载动态调整）</li><li><b> Qwen3.5-Plus/DeepSeek-V3.24-Flash/doubao-seed-2-0-lite/GPT-5-mini/Gemini-3-Flash/Kimi+Qwen/Kimi+DeepSeek/GLM-4.7 </b> 模型仅限 <b> Pro/Max </b> 会员使用，计入会员通用翻译额度，Pro 会员每月可享受 <b> 高达 2000 万 Token </b> 的翻译额度，Max 会员每月可享受 <b> 高达 5000 万 Token </b> 的翻译额度。失败的翻译不计入翻译额度。</li></ul><br/>在翻译任务启动时，系统将根据"3000 Token × 翻译页数"的计算方式预先扣除相应的通用翻译额度。待翻译完成后，我们将按实际消耗进行结算，多余额度将退还至您的账户，不足部分则需补充。若翻译过程中遇到任何系统错误，所有预扣的通用翻译额度将自动全额返还至您的账户。当不启用自动提取术语时，单页预扣 Token 数为 3000 Token/页。当启用自动提取术语功能时，单页预扣 Token 数为 6000 Token/页。<br/><br/>从实际使用统计来看，启用自动术语提取时，平均每页约消耗 7381.56 Token，其中 P25–P75 区间为 4215.42–9490.89 Token；关闭自动术语提取时，平均每页约消耗 4702.98 Token，P25–P75 区间为 2642.38–5797.40 Token。其中，P25（第 25 百分位）表示有 25% 的页面 Token 消耗低于该值，P75（第 75 百分位）表示有 75% 的页面 Token 消耗低于该值，P25–P75 区间可用于描述大多数页面的常见消耗范围，从而减少极端样本对整体评估的干扰。
2 weeks ago
User avatar None

String updated in the repository

  1. Immersive Translate Site
  2. Immersive Translate Document App
  3. Chinese (Simplified)
All users currently have access to the GLM-4-Flash-250414 model for translation, while Pro users can also choose to use the Qwen3.5-Plus/DeepSeek-V4-Flash/doubao-seed-2-0-lite/GPT-5-mini/Gemini-3-Flash/Kimi+Qwen/Kimi+DeepSeek/GLM-4.7 models for translation, subject to actual availability.

After comparison, we found that Kimi-K2.5 is effective in extracting terminology, hence we are introducing the "Kimi + Qwen" and "Kimi + DeepSeek" translation services:

If you choose the "Kimi + Qwen" translation service and enable automatic terminology extraction, Kimi-K2.5 will be used to extract terminology, and Qwen3.5-Plus will be used to complete the text translation. All related consumption will be counted towards Qwen usage. (Limited time test)

If you choose the "Kimi + DeepSeek" translation service and enable automatic terminology extraction, Kimi-K2.5 will be used to extract terminology, and DeepSeek-V4-Flash will be used to complete the text translation. All related consumption will be counted towards DeepSeek usage. (Limited time test)

Since BabelDOC uses a backend translation architecture, all translation logic is executed on the server side, independent of the translation engine used by the plugin. Therefore, the range of translation engines available for BabelDOC differs from those available for immersive translation plugins, and BabelDOC only supports certain advanced translation models, not all advanced models are available.
所有用户目前均可使用 GLM-4-Flash-250414 模型进行翻译，而 Pro 用户还可额外选择使用 Qwen3.5-Plus/DeepSeek-V3.24-Flash/doubao-seed-2-0-lite/GPT-5-mini/Gemini-3-Flash/Kimi+Qwen/Kimi+DeepSeek/GLM-4.7 模型（以实际可选模型为准）进行翻译。<br/><br/>经过对比我们发现 Kimi-K2.5 提取术语效果较好，因此推出“Kimi + Qwen”和“Kimi + DeepSeek”翻译服务：<br/><br/>若选择“Kimi + Qwen”翻译服务，且启用自动术语提取，则会使用 Kimi-K2.5 提取术语，并使用 Qwen3.5-Plus 完成文本翻译。相关消耗均会计入 Qwen 消耗。（限时测试）<br/><br/>若选择“Kimi + DeepSeek”翻译服务，且启用自动术语提取，则会使用 Kimi-K2.5 提取术语，并使用 DeepSeek-V3.24-Flash 完成文本翻译。相关消耗均会计入 DeepSeek 消耗。（限时测试）<br/><br/>由于 BabelDOC 采用后端翻译架构，所有翻译逻辑均在服务器端执行，与插件所使用的翻译引擎相互独立。因此，BabelDOC 可选用的翻译引擎范围与沉浸式翻译插件存在差异，BabelDOC 仅支持部分高级翻译模型，并非所有高级模型均可使用。
2 weeks ago
User avatar None

String updated in the repository

  1. Immersive Translate Site
  2. Immersive Translate Document App
  3. Chinese (Simplified)
All users can currently use the GLM-4-Flash-250414 model for translation free of charge, while Pro users can also choose to use the Qwen3.5-Plus/DeepSeek-V4-Flash/doubao-seed-2-0-lite models for translation.
所有用户目前均可使用 GLM-4-Flash-250414 模型进行翻译，而 Pro 用户还可额外选择使用 Qwen3.5-Plus/DeepSeek-V3.24-Flash/doubao-seed-2-0-lite/Kimi+Qwen/Kimi+DeepSeek/GLM-4.7 模型（以实际可选模型为准）进行翻译。<br/><br/>经过对比我们发现 Kimi-K2.5 提取术语效果较好，因此推出“Kimi + Qwen”和“Kimi + DeepSeek”翻译服务：<br/><br/>若选择“Kimi + Qwen”翻译服务，且启用自动术语提取，则会使用 Kimi-K2.5 提取术语，并使用 Qwen3.5-Plus 完成文本翻译。相关消耗均会计入 Qwen 消耗。（限时测试）<br/><br/>若选择“Kimi + DeepSeek”翻译服务，且启用自动术语提取，则会使用 Kimi-K2.5 提取术语，并使用 DeepSeek-V3.24-Flash 完成文本翻译。相关消耗均会计入 DeepSeek 消耗。（限时测试）<br/><br/>由于 BabelDOC 采用后端翻译架构，所有翻译逻辑均在服务器端执行，与插件所使用的翻译引擎相互独立。因此，BabelDOC 可选用的翻译引擎范围与沉浸式翻译插件存在差异，BabelDOC 仅支持部分高级翻译模型，并非所有高级模型均可使用。
2 weeks ago
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