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Is there an AI-based conversation model to practise German for free?

Evidence-based answer · Last updated · How it’s made

The short answer

None of the sources describe a free, dedicated AI conversation tool built specifically for German — the research base is almost entirely about English, Korean, French, Japanese, Dutch, and Luxembourgish conversation bots. That said, one source explicitly mentions Duolingo's free AI conversation character "Lily," which does include German among its supported languages, and the broader research shows AI conversation tools of this general type are effective and increasingly common, so a German learner has real options even though the evidence for German specifically is thin.

Asked as someone learning German. Findings drawn from German-specific research are framed for German learners and may not hold for other languages; where the evidence is general second-language research, the report says so.

Duolingo's Lily is a concrete free option

Duolingo has built and deployed an AI conversational tutor character called 'Lily' inside its free app, designed to let learners practice real-world conversations in their target language, with the system adapting to the learner's proficiency level and remembering prior conversations.1

Almost all research is on languages other than German

The available studies on AI conversation partners for language learning focus overwhelmingly on English, Korean, Japanese, French, Dutch, Chinese, and Luxembourgish learners; none of the sources report a study, tool, or evaluation built specifically for German learners.3,4,5,6,7,8,9,10,11,12,14

Dialogue-based AI practice works, on average

A meta-analysis pooling 17 studies and over 800 participants found that computer dialogue systems for language practice produce a medium-sized, statistically significant improvement in learners' second-language skills, though the size of the benefit varies a lot depending on how the system is designed.2

In plain terms

A 'medium effect size' is a statistical way of saying the improvement is noticeable and meaningful, not huge but not trivial either — roughly in the same ballpark as many other classroom interventions researchers consider worthwhile.

Newer LLM-based bots engage users more than older bots

Studies comparing newer large-language-model chatbots (like ChatGPT-style systems) to older rule-based dialogue systems find the LLM-based ones carry conversations more fluidly and keep learners more engaged, though older rule-based systems sometimes push learners to produce more repairs and negotiate meaning more actively, which is itself a useful speaking skill.5,8

Chatbot practice helps grammar and vocabulary gains

In a study of Korean-language learners, students who practiced grammar points with an AI chatbot scored significantly higher on a later grammar test than on points practiced by conventional means, with the biggest gains seen among students who started out with lower proficiency.12

Character-based bots can boost enjoyment and speaking practice

Stylized, personality-driven AI conversation agents (for example, an anime-styled character for Japanese learners) increased how often and how creatively learners engaged in practice sessions, and more advanced learners used more varied and expressive language with them.11

Engagement and speaking gains beat older listen-and-repeat tools

In a six-day study, Chinese university students who practiced English with a conversational AI bot showed significantly higher engagement, more varied vocabulary use, and larger gains on a speaking test than students who used an older 'listen-and-repeat' style program.8

Reviews describe real limitations of chatbot conversation practice

Broader reviews of AI chatbots for speaking practice note recurring weaknesses: many tools are still text-focused rather than voice-focused, they struggle to handle beginners' grammar and typing mistakes gracefully, and there isn't yet strong long-term evidence that chatbot practice matches or beats traditional teaching for pronunciation and fluency over time.13,15

What to do with this

Since the specific research on German-language AI conversation bots is very limited, the most concrete, verifiable free option pulled directly from these sources is Duolingo's built-in AI conversation character 'Lily,' which is designed for real-world conversation practice and adapts to your level — worth trying since Duolingo is free to use. Beyond that, the general research on AI dialogue tools suggests it's worth treating any AI conversation partner (whether free or paid) as a genuine supplement to speaking practice rather than a full replacement for a human tutor or exchange partner: use it for low-stakes, repeatable practice where you're not embarrassed to make mistakes, since one advantage of these systems noted in the research is that they never lose patience and are available any time you want to practice. If you try an AI chatbot and find it doesn't handle mistakes or beginner-level German gracefully, that matches a known limitation in the literature, so don't assume the technology or your German is at fault — pairing it with structured lessons or a human conversation partner for corrective feedback is a reasonable way to cover that gap.

Now pick something to do it with

Each of these opens an overview of the apps, courses and immersion material worth a look for that — filtered to exactly what the advice above points you at:

Or see the full resource list

Worth knowing

  • Only one source names an actual, specific, free German-capable tool (Duolingo's Lily feature), and it comes from a conference talk abstract rather than a peer-reviewed effectiveness study, so we can't say from these sources how well Lily specifically works for German learners.
  • All the other effectiveness evidence — the meta-analyses, the engagement studies, the grammar-gain studies — was conducted on learners of English, Korean, Japanese, French, Dutch, or Luxembourgish, not German, so those findings are offered as general patterns about how AI conversation tools tend to perform, not proof of what will happen for a German learner specifically.
  • The field also has documented publication bias (studies with disappointing results are less likely to get published), so real-world results with any given free tool could be less impressive than the average effect reported here.

Want a deeper literature dive?

There’s enough published research here to go wider than the usual pass. Available on the Pro plan.

See plans

  1. [1]Natalie Glance. Improving Learning Efficacy on Duolingo via Generative AI and the Learner Feedback Loop. Knowledge Discovery and Data Mining 2025. doi.org/10.1145/3711896.3736809
  2. [2]Serge Bibauw, Wim Van Den Noortgate, Thomas François, Piet Desmet. Dialogue systems for language learning: A meta-analysis. Language learning & technology 2022. doi.org/10.64152/10125/73488
  3. [3]Yu Li, Shang Qu, Jili Shen, Shangchao Min, Zhou Yu. Curriculum-Driven Edubot: A Framework for Developing Language Learning Chatbots through Synthesizing Conversational Data. SIGDIAL Conferences 2023. doi.org/10.48550/arXiv.2309.16804
  4. [4]F. Cornillie, Julie Gijpen, Sameh Said‐Metwaly, Steffen Luypaert, Wim Van Den Noortgate. Toward Adaptive Spoken Dialogue Systems for Language Learning: Predicting Task Completion from Learning Process Data. CALICO journal 2025. doi.org/10.3138/calico-2025-0035
  5. [5]V. Timpe‐Laughlin, Rahul Divekar, Tetyana Sydorenko, Judit Dombi, Saerhim Oh. Intent‐Based Versus GPT‐Based Conversational Agents: Benefits and Challenges for Practicing and Assessing Oral Interaction. TESOL Quarterly (Print) 2025. doi.org/10.1002/tesq.3409
  6. [6]Shuyao Xu, Long Qin, Tianyang Chen, Zhenzhou Zha, Bingxue Qiu, Weizhi Wang. Large Language Model based Situational Dialogues for Second Language Learning. arXiv.org 2024. doi.org/10.48550/arXiv.2403.20005
  7. [7]Hedi Tebourbi, Sana Nouzri, Yazan Mualla, Meryem El Fatimi, Amro Najjar, Abdeljalil Abbas-Turki, Mahjoub Dridi. BPMN-Based Design of Multi-Agent Systems: Personalized Language Learning Workflow Automation with RAG-Enhanced Knowledge Access. Information 2025. doi.org/10.3390/info16090809
  8. [8]Lili Dai, Fengming Wu. An AI-powered conversational system for college students learning English as a second language. Education and Information Technologies 2025. doi.org/10.1007/s10639-025-13640-3
  9. [9]Kim Heyoung, Hyejin Yang, Dongkwang Shin, Jang Ho Lee. Design principles and architecture of a second language learning chatbot. Language learning & technology 2022. doi.org/10.64152/10125/73463
  10. [10]Li, Kuo-Chen, Chang, Maiga, Wu, Kuan-Hsing. Developing a Task-Based Dialogue System for English Language Learning. Education Sciences 2020. https://eric.ed.gov/?id=EJ1277007
  11. [11]Zackary Rackauckas, Julia Hirschberg. Animating Language Practice: Engagement with Stylized Conversational Agents in Japanese Learning. 2025. https://www.semanticscholar.org/paper/7d71aaccca55b3b950f96376aacdc9051bd83c10
  12. [12]Jiyoung Shin, Yujeong Choi. Using an AI-powered chatbot for improving L2 Korean grammar: A comparison between proficiency levels and task types. Language learning & technology 2025. doi.org/10.64152/10125/73614
  13. [13]Lola López-Molines. A Systematic Review of Generative Artificial Intelligence-Based Tools to Improve Oral Skills in English as a Foreign Language. The EUROCALL Review 2025. https://eric.ed.gov/?id=EJ1494447
  14. [14]de Vries, Bart Penning, Cucchiarini, Catia, Bodnar, Stephen, Strik, Helmer, van Hout, Roeland. Spoken Grammar Practice and Feedback in an ASR-Based CALL System. Computer Assisted Language Learning 2015. doi.org/10.1080/09588221.2014.889713
  15. [15]Ngoc Hoang Vy Nguyen, Vũ Phi Hổ Phạm. AI Chatbots for Language Practices. International journal of AI in language education. 2024. doi.org/10.54855/ijaile.24115