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xiaoqiangapi

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I compared 4 Chinese LLMs – DeepSeek can be as low as 1/50 the price of OpenAI (and here’s a gateway to use them overseas)

I’m a former Chinese teacher who accidentally became an API provider. Here’s the price, speed, and how to actually use them from outside China--DeepSeek, MiniMax, Zhipu and Qwen

Recently, many overseas developers have asked me: "Are China's big models really cheap? Which ones exactly? How does it compare to OpenAI?"

To be honest, I also started from scratch and worked my way through step by step to help students find cheap apis. It was this experience that led me to start seriously studying large models in China.

Today, in the most accessible way, I would like to introduce to our fellow developers around the world: ** How far have China's large models developed as of today in April 2026? Which models are worth paying attention to? How about the price? **

This article is not an advertisement; it's my research report as a "non-tech entrepreneur". If you find it useful, please give it a thumbs up, share it and follow.


1 Industry Big Event: China's large model weekly call volume surpasses US for the first time

Data released by OpenRouter, the world 's largest AI model invocation statistics platform, in collaboration with Stanford HAI Institute in March 2026 showed:

  • ** China's weekly call volume of large models reached 4.69 trillion tokens **, up 320% year-on-year
  • ** Surpassing the US for two consecutive weeks ** (4.21 trillion tokens)
  • In the TOP10 global callings, ** Chinese models occupy 6 seats **

What does that mean? It's not a mere "quantitative" lead, but a comprehensive catch-up in terms of technological maturity, ecological completeness, and industrial implementation capabilities.

For overseas developers, this means: ** You have more low-cost, high-performance options **.


2. Detailed Explanation of the Four Major Domestic Flagship Models

Here are the four most notable large Chinese models at present.

(1) DeepSeek - the king of ultimate cost performance

  • ** Core feature ** : extremely low inference cost, claimed to be "1/20 to 1/50 of OpenAI"
  • ** Context length ** : Supports *1 million tokens * (can handle the Three-Body trilogy all at once)
  • ** Inference speed ** : approximately 1200 tokens /s (CPU), 8500 tokens /s (GPU)
  • ** Advantages ** : Open source, free commercial use, excellent Chinese language skills, extremely low API price
  • ** Suitable scenarios ** : Individual developers with limited budgets, start-up teams, large amounts of text processing

(2) MiniMax M2.5 - the world's most invoked

  • ** Core feature ** : Excellent value for money, inference cost only 1/8 of GPT-4 Turbo
  • ** Context length ** : 800,000 tokens (measured to stably handle 750,000 tokens)
  • ** Inference speed ** : 1200 tokens /s (CPU), 8500 tokens /s (GPU)
  • ** Advantage ** : The world's leading Chinese processing power, high dialect recognition accuracy
  • ** Suitable scenarios ** : corporate customer service, code development, document processing, intelligent translation

(3) Zhipu GLM-5-Turbo -- Agent scenario leading in China

  • ** Core feature ** : Neural symbol fusion architecture, 18% higher accuracy in complex reasoning
  • ** Context length ** : 200K Token
  • Inference speed: 900 Token/s (CPU), 7200 Token/s (GPU)
  • ** Advantage ** : The Agent has outstanding autonomous planning capabilities and can complete multi-step and cross-tool tasks
  • ** Suitable scenarios ** : Office automation, intelligent assistants, developer tools

(4) Alibaba Tongyi qianwen Qwen 3.5-Max - strong multimodal and coding capabilities

  • ** Core features ** : Top 5 math skills globally, code generation accuracy over 94%
  • ** Context length ** : 640,000 tokens
  • Inference speed: 1000 Token/s (CPU), 7800 Token/s (GPU)
  • ** Advantage ** : Supports native fusion of text, image and audio, built into Alibaba Cloud
  • ** Suitable scenarios ** : Financial risk control, academic research, industrial design, multimodal content creation

III Price Comparison: Chinese Model vs. OpenAI (Reference April 2026)

Model: Input Price (/1M tokens) Output Price (/1M tokens) : approximately OpenAI's
| :--- | :--- | :--- | :--- |
DeepSeek | * * * * | | ~ $0.014 to $0.028 | | 1/20 ~ 1/50
MiniMax M2.5 Unpublished ~$1.2 1/25
** Smart Spectrum GLM-5** Please check official/Please check official/about 1/10
** Tongyi Thousand Questions ** * Please check official/Please check official/approximately 1/8 to 1/10
OpenAI GPT-4 Turbo $10.00 $30.00 benchmark

Note: The above is the market reference price. The actual price is subject to the official documentation.

** Conclusion ** : The API cost of Chinese models is generally 1/10 to 1/50 of that of OpenAI. This is a very realistic option for individual developers and start-up teams with limited budgets.


4 Strengths and Weaknesses of the Chinese Model (Objective Evaluation)

** Strengths: **

  • ✅ very low price, suitable for cost-sensitive projects
  • ✅ highly proficient in Chinese (a significant advantage if you need to handle Chinese translations or Chinese content)
  • ✅ Some models support edge-side deployment (run locally on mobile or PC)
  • ✅ context length is large (800,000 to 1,000,000 tokens), suitable for handling long documents

** Shortcomings: **

  • ❌ English/other languages are not as good as Chinese overall (but normal API calls are sufficient)
  • ❌ overseas localization knowledge (such as the latest buzzwords, local news) may not be updated in a timely manner
  • ❌ Some model documentation is only available in Chinese

** My opinion ** : If you are using it for technical tasks such as *API calls, translation, content generation, code assistance *, the cost-performance advantage of Chinese models is very obvious. If you are going to do an application that is deeply localized overseas, it is recommended to test it first.

How to try these models :
Official API (fast but may need network setup)
My gateway – one key, PayPal, stable for overseas (link)
Open-source deployment (free but technical)

5, Next Step preview

Which Chinese LLM are you most interested in? I’ll run a speed test next – comment below.

References


Top comments (1)

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xiaoqiangapi3721 profile image
xiaoqiangapi

To gather this information, I went through over a dozen official documents and eventually found that the data of DeepSeek was indeed quite exaggerated. But I also knew that prices change rapidly, so I specifically marked "April 2026".

There is a question that I have always wanted to ask the developers in the community: In your actual projects, do you value the price of the model more, or the response speed? Or stability? Security? Convenience?

I plan to specifically measure these dimensions in the following articles. Your opinions are extremely valuable. Thank you in advance!