DeepL

@DeepLcom · Cologne, Germany · joined 01 Feb 2018

Connect and scale your business globally with the AI layer for language and superior quality translation across text, speech-to-speech, documents, and more 🌏💬

19 954Followers

91Following

1 215Posts total

58.1KViews on collected posts

Against accounts of the same size

8 posts from the last 90 days, next to the 10K–100K follower range. shown widely, but few of those viewers react.

Median views1 097this account1 266median for 10K–100K

Reach, %5.50%this account3.99%median for 10K–100K

Engagement, %0.58%this account1.98%median for 10K–100K

Metric	This account	Median for 10K–100K	Ratio
Median views per post	1 097	1 266	0.87×
Reach (views ÷ followers)	5.50%	3.99%	1.38×
Engagement rate	0.58%	1.98%	0.30×

Others in this range → Compare with another account → How these benchmarks are built →

Growth & engagement

How the posts we collected actually performed: views and reaction rate post by post, what the audience did with them, and where the follower count goes.

Views per post

77720 Aug

92324 Aug

92927 Aug

49.7K28 Aug

1.8K

1.3K

73031 Aug

Last 8 collected posts, oldest on the left. The scale is logarithmic: one post can outrun the rest a hundred times over.

Engagement rate per post

0.13%20 Aug

0.76%24 Aug

0.22%27 Aug

0.22%28 Aug

1.27%

2.32%

1.03%

0.41%31 Aug

Reactions — likes, reposts, replies and quotes — divided by views. Median for 10K–100K accounts is 1.98%.

What the audience does

Likes67.1%157 in total

Reposts3.0%7 in total

Replies8.5%20 in total

Quotes8.5%20 in total

Bookmarks12.8%30 in total

Share of every reaction we collected for this account. Replies mean argument, reposts mean endorsement, bookmarks mean the post was worth keeping.

The follower curve appears once this account has two daily snapshots — we take one a day, and this one is on its first.

Latest posts

There’s an inconvenient truth that nobody in AI translation likes to talk about. What we measure in quality test scores is becoming less important than what we don’t. Gaps in MQM-type quality benchmarks may be narrowing, but the differences in real-world performance are becoming 730 views · 2 likes · 1 reposts · 0 replies 31 Aug 2026 @DeepLcom GLM 5.3 flash deepseek v4 flash gemini flash lite etc 1.3K views · 13 likes · 0 reposts · 0 replies 28 Aug 2026 @DeepLcom no way someone talking about GPT-5.2 or Opus 4.6 2K views · 46 likes · 0 reposts · 0 replies 28 Aug 2026 @DeepLcom How about gpt-5.6-luna? 1.8K views · 23 likes · 0 reposts · 0 replies 28 Aug 2026 If you’re using a general-purpose LLM for translation, quality equals latency. If you’re using a specialized model like DeepL, it doesn’t. OpenAI GPT-5.2 is 4x slower than DeepL. Claude Opus 4.6 is 6x slower. Google Gemini 3.1 Pro is a vast 29x slower. If you’re choosing a http 49.7K views · 66 likes · 4 reposts · 19 replies 28 Aug 2026 Residents and businesses can speak to Walsall Council in the language of their choice thanks to Kerv’s CX Translation real-time voice and digital translation, powered by the DeepL API. Enabling seamless, real-time communication across language barriers ensures callers feel http 929 views · 2 likes · 0 reposts · 0 replies 27 Aug 2026 Adding @Mixhalo's ultra-low latency audio to DeepL’s end-to-end language intelligence has transformed what we’re able to build with Voice. When you control the speed of audio delivery, and remove it as a constraint, what was previously impossible quickly becomes a product https:/ 923 views · 5 likes · 1 reposts · 1 replies 24 Aug 2026 A general-purpose LLM can generate a translation for you. What it can’t do is give you translations that are consistent, predictable and controllable, every time. If you’re embedding an AI translation API in products, pipelines or workflows, that really matters. If you’re https:/ 777 views · 0 likes · 1 reposts · 0 replies 20 Aug 2026