Mianshiya
Mianshiya (面试鸭) is a Chinese-language interview question bank with 10,000+ company questions across Java, frontend, and AI/LLM stacks.
Mianshiya is a practical option for preparing for technical interviews in China, especially campus and experienced-hire cycles, because it organises 10,000+ questions by stack, difficulty and company and pairs them with written explanations. The paid VIP membership is listed at ¥99/year. What it is not: there is no replacement for hands-on project work, and the seed data notes no public API or mobile app, with the free tier limited to browsing part of the bank. If you want Chinese-language interview questions covering AI large models and agents alongside Java and frontend, it fits well; if you need international algorithm practice or guided one-to-one coaching, look at LeetCode or a course
Verified 12d ago · liveness 56/100 · cite: rightaichoice.com/tools/mianshiya
- Computer-science students preparing for campus recruiting
- Backend, frontend and AI engineers preparing to change jobs
- Working developers self-studying interview fundamentals
- Teams or interviewers looking for question-writing reference
- People who need hands-on project experience rather than a question bank
- Job seekers who want one-to-one coaching or paid courses
- Non-technical roles such as product or operations
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Skip Mianshiya if you need English-language algorithm practice or an international question bank rather than Chinese-language, company-tagged interview questions with written explanations.
The free tier covers only part of the bank, so anyone practising seriously will hit the VIP paywall to unlock the full 10,000+ questions and the mock-interview mode.
The seed data lists a free tier limited to part of the bank and a VIP membership at about ¥99/year — low against interview-prep courses and bootcamps, and comparable to a few months of a general online course subscription. If you only need occasional browsing, the free tier may be enough; steady practice is where the paid tier earns its place.
In short
Mianshiya — Mianshiya (面试鸭) is a Chinese-language interview question bank with 10,000+ company questions across Java, frontend, and AI/LLM stacks. Best for Computer-science students preparing for campus recruiting, Backend, frontend and AI engineers preparing to change jobs, Working developers self-studying interview fundamentals. Free to start; it also has paid plans, priced in a currency we have not confirmed — see the pricing table for the vendor’s own figures.
Viability Score
How well maintained and how widely used is Mianshiya? Built from what the vendor actually publishes (docs, changelog, tutorials, integrations, pricing), whether the site is live, and how much real users discuss it. How we calculate this
Last calculated: October 2026
How we score →Key Features
- 10,000+ frequently asked enterprise interview questions
- Coverage of 30+ stacks including Java, frontend, AI large models, Go and C++
- AI large model, AI agent, RAG, LLM and prompt engineering question sets
- Filter by tech stack, difficulty and company tag
- Detailed answers and explanations with reference links
- Online practice with a timed mock-interview mode
- Wrong-answer notebook
- Question bookmarking and collections
- Progress tracking with accuracy and practice-volume stats
- Community contribution with expert review of questions
- Question search with multi-condition filters
- User notes and comments
- Partial browsing without login
- VIP membership with ad-free browsing and priority explanations
- Interview-question rankings and hot tags
About Mianshiya
Mianshiya (面试鸭) is a Chinese-language interview preparation site built by the developer known as 程序员鱼皮. It collects more than 10,000 frequently asked enterprise interview questions covering Java, frontend, AI large models, AI agents, RAG, C++, Go, Python, testing, operations, backend, operating systems, computer networking, Redis, MySQL, algorithms, Spring, JVM, Java concurrency, Linux, LLM, prompt engineering and system design. You can browse part of the question bank without logging in; creating an account lets you save practice records and join community discussion. The site provides online practice, a timed mock-interview mode, answers and explanations, question bookmarking, a wrong-answer notebook, and progress tracking with accuracy and volume statistics. Questions are community-contributed and reviewed by experts, and the site is built on a React frontend, Node backend and cloud-development stack. Its core difference is focus on the Chinese hiring market: questions are drawn from real big-company interview experience, sorted by tech stack, difficulty and company, and paired with detailed explanations and reference links. Extras include interview-question rankings, hot tags and user notes. Compared with international platforms such as LeetCode, Mianshiya is closer to the domestic interview ecosystem, is written in Chinese, and spans a wider range of stacks including newer AI topics.
Behind the Verdict
Mianshiya's value is its breadth of Chinese-language, company-flavoured interview questions. Seed data lists 10,000+ questions spanning 30+ stacks, including AI large models, AI agents, RAG, prompt engineering and LLM topics that older question banks often miss, plus long-standing staples (Java concurrency, JVM, Spring, MySQL, Redis, networking, algorithms, system design). Filtering by tech stack, difficulty and company tag is the part that saves you the most time: you can pull Huawei, Tencent or Alibaba-tagged questions and drill them in one sitting instead of reading a generic list. Study mechanics are the second strength. The timed mock-interview mode forces you to answer under pressure rather than read passively. The wrong-answer notebook collects the questions you keep missing, and progress tracking reports accuracy and volume so you can see whether you are actually improving. Self-testing beats re-reading, and this design supports that. The honest weaknesses: the catalogue is community-contributed and expert-reviewed, but individual questions may lag behind current interview practice, so treat explanations as a starting point and verify against documentation. The seed data also notes no public API and no mobile app, so the platform is essentially web-only. The free tier covers only part of the bank, so heavy users should plan on the paid membership; the seed data quotes VIP at ¥99/year, which is low relative to interview-prep courses. Note that pricing was not verified against a live pricing page in this run.
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Real-world workflow fit
Concrete scenarios for the personas Mianshiya actually fits — and what changes day-one when you adopt it.
Filter the bank by company tag and tech stack, then run timed mock interviews on the AI large-model and Java concurrency sets each evening.
Outcome: A repeatable nightly routine that surfaces weak topics through the wrong-answer notebook and tracks accuracy over the recruiting season.
Work through MySQL, Redis, JVM and system-design categories, bookmarking questions to revisit and writing short user notes as answers.
Outcome: A personal set of bookmarked questions plus notes you can reread the week before interviews.
Practise the AI large model, AI agent, RAG and prompt engineering question sets, then share the collection with teammates.
Outcome: Familiarity with the terminology and design questions that AI-application interviews in China tend to ask.
Use Cases
- Drill 10 Java concurrency questions before a big-company interview
- Filter by a Huawei, Tencent or Alibaba company tag to practise that employer's recent questions
- Use the wrong-answer notebook to re-review the topics you keep failing
- Take the timed mock-interview mode on AI large-model questions
- Collect prompt engineering questions and share them with your team
- Use the daily recommended questions to keep a practice habit
Limitations
- The free tier only exposes part of the question bank, so unlocking everything and the mock-interview mode requires the paid membership.
- The seed data states there is no public API and no mobile app, so the platform is used mainly through the web.
- Questions are community-contributed and expert-reviewed, but some may not reflect the most recent interview practice, so verify explanations against primary documentation.
- Pricing and plan details were not confirmed against a live pricing page in this run.
as of 2026-09-26
Verification history
We have re-verified Mianshiya 8 times since . Each pass re-reads the vendor's own pages and re-checks every listed field against that evidence; passes where nothing had changed are marked as such.
- — re-checked, vendor evidence unchanged
- — re-checked, vendor evidence unchanged
- — re-checked, vendor evidence unchanged
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Showing the 6 most recent of 8 verification passes.
Free to cite with attribution — this page re-verifies continuously.
12-month cost
Project the real annual outlay, including the implied monthly cost when only an annual tier is published.
Vendor list price only. Add-on usage, seat overages, and contract minimums are surfaced under Hidden costs & gotchas.
Plans compared
For each published Mianshiya tier: who it actually fits, and what it adds vs. the previous tier. Cross-reference the cost calculator above for projected annual outlay.
免费版
¥0
Ideal for
Students or casual browsers who want to sample the question bank before committing, or who only need occasional practice.
What this tier adds
Starting tier: free access to part of the bank, basic search and community discussion.
VIP会员
¥99/年
Ideal for
Anyone in an active job search who practises most days and needs the full question bank plus mock interviews.
What this tier adds
Adds the full 10,000+ question bank, timed mock-interview mode, wrong-answer notebook, collections, progress tracking, priority explanations and ad-free browsing. Priced at ¥99/year in the seed data.
Where the pricing makes sense
The company stage and team size where Mianshiya's pricing actually pencils out — and where peers do it cheaper.
The seed data lists a free tier limited to part of the bank and a VIP membership at about ¥99/year — low against interview-prep courses and bootcamps, and comparable to a few months of a general online course subscription. If you only need occasional browsing, the free tier may be enough; steady practice is where the paid tier earns its place.
Setup time & first value
How long it actually takes to get something useful out of Mianshiya — broken out by persona, not the marketing-page minute.
No installation is required — you can browse part of the question bank immediately on the web. Registering an account to save progress and use the notebook takes a couple of minutes. Setting up a structured routine around a specific stack and difficulty filter takes about ten minutes.
Switching to or from Mianshiya
How to bring data in from common predecessors and how to get it back out — written for the switcher, not the buyer.
- →From LeetCode: keep LeetCode for algorithm practice and use Mianshiya for Chinese-language stack and company-tagged interview questions.
- ↗To LeetCode: move algorithm drill to LeetCode while keeping Mianshiya for Chinese-language stack questions.
Resources & Guides
Tutorials & Learning
YouTube returned 2 videos for “Mianshiya”, and we withheld 2: 2 could not be judged, because “Mianshiya” is a single word that other videos use for other things. We are showing none, because we could not prove any of them are about Mianshiya.
Official links
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Featured Head-to-Head Comparisons
Mianshiya vs Surge Ai
Mianshiya is for individual developers prepping for tech interviews with a huge question bank. Surge AI is an enterprise platform supplying expert human feedback for frontier AI alignment. They solve completely different needs—choose Mianshiya if you're studying, Surge if you're building safer, smarter models.
Mianshiya vs Praktika
Praktika and Mianshiya serve completely different needs: one for language speaking practice, the other for technical interview prep. Choose Praktika if you're an intermediate language learner wanting to build conversational fluency with AI tutors; choose Mianshiya if you're a developer preparing for Chinese tech company interviews. They are not direct competitors.
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