A Guide to Free Access to Mainstream AI Models in China: Options and Pitfalls

The AI Model Access Dilemma for Users in China

As overseas AI models like GPT-5.5, Gemini 3.1 Pro, Claude, and Grok continue to iterate and improve, demand from users in China has grown increasingly strong. However, paywalls, network restrictions, and account registration hurdles have kept many people at bay.

These overseas models each have distinct technical strengths: GPT-5.5 is OpenAI's major upgrade following GPT-4o, delivering significant improvements in reasoning depth, multimodal understanding, and code generation; Gemini 3.1 Pro is Google DeepMind's flagship model, renowned for its ultra-long context window (supporting million-level token inputs) and powerful frontend code generation capabilities; Claude, developed by Anthropic — founded by former OpenAI Research VP Dario Amodei — differentiates itself through its "Constitutional AI" safety alignment approach and industry-leading long-text processing; Grok is a product of Elon Musk's xAI, marketed for its real-time access to X platform data streams and fewer content restrictions. Competition among these models has shifted from pure parameter-count battles to comprehensive contests of reasoning ability, tool use, and multimodal integration.

Recently, a content creator on Bilibili shared an aggregator site claiming to offer zero-barrier free access to multiple mainstream AI models — including Gemini, GPT, Grok, Kimi, and DeepSeek — all within China's domestic network environment. The popularity of such content reflects the current state of China's AI tool ecosystem and users' real pain points.

Features and User Experience of Aggregator Sites

One-Stop Model Switching

According to the video demonstration, the site provides a unified entry point for multiple AI models. Users can jump directly to the corresponding model's interface without switching network environments. Taking Gemini as an example, selecting its entry point leads directly to the official page, with support for switching between different model versions, including the latest Pro series.

Overview of Covered Mainstream Models

Based on the video, the site covers an impressively wide range of models:

• DeepSeek: A leading Chinese AI model using a Mixture of Experts (MoE) architecture with 671 billion parameters but activating only about 37 billion per inference, dramatically reducing computational costs while maintaining exceptional reasoning quality — widely regarded as an "efficiency revolution" in the industry
• GPT Series: Including the latest GPT-5.5 and GPT Image 2
• Gemini 3.1 Pro: Google's latest flagship model with outstanding frontend code generation
• Grok: xAI's model, available via mirror access
• Claude: Made by Anthropic, excelling at long-text processing
• Kimi: A Chinese long-context model developed by Moonshot AI, supporting context windows of up to 2 million characters, capable of processing entire books or large document collections in a single input

Additionally, the site includes various prompt instruction packs covering specialized prompt templates for models like DeepSeek and Grok 3, which can be helpful references for beginners. Prompt Engineering refers to the practice of carefully designing input instructions for AI models to guide them toward more accurate, expected outputs. Common techniques include Chain-of-Thought prompting (having the model reason step by step) and Few-shot Learning (providing examples to guide output format). Because different models vary in training data, alignment methods, and architecture, they may respond very differently to the same prompt — making model-specific prompt templates genuinely useful. However, as model capabilities rapidly evolve, the practice of relying heavily on fixed templates is being replaced by more flexible interaction approaches.

Risks You Must Consider Before Using Aggregator Sites

Compliance and Data Security

The video specifically states at the end that the site "accesses and calls all AI models through legal and compliant channels within China, strictly following relevant national laws and regulations." However, users should still exercise caution:

• Data security concerns: When using AI models through third-party sites, your input data may pass through intermediary servers, creating privacy leak risks
• Questionable service stability: Aggregator sites typically rely on API forwarding or mirror deployment, meaning service could be interrupted at any time
• Compromised feature completeness: Despite claims of "full-featured access," mirror sites often differ from official services in functionality and rate limits

From a technical architecture perspective, these aggregator sites typically use one of two approaches. The first is API Proxy, where the site operator deploys a middleware service on overseas servers that forwards user requests to each model's official API endpoints and relays responses back. Under this approach, all user input data passes through the intermediary server, and the operator has full technical capability to log, store, and even analyze this data. The second is Mirror deployment, using reverse proxy technology to "mirror" the official web interface to a domestically accessible domain. Users appear to be using the official interface, but all traffic is actually routed through third-party servers. Either way, there's an uncontrolled "middleman" between the user and the AI model — a scenario known in information security as a potential "Man-in-the-Middle" (MITM) attack risk. Therefore, users should avoid entering any sensitive personal information, business data, or confidential content when using such sites.

The Hidden Costs Behind "Free"

There's no such thing as a free lunch. Operating these sites isn't cheap — API call fees and server expenses all require funding. Take GPT-5.5 as an example: its API pricing is significantly higher than previous models, and a site with just a few thousand daily active users could face monthly API costs of tens of thousands of dollars. Common monetization models include: traffic monetization (ads), user data collection, and conversion to paid tiers. While enjoying the convenience, users should understand the hidden costs they may be paying.

Legitimate Ways to Use AI Models in China

Rather than relying on third-party aggregator sites and taking on unknown risks, it's better to prioritize the legitimate channels already available in China.

Recommended Free Chinese AI Models

• DeepSeek (deepseek.com): Freely available, with reasoning capabilities on par with GPT-4 level, using MoE architecture to achieve exceptional cost-effectiveness — its training cost is a fraction of comparable models
• Kimi (kimi.moonshot.cn): Excellent long-text processing with generous free quotas, supporting context windows up to 2 million characters
• Tongyi Qianwen (tongyi.aliyun.com): Built by Alibaba, leveraging Alibaba Cloud's computing infrastructure, with comprehensive multimodal capabilities (understanding and generating text, images, audio, and video)
• Doubao (doubao.com): ByteDance's offering, providing a smooth daily-use experience
• Zhipu ChatGLM (chatglm.cn): Based on the GLM (General Language Model) technology developed by Tsinghua University's KEG Lab, using an autoregressive blank-filling pre-training paradigm different from the GPT series, performing particularly well in Chinese academic scenarios

These Chinese models each have distinctive technical approaches, forming a differentiated competitive landscape that covers the vast majority of users' daily needs.

Official Compliant Channels for Overseas Models

Some overseas models have entered the Chinese market through compliant channels or offer free-tier services. For example, Google Gemini has opened free access in certain regions. Users should follow the latest policy updates from each model's official channels.

Choose the Right AI Tool Rationally

The AI model landscape has undergone profound changes. Chinese models have caught up with or even surpassed overseas competitors in multiple dimensions — particularly DeepSeek's performance on reasoning tasks and Kimi's advantages in long-text processing, both of which have gained widespread recognition.

For most users, rather than spending time hunting for various "free access" workarounds, it's better to deeply master one or two models that fit your workflow. The value of a tool lies not in quantity, but in whether you can use it well.

Of course, for developers and researchers who need to compare output quality across different models, multi-model access is a genuine necessity. It's recommended to obtain services through official APIs and authorized resellers — this protects your data security while supporting the healthy development of the AI ecosystem.

Key Takeaways