QWEN3-Max-Preview vs CHATGPT5 vs Gemini 2.5 PRO vs Deepseek v3.1

Comparative Review of AI Language Models for Subtitle Translation: QWEN3-Max-Preview, ChatGPT-5, Gemini 2.5 PRO, and DeepSeek v3.1

In the rapidly evolving landscape of artificial intelligence, selecting the right language model for specific tasks can be challenging. Recently, I undertook an informal evaluation of four notable AI language models to determine their effectiveness in translating subtitles from English to Mandarin Chinese. This comparison focused specifically on handling .srt transcript files, a common format for video subtitles, spanning approximately 150 to 250 lines for videos of 5 to 10 minutes.

Background and Motivation

My previous experience largely involved using Gemini 2.5 Flash to perform such translations. While effective initially, I noticed increasing inconsistencies, particularly with timestamp accuracy and output quality. Consequently, I decided to explore alternative models to find a more reliable solution.

Methodology

For this review, I input the same transcript into each model, observing how well they maintained timestamp integrity, translation accuracy, and overall usability. The evaluations were conducted using free and paid versions of each platform when applicable, acknowledging that some limitations exist in free tiers.

Findings

• Gemini 2.5 Flash
  As a long-standing tool in my workflow, Gemini 2.5 Flash typically handled subtitle translation efficiently. However, recent updates have introduced notable issues. During my latest attempts, timestamps became misaligned—extra minutes were added, causing the subtitles to fall out of sync upon editing. Despite multiple retries, these problems persisted. Previously, manual timestamp adjustments or dividing the transcript into smaller segments sufficed, but the recent regressions diminish its reliability.

• Gemini 2.5 PRO
  Upgrading to the Pro version improved timestamp preservation and delivered more consistent results. The translation quality scored approximately 6.5 out of 10—a decent baseline but with noticeable gaps. It occasionally missed colloquial expressions and translated line-by-line rather than capturing the overall context, leading to less natural results.

• ChatGPT-5 (Plus Subscription)
  Despite high expectations, ChatGPT-5 proved limited for extensive subtitle translation. It could process only about 50 lines at a time before halting. Attempting to continue the task often resulted in hallucinations or extraneous outputs, such as separate downloadable documents containing partial translations. As a result, I found it unsuitable for sizeable subtitle projects, especially when seamless context preservation is required.

• **Deep