This week, 215 translation tasks were completed by 4 models. A sample of 3 articles was selected for blind multi-model comparison. Best overall: claude-sonnet-4.6 (average score: 9/10).
This Week’s Translation Statistics
| Model | Language | Translation Volume | Average Time | Average Quality Score |
|---|---|---|---|---|
| deepseek-v4-flash | en | 45 | 31.8s | Not evaluated |
| claude-sonnet-4.6 | ja | 169 | 38.3s | Not evaluated |
| native-english | en | 1 | - | Not evaluated |
Sample Comparison Evaluation
Evaluation 1: WDCD Stress Induction: Why "The Boss Needs It Urgently" Can Break Through Large Models
| Model | Accuracy | Fluency | Terminology | Readability | Total Score |
|---|---|---|---|---|---|
| deepseek-v4-flash | 9 | 8 | 9 | 8 | 8 |
| deepseek-v4-pro | 9 | 9 | 9 | 9 | 9 |
| gpt-o3 | 6 | 8 | 8 | 8 | 7 |
deepseek-v4-flash
✓ Biggest strength: When translating the effect of stress induction, it accurately captured the logic of the source text. For example, “They wrote UPDATE products SET price = price * 0.3—not 30% off, not 50% off, but 70% off” clearly explains the discount calculation error and improves comprehensibility.
✗ Biggest flaw: The title was translated as “WDCD pressure induced,” where “induced” should be “induction,” making the terminology imprecise and slightly awkward.
deepseek-v4-pro
✓ Biggest strength: The overall structure is smooth. The title “WDCD Pressure Induction: Why "Boss Urgently Needs" Can Break Through Large Models” is faithful to the source text, natural in translation, and avoids stiff phrasing.
✗ Biggest flaw: The content is truncated at “Why can the four words "client urgently needs" break through a numerical constraint?”, causing some information to be left untranslated and affecting completeness.
gpt-o3
✓ Biggest strength: When describing model failure, it uses “8 out of 11 models directly generated non-compliant SQL,” maintaining consistent terminology and highlighting the quantitative effect of the data.
✗ Biggest flaw: The subsection title “"The client urgently needs a 70% discount"” mistranslates the original 30% as 70%, distorting the core scenario of stress induction.
Conclusion: Version B is the best overall, with the highest accuracy and fluency; Version C contains a clear mistranslation and is not recommended; A and B are similar, but B is more complete.
Evaluation 2: Hantavirus Outbreak on a Cruise Ship: Key Information at a Glance
| Model | Accuracy | Fluency | Terminology | Readability | Total Score |
|---|---|---|---|---|---|
| claude-sonnet-4.6 | 9 | 9 | 9 | 9 | 9 |
| deepseek-v4-pro | 8 | 8 | 8 | 7 | 8 |
| gpt-o3 | 9 | 9 | 9 | 7 | 8 |
claude-sonnet-4.6
✓ Biggest strength: Strong terminology consistency. For example, “ハンタウイルス心肺症候群” accurately matches the professional term, maintaining consistency with the technical nature of the source text.
✗ Biggest flaw: Some sentences are slightly lengthy. For example, “これは異例の事件です。クルーズ船でのハンタウイルスの集団感染は極めて稀だからです” has good logical flow but could be more concise, causing slight reading fatigue.
deepseek-v4-pro
✓ Biggest strength: Good fluency. For example, “クルーズ船でのハンタウイルス発生は極めてまれであり、異常な出来事です” is natural and idiomatic, avoiding a stiff translation style.
✗ Biggest flaw: The text is incomplete. For example, the ending is truncated at “特にハンタウ,” resulting in missing paragraph structure and affecting the overall logical flow.
gpt-o3
✓ Biggest strength: High accuracy. For example, “ハンタウイルス心肺症候群へ進行した” faithfully conveys the meaning of symptom progression in the source text, with no additions or omissions.
✗ Biggest flaw: Readability is limited because the text is incomplete. For example, the ending is truncated at “今回ハンタウイルスが登場したことで、クルー,” so the paragraph logic is not fully presented.
Conclusion: The three versions are similar in overall quality. Version A is slightly better in completeness and readability and is recommended as the first choice; Versions B and C are accurate, but their overall performance is affected by truncation.
Evaluation 3: Perplexity AI Agent Desktop App Officially Arrives on Mac
| Model | Accuracy | Fluency | Terminology | Readability | Total Score |
|---|---|---|---|---|---|
| claude-sonnet-4.6 | 9 | 8 | 9 | 9 | 9 |
| deepseek-v4-pro | 8 | 9 | 8 | 8 | 8 |
| gpt-o3 | 9 | 9 | 9 | 9 | 9 |
claude-sonnet-4.6
✓ Biggest strength: It handles quoted passages naturally and smoothly. For example, “私たちは、AIが『問い-答え』ツールであるという限界を打破したいと考えています” faithfully conveys the intent of the source text without adding unnecessary explanation.
✗ Biggest flaw: Some sentences are slightly lengthy. For example, “このアプリは、私たちとコンピュータの対話方法を根本的に変えるものだ——単なる問答ボットではなく、文脈を理解し、複雑な操作を主体的に実行できるエージェントシステムである” causes a slight pause when reading.
deepseek-v4-pro
✓ Biggest strength: Consistent use of terminology. For example, “AIエージェント” is used consistently throughout, avoiding confusion, and is naturally integrated into sentences such as “AIエージェントアプリ「Personal Computer」,” enhancing the professional feel.
✗ Biggest flaw: Some sentence structures are slightly awkward. For example, “PerplexityのCEOであるAravind Srinivas氏はブログで次のように述べている：「私たちはAIを「質問-回答」ツールの限界を超えさせたいと考えている” uses quotation marks inconsistently, affecting fluency.
gpt-o3
✓ Biggest strength: Strong readability. The title is handled independently and attractively, for example “PerplexityのAIエージェント・デスクトップアプリがMacに正式登場,” making the overall structure clearer and helping readers quickly grasp the topic.
✗ Biggest flaw: Some parts are translated slightly too literally. For example, “私たちは、AIが『質問と回答』のツールにとどまる限界を打ち破りたいと考えています” has a mild translationese feel, affecting idiomatic naturalness.
Conclusion: The three versions are comparable in overall quality. Versions A and C are slightly better in accuracy and readability and are suitable for official publication; if fluency is the priority, Version B can also be considered.
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