DeepL vs Google Translate vs ChatGPT: Translation Test
Can Google Translate beat LLMs on tough idioms? We tested GPT-6.1, Claude, Gemini, DeepSeek, and Google Translate on tricky Polish expressions.
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On a passage packed with Polish idioms, Google Translate literally translated 7 out of 14 challenging phrases, whereas modern large language models (GPT-6.1 Sol, Claude Sonnet 5.5, Gemini 3.8 Flash) made between zero and one minor shift in meaning. Numbers, currencies, and dates were handled flawlessly across all tools. DeepL was not included in the measured benchmark because its free API requires an authentication key, but its features and pricing are compared below. You can explore everything about DeepL in our dedicated guide to DeepL. For a broader benchmark (70 sentences spanning legal, medical, tech, and slang, featuring 8 translation engines including DeepL), see our roundup of the best AI translators.
How the Benchmark Was Conducted
I wrote three paragraphs (143 words) packed with common translation traps: 13 idioms, gross and net currency amounts, decimal commas, a European date format (15.11.2026), a specific time of day, and a specific grammatical noun referring to a female HR officer that lacks a direct single-word equivalent in English. On October 3, 2026, each tool was given the exact same Polish input with instructions to translate it into natural English:
- Google Translate - the public, free web endpoint (no API key required), processed paragraph by paragraph.
- GPT-6.1 Sol, Claude Sonnet 5.5, Gemini 3.8 Flash, DeepSeek V4.1 Flash - accessed via OpenRouter at temperature 0, using an identical translation prompt.
- Bielik 11B - a Polish-focused open model run locally via Ollama on an Nvidia RTX 4090 GPU.
Here is an English translation of the test passage used in the benchmark (the original test was conducted strictly using the Polish text):
The boss promised us pie in the sky: a 15% raise starting July 1, 2026, and a gross bonus of 2,500 original Polish currency units. It ended as usual - too little, too late, with a measly 3.5% in October. The HR officer just shrugged her shoulders, and I stopped putting on a brave face.
At the meeting with the client from Gdańsk, everything went like clockwork, even though everyone had been on pins and needles earlier. The client ordered 1,200 units at 49.99 original Polish currency units net with delivery by 15.11.2026. There is no use counting our chickens before they hatch, but if they pay on time, we will break even.
My grandfather used to say that the early bird catches the worm, but he himself slept like a log until 10:30. He would drink half a liter of coffee, read the sports paper from cover to cover, and when grandmother asked him to take out the trash, he replied that it was not his cup of tea. He is 87 years old and still keeps his finger on the pulse.
I evaluated 20 checkpoints: 14 tricky idiomatic phrases and contextual pronoun references, alongside 6 sets of numerical figures and dates. A correct, natural translation earned 1 point, a slight shift in nuance earned 0.5 points, while a literal, erroneous, or omitted translation received 0 points.
Benchmark Results
| Meaning of the Polish test fragment (English explanation) | Google Translate | GPT-6.1 Sol | Claude Sonnet 5.5 | Gemini 3.8 Flash | DeepSeek V4.1 | Bielik 11B |
|---|---|---|---|---|---|---|
| Empty promises | pears on willow ✗ | the moon ✓ | the moon ✓ | pie in the sky ✓ | the moon ✓ | grapes on the trees ✗ |
| Too little, too late | mustard after dinner ✗ | too little, too late ✓ | ✓ | ✓ | ✓ | ✓ |
| The HR officer shrugged helplessly | the staff threw up their hands ✗ | the HR officer ✓ | the HR woman ✓ | the HR lady ✓ | HR ✓ | the HR manager ✓ |
| Putting on a brave face | a good face for a bad game ✗ | a brave face ✓ | ✓ | ✓ | ✓ | stopped pretending ✓ |
| Smoothly / like clockwork | smoothly ✓ | like clockwork ✓ | without a hitch ✓ | ✓ | ✓ | smoothly ✓ |
| On tenterhooks | on tenterhooks ✓ | on edge ✓ | on pins and needles ✓ | ✓ | ✓ | on edge ✓ |
| Counting chickens before they hatch | splitting the skin of a bear ✗ | count our chickens ✓ | ✓ | ✓ | ✓ | ✓ |
| We will break even | break even ✓ | break even ✓ | come out ahead ½ | come out ahead ½ | break even ✓ | be in the black ½ |
| The early bird… | God gives to those who get up in the morning ✗ | the early bird catches the worm ✓ | ✓ | ✓ | ✓ | ✓ |
| Slept like a log | slept like the dead ✓ | like a log ✓ | ✓ | ✓ | ✓ | omitted ✗ |
| From cover to cover | from cover to cover ✓ | ✓ | ✓ | ✓ | ✓ | ✓ |
| Not his cup of tea | not his cup of tea ✓ | wasn’t his thing ✓ | ✓ | ✓ | wasn’t his job ✗ | wasn’t his department ½ |
| Keeps a finger on the pulse | finger on the pulse ✓ | ✓ | ✓ | ✓ | ✓ | ✓ |
| The narrator's grandmother | his grandmother ✗ | Grandma ✓ | my grandmother ✓ | Grandma ✓ | Grandma ✓ | my grandmother ✓ |
| 6 groups of numbers and dates | 6/6 | 6/6 | 6/6 | 6/6 | 6/6 | 6/6 |
| Total (out of 20) | 13 | 20 | 19.5 | 19.5 | 19 | 17 |
| Response Time | 3.6 s | 9.5 s | 3.8 s | 11.6 s | 18.3 s | 335 s* |
| Cost | $0 | $0.0043 | $0.0042 | $0.0084 | $0.0016 | $0 |
* Bielik ran on a local GPU that was concurrently handling another workload, inflating its processing time. The combined OpenRouter API calls cost a total of $0.0185.
Key Takeaways
Numbers and Dates Are No Longer Stumbling Blocks
In previous years, automated translators frequently mismanaged decimal commas (leaving “3,5%”) or converted space-separated thousands (“2 500”) into invalid formats. In this test, every tool accurately rendered “2,500 gross in original Polish currency units”, “3.5%”, “1,200 units”, “49.99 net in original Polish currency units”, and “November 15, 2026” (with Claude opting for British style: “15 November 2026”). GPT-6.1 Sol went a step further, appending “each, excluding tax” alongside the net pricing, offering clearer clarity for an English-speaking reader.
Idioms Separate Traditional Engines from LLMs
Google Translate often translates idioms word for word. While an English reader might piece together the meaning of “God gives to those who get up in the morning”, expressions such as “pears on willow” or “mustard after dinner” become incomprehensible nonsense. LLMs identify the underlying metaphorical meaning and substitute appropriate cultural equivalents (such as counting chickens before they hatch instead of skinning an unhunted bear).
Narrative Context and Personification
The most revealing error in Google Translate was not an idiom, but narrative context. In the final paragraph, the grandmother mentioned is the narrator’s grandmother. Google translated the phrase as “his grandmother” (implying she was the grandfather’s grandmother). Sentence-by-sentence statistical translation fails to retain narrative perspective. Because LLMs process the entire passage at once, they made no such mistakes. Similarly, Google misconstrued the female HR officer as “the staff”, confusing a specific role with the entire workforce.
Language-Specific Models Need Strong Target Language Proficiency
While Bielik 11B processes Polish source text well, its English output struggled compared to frontier general-purpose models. It fabricated an artificial idiom (“grapes on the trees”) and entirely dropped “slept like a log”. For Polish-to-English translation workloads, larger multi-lingual models remain preferable. You can see how other local setups perform in our benchmark of local AI models, alongside our detailed look at Bielik.
Feature Comparison: DeepL vs Google Translate vs Chat LLMs
| Feature | DeepL | Google Translate | ChatGPT, Claude, Gemini |
|---|---|---|---|
| Pricing | Free tier; paid tiers from €7.49 per month billed annually (approx. $8.37 based on the ECB reference rate of 1.1181 on 2026-10-12, ECB reference) | Free | Free tiers with usage limits; paid subscriptions from approx. $20/month |
| Supported Languages | 114 | Over 240 | Dozens |
| Formatted Document Uploads | DOCX, PPTX, XLSX, PDF | Browser-based documents | Layout formatting is frequently lost |
| Glossary Support | Yes, including on Free (1 glossary) | Available via Cloud Translation API | Configured through prompting |
| Tone and Audience Control | Formal/informal toggles, style rules | None | Fully customizable via instructions |
| Polish Proofreading / Polishing | DeepL Write does not support Polish | None | Yes |
| Data Privacy | Paid plans do not use customer text for model training | Varies by product and tier | Varies by plan, enterprise tier, and account settings |
Choosing the Right Tool for the Job
- Idiomatic text, client correspondence, or public copy: Use a chat LLM instructed to translate naturally for your target audience, specifying any names or numbers that must remain untouched.
- Formatted workplace documents (proposals, presentations, manuals): DeepL with a defined glossary retains layouts while preserving core terminology.
- Quick comprehension, web browsing, and low-resource languages: Google Translate provides broad, instant access.
- Confidential business documents: A paid DeepL Pro subscription with contractual data-use exclusions or a fully offline local model.
An effective translation prompt for LLMs: “Translate into natural British English. Replace idioms with natural English equivalents that convey the same meaning rather than translating literally. Keep currency amounts in original Polish currency units. Do not add commentary or explanations. Preserve the original paragraph breaks.” You can explore more prompt frameworks in our guides to AI translation tools and how to translate text with AI.
Benchmark Limitations
- This benchmark evaluated a single passage translated in one direction (Polish into English). Translating into other target languages may produce different rankings.
- DeepL was not included in the automated scores because its free API requires registered credentials, and web-pasting was omitted to ensure strict programmatic parity across the benchmark.
- Scoring involves subjective editorial judgment on stylistic nuances (such as whether translating “break even” as “come out ahead” is an acceptable variation or a slight departure from the source text).
- LLM outputs are inherently non-deterministic; while setting temperature to 0 minimizes variation, exact phrasings can still vary slightly across iterations.
Frequently Asked Questions
Is DeepL better than Google Translate?
DeepL offers dedicated features like document layout preservation, formal/informal tone toggles, and customizable glossaries. Google Translate supports more languages (over 240) and remains fully free across web and mobile interfaces. In our test on complex idiomatic text, Google Translate translated 7 of 14 challenging idioms and context references literally, though it handled numbers and dates with complete accuracy.
Does ChatGPT translate better than DeepL?
Chat LLMs like ChatGPT allow you to specify exact tone, target audience, and localization guidelines via natural language prompts, making them effective for nuanced creative or colloquial writing. DeepL maintains an advantage when handling structured workplace file formats (like DOCX, PPTX, or PDF) where visual layouts must be preserved alongside glossary terms.
Which AI model scored highest in this translation test?
In this Polish-to-English idiomatic benchmark, GPT-6.1 Sol achieved a perfect 20 out of 20 score, closely followed by Claude Sonnet 5.5 and Gemini 3.8 Flash (19.5 points each), and DeepSeek V4.1 (19 points). Bielik 11B scored 17 points, while Google Translate finished with 13 points.
Is Google Translate completely free to use?
Yes, Google Translate is free through its public web interface and mobile applications. Google charges only for its commercial Cloud Translation API, which is billed per million characters translated.
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The translation test was conducted on October 3, 2026. DeepL pricing verified from its official European rate sheets.


