AI ToolsAccess Guide

Environment Basics

Why are AI Services sensitive to the Network Environment?

One visit involves multiple checks

The browser address bar shows a single product domain, but a complete visit usually involves page assets, identity authentication, API requests, streaming responses, file storage and content delivery. Different steps may use different hosts and connection methods. Seeing the page shell does not mean that the follow-up API has established a stable session. A common symptom is that navigation and history load while a submitted prompt waits indefinitely; text responses may work while attachments or image generation fail. The issue is not simply whether the website opens, but whether one part of the request chain completed.

AI platforms may use the exit IP region to determine the service entry point, feature availability and identity verification flow. This detection depends on the network exit, not the operating system language, browser language or device time zone. If the exit region changes frequently, the session history seen by the login service lacks continuity. For accounts that store conversations, projects, code indexes or API credentials over time, a stable and explainable environment is usually more valuable than briefly pursuing the lowest latency.

IP Reputation & Session Continuity

An exit IP is more than a geographic label. A platform may consider the address's network, historical request patterns, switching frequency over a short period and account behavior when deciding whether extra verification is needed. A shared exit is not automatically a problem, but an exit carrying many high-frequency automated requests at once may encounter congestion or risk checks more easily. Conversely, a dedicated exit does not make account behavior irrelevant; unusual concurrency, repeated failed logins and intensive session creation can still trigger the platform's safeguards.

Session continuity includes the exit region, browser cookies, local storage, device time and authentication redirect state. Changing routes midway through login can start authorization in one region and finish the callback in another. The credentials saved by the browser may then be incomplete, appearing as an immediate logout after successful login or a request to authenticate again on every new page. The safer approach is to choose one route and keep it unchanged throughout login and authorization, then verify the main features afterward.

Long-lived connections differ from ordinary web requests

Traditional web requests often end as soon as a resource is retrieved, so a brief disruption may only reload one image. AI conversations usually depend on continuous transmission, with the response arriving in segments as it is generated. If the connection resets midway, text already received may remain while later content stops; some clients show a retry control, while others leave a cursor that no longer moves. Code completion, voice interaction and large-file processing also depend on persistent state, so occasional packet loss affects them more noticeably than ordinary content pages.

Therefore, do not judge a route only by how quickly the homepage opens. More useful observations include whether several consecutive conversations complete, whether longer answers stop frequently, whether a session survives tab switching, whether attachments transfer reliably and whether waking from sleep requires a new connection. Recording these symptoms helps determine whether the cause is route instability, browser power saving, account limits or a busy service.

Region, IP, session and long-lived connections together form the operating environment for an AI service. Changing only the browser language usually cannot fix a network problem, while repeatedly clearing all data may destroy a session that was working. A safer method is to keep a known-good baseline and change one variable at a time, then compare the result. The route selection and systematic troubleshooting sections below develop this method further.

Identity & Sessions

Account Creation, Login & Authorization

Keep your RBVPN account separate from your AI platform accounts

Your RBVPN account provides network service, while each AI platform manages its own account. They are not connected. RBVPN requires no email address; a username and password are enough. ChatGPT, Claude, Gemini, Copilot, Midjourney and Cursor each have their own account systems, regional rules and verification flows, so follow the current official requirements shown by the relevant platform. Do not confuse your network service login with your AI platform login.

In practice, confirm that the client is connected before opening the target platform in a browser. If the RBVPN client reports a connection but the platform remains on the authentication page, check whether the login flow redirects to another domain, whether browser privacy settings block it and whether the exit remains consistent before and after login. For client import steps, see the Guides; for the basics of subscription links, see What Is a Subscription Link?.

Keep the environment consistent during account creation

Account creation usually consists of several consecutive pages: opening the sign-up entry point, accepting terms, creating credentials, completing verification and returning to the product. Even when it looks like one form, the process may cross identity and product services. Switching routes repeatedly halfway through can attach different exit information to successive requests, causing the platform to restart the flow or mark temporary state on the old page as expired.

A safer approach is to choose a stable route in a region supported by the target platform, disable rules that rotate the exit automatically and complete the process in one browser window. If the platform clearly says the service is unavailable in the current region, respect that notice and check its rules rather than repeatedly submitting forms to test the boundary. Repeated failed submissions create more session confusion and make it harder to tell whether the original issue involved the region, account details or browser state.

Login Callbacks & Cookies

A common third-party authorization flow sends you from the AI product to an identity provider, then returns with a temporary authorization result. If the browser strictly blocks cross-site cookies, pop-ups or redirects, the authorization page may report success while the product still shows you as signed out. First check whether the address bar remains on an authentication domain, whether a pop-up was blocked and whether a privacy extension modified the request.

Do not begin by clearing all browser data. Instead, create a separate browser profile or use a temporary window for testing. If the temporary window works, inspect cookies, extensions or cache in the main profile; if both fail, investigate the route and account state. A separate profile also prevents work and personal accounts from overwriting each other's authorization state, which is especially useful for developers using several AI platforms.

Repeated logout after login

An immediate logout after successful login should be analyzed through session storage, system time, exit changes and platform account status. An inaccurate device clock can invalidate temporary credentials; automatic site-data cleanup on browser exit can remove the session; rules that select routes across multiple regions can make background refresh requests appear to come from a new environment. Fix the route and keep the browser open, then check whether the logout still occurs to narrow the cause quickly.

If only one platform repeatedly logs you out while other platforms and ordinary websites work normally, the issue is more likely related to that platform's account or site data. If every site that requires login behaves similarly, prioritize browser policies, system time and network switching. Account recovery, identity verification and appeals are provided by the platform itself; network connectivity cannot replace proof of account ownership.

The core principles for the account stage are environmental continuity, clear identity boundaries and complete error context. A network route addresses transport and exit issues; it does not change platform terms or remove restrictions on the account itself. Understanding that boundary makes later decisions more accurate.

Route Management

How to choose Routes for AI Tools

The target service region matters more than apparent distance

When choosing a route, many people look only at whether a city is nearby. Physical distance affects round-trip paths, but AI services also depend on regional availability, exit network quality and cross-border link stability. A nearby exit that takes a poor detour to the target service may perform worse than a farther region with a steadier path. First confirm which regions the platform supports, then compare conversation continuity, login and upload performance among candidates.

One route does not have to suit every task. Text chat depends mainly on sustained responses; image and attachment tasks care more about uploads; code completion sends frequent small requests; indexing a large codebase creates a longer synchronization process. Keep a small set of tested routes for different tasks instead of selecting randomly from the full list each time. RBVPN covers 100+ countries and 190+ routes; see the Network page for specific regions and route types.

Understanding IEPL, relay and direct routes

IEPL routes generally emphasize path organization and stability across the cross-border backbone, making them suitable for office work, meetings and AI streaming where continuous transmission matters. Relay routes first reach an intermediate access point before continuing to the exit, which can help adapt paths to complex network conditions. Direct routes use a more straightforward structure and suit situations where the local carrier's path to the target exit is already strong. A route label describes the scheduling method; it does not guarantee the same result everywhere.

Assess route types together with the current access network. Home broadband, office networks and public networks may use different local exits, so the same route can perform differently. If an office network restricts proxy connections, normal performance at home does not prove the route is faulty. If every access network fails on the same platform, check the platform region and account state instead.

Build your own baseline route

A baseline route is not theoretically optimal; it is a route already verified on your current access network, device and target service. Verification should cover login, sending a request, receiving a longer response, switching pages and reconnecting. Keep the route as a control after confirmation. When something later goes wrong, test the baseline first. If it also fails, determine whether the local network, platform status or account has changed.

When testing candidate routes, change only one factor at a time: region or route type. If you also change browsers, clear the cache, switch routes and modify DNS, it becomes difficult to know what helped. Users who need stable work environments can record separate baselines for office and home networks because their access paths differ and their conclusions cannot simply be shared.

Automatic selection is not ideal for every scenario

Automatic scheduling works well for ordinary browsing, but login authorization, ongoing conversations and API tasks place greater value on a consistent exit. If the client switches routes based on momentary conditions, an established session may need to renegotiate and the platform may see a different exit. For important tasks, temporarily fix a tested route and restore the usual rules afterward. The goal is not permanent use of one node, but a predictable single work session.

Unlimited devices let you configure Windows, macOS, iOS, Android and Linux separately, but routes should still be managed by purpose. Keep a stable exit on a development machine and favor convenient connections on mobile devices instead of applying one rule to every situation. To compare plans and traffic options, see Plan Pricing.

Web Interaction

Troubleshooting Web Apps and Streaming

An open page does not mean the conversation path is complete

AI web apps often load the static interface first, then request account data, model lists and conversation history before establishing the persistent connection used for responses. If only static assets succeed, the full layout may still appear while new conversations cannot be created. Open the browser developer tools' Network panel and check whether sending a prompt creates a request that stays open, whether it fails immediately and whether the failure occurs on the product domain or another domain such as authentication or storage.

If you are not familiar with developer tools, use behavioral comparisons. Refresh the page and check whether history loads; send a short text and see whether output begins; then test a longer response and an attachment. If short text works but long responses often stop, focus on persistent connections and device sleep. If no send action gets a response, check script extensions, login state and API requests first.

Streaming responses stop midway

A response stopping midway can result from a route reset, browser background power saving, platform load or an account usage limit. The symptoms can look similar, but the surrounding clues differ. A network reset often affects other persistent tasks at the same time; browser power saving usually appears after a tab goes into the background; a platform restriction provides a clearer notice; an isolated conversation-context issue may disappear in a new chat.

Start with low-risk checks: keep the current route, bring the page to the foreground and resend a short request; start a new conversation; disable content-blocking extensions that apply only to the site; then switch to the verified baseline route. Do not clear the session and change accounts in the same test, or you will not know why it recovered. If the response matters to your work, copy the generated portion before refreshing.

File Uploads & Generated Tasks

An attachment upload usually sends the file to a storage service first, then passes a file reference to the conversation service. If upload progress completes but the model cannot read the file, follow-up processing between storage and conversation may have failed. If progress itself stops, the issue is closer to transport or browser permissions. File names, formats, sizes and platform policies also affect the result; a route can handle transmission but cannot change which file types the platform permits.

Image generation and other long-running tasks may use queues, polling or persistent connections. When a page waits for a long time, check first whether the task status is still changing instead of submitting the same task repeatedly. Repeated actions may create multiple tasks and consume the platform's allocated usage. If the task remains after reopening the page, it was handed to the server; if no task record appears at all, inspect the initial submission stage.

Browser Extensions & Privacy Policies

Content blockers, script managers, privacy tools and request-rewriting extensions can affect authentication redirects, streaming APIs or file domains. An extension working on ordinary content sites does not mean it is compatible with a complex application. The most effective comparison is a separate browser profile without extensions, rather than guessing through rules one by one. Once the separate profile works, return to the main profile and enable items individually until the conflict is found.

Strict cookie-cleanup policies can also cause sessions to disappear repeatedly. Keep only the necessary site data for the platform in use instead of disabling all privacy protection. On organization-managed devices, first confirm that browser and proxy settings allow the target service. Local user settings may not override organizational policies, and repeatedly changing the client will not alter that fact.

Web troubleshooting works best when static pages, identity APIs, conversation APIs, streaming output and file tasks are separated. Once you know which layer failed, you can choose the right comparison test, avoiding the misclassification of account limits as route problems or browser-extension conflicts as platform outages.

Programmatic Access

How AI APIs differ from web apps

Web availability does not imply API availability

Web apps usually let the platform's frontend manage authentication, retries and streaming parsing, while an API is called directly by the developer's program. They may use different domains, credentials, account quotas and regional policies. A working browser conversation proves only that the web product path is available; it does not prove that a CLI, server or CI environment is configured correctly. Conversely, a working API does not mean the web account's cookies and authorization state are healthy.

Classify API failures first as connection establishment, authentication, invalid parameters, platform rate limiting or response parsing. Connection problems usually occur before a business response arrives; identity and parameter errors return structured errors; rate and quota limits often include a clear type; parsing failures may occur when a client treats a streaming response as one complete response. Classification matters more than repeated resubmission.

Proxy Environment Variables & Application Support

Whether a CLI tool uses a proxy depends on its runtime and whether its network library reads proxy environment variables. A running process may not update after variables are set, and an IDE launched from a desktop icon may not inherit variables from a terminal. Set the environment in the same terminal session, then launch the test command. The example below uses an obvious local proxy placeholder, contains no real credentials and does not point to a real subscription address.

export HTTPS_PROXY="http://127.0.0.1:LOCAL_PROXY_PORT"
export HTTP_PROXY="$HTTPS_PROXY"
export NO_PROXY="localhost,127.0.0.1"

curl --verbose "https://example.com/health"

The address in the example only demonstrates variable syntax; use the API endpoint from the relevant platform's official documentation in practice. If a network library does not read these variables, configure the proxy explicitly in the library's client constructor or use system-level network routing. Do not configure multiple proxy layers without recording their sources, or requests may be forwarded repeatedly and the actual exit will be impossible to identify.

Understand timeouts by phase

A request timeout is not one setting. Connection establishment, the TLS handshake, waiting for the first response segment and reading the complete response may each have separate timeout controls. An AI streaming API can keep reading for a long time after output begins; a client with only a short total timeout may disconnect while the response is being generated normally. An unlimited wait is also unsuitable because a broken connection could occupy a task slot indefinitely.

Separate connection and read timeouts, and allow streaming requests to keep reading. Set actual values according to the platform documentation, task length and application tolerance; this page does not prescribe context-free fixed values. Recording when the request starts, the connection is established, the first content arrives and the response ends helps show whether the bottleneck is connection setup or model processing.

Retries, Concurrency & Idempotency

Automatic retries after connection failures are common, but generation requests are not necessarily idempotent. If the server accepted a task but the client did not receive confirmation, retrying directly may create a duplicate response or task. The application should use request identifiers, task status or the platform's idempotency mechanism rather than resending every error unconditionally. When streaming stops midway, make clear whether to resume, regenerate or inform the user.

Concurrency should reflect account limits, application needs and platform documentation. A sudden increase can amplify pressure on the local connection pool, proxy path and platform rate limits at once. During development, validate correctness with serial requests before gradually adding queues and concurrency controls. If failures occur only under concurrency, inspect connection reuse, file descriptors, proxy capacity and platform responses instead of simply changing the exit.

Key & Logging Boundaries

Inject API keys through environment variables or a dedicated secrets manager; never put them in public repositories, frontend scripts or screenshots. Debug logs may record request IDs, error types, timing phases and exit regions, but should remove authorization headers, cookies, sensitive user input and complete responses. Network troubleshooting needs enough context, not every piece of content.

AI_API_KEY="YOUR_API_KEY"
AI_API_ENDPOINT="https://api.example.com"
AI_REQUEST_TIMEOUT="YOUR_TIMEOUT"

network:
  endpoint: "${AI_API_ENDPOINT}"
  timeout: "${AI_REQUEST_TIMEOUT}"
  key_from_environment: "AI_API_KEY"

For a further comparison of fixed exits, concurrency and timeout strategies, read Which AI API Accelerator Is Best?. That article focuses on selection; this chapter establishes a troubleshooting framework: confirm the network path the program actually uses, then evaluate the business response instead of applying web-app behavior directly to APIs.

Engineering Environments

CLI, IDE Plugins & CI Configuration

Confirm the actual exit from the command line first

After a desktop client reports a successful connection, the browser may be using the system proxy while the terminal program is not. Some tools read system proxy settings, some read only environment variables and others use their own network implementation. When validating a CLI, launch the target program from the same terminal and inspect detailed connection logs. The goal is not to expose a real address, but to confirm that DNS resolution, connection establishment and the TLS handshake follow the expected path.

Proxy variables in a Shell configuration file may apply only to new terminals. Continuing in an old window after editing the file can make a valid setting appear ineffective. Also watch for differences in variable capitalization, since tools do not all read them the same way. Team documentation should state where variables are set, which startup script reads them and how to restore the environment when development ends, preventing proxy settings from lingering and affecting internal services.

IDE plugins run in their own processes

Cursor, Copilot and other AI coding plugins commonly run in the editor's main process, an extension host or a separate background process. Changing terminal environment variables after opening the editor does not necessarily reach an extension that is already running. If a plugin login page is blank, completion waits indefinitely or the chat panel cannot connect, fully quit the editor and relaunch it from a terminal with the environment configured, or use the editor's network settings.

A plugin may access identity services, model APIs, update services and resource domains at the same time. Allowing one primary domain is not enough to guarantee full functionality. On enterprise networks with domain allowlists, consult the plugin's official network requirements and approve each necessary domain instead of guessing from one error. If browser login succeeds but the editor receives no callback, check that the system returns the authorization link to the correct application and that security software is not blocking the local callback.

Containers and hosts are different network spaces

When a command runs inside a container, the host's local proxy address may point to the container itself. Copying a loopback address from the desktop environment commonly results in a refused connection. Configure a host entry reachable from the container based on how the container runs, or provide an explicit proxy service within the container network. Do not hard-code a platform-specific address here because desktop systems, container engines and team network topologies differ.

Separate the image-build phase from the container-runtime phase. Downloading dependencies during a build requires network access from the builder, while AI API calls at runtime originate from the application container. Putting proxy credentials into an image layer creates a leakage risk. Use the build environment's secret-injection capability and ensure the final image retains neither the variables nor the configuration files.

CI environments need an explicit exit strategy

CI jobs usually run on remote runners and do not automatically use the developer's local RBVPN connection. If a workflow calls an AI API, first confirm the runner's region, whether the platform allows access from that region and whether the organization provides a fixed exit. Copying a locally working configuration directly to a cloud job often fails because the network boundaries differ. Self-hosted runners require operations teams to manage exits and credentials; repository code should not create an unauditable forwarder on the fly.

Be especially careful with CI retries. Re-running an entire pipeline after failure may repeat a generation task that already succeeded. Save external-call results and task status in a traceable location, and define clear boundaries between repeatable and non-repeatable steps. Keep request IDs and error categories in logs, but never print keys or complete user data.

Team configuration should be reproducible

Getting something working on one computer does not mean the team can maintain it. Put non-sensitive settings in a template and document environment variable names, startup order, health checks and recovery steps; inject real credentials separately in each environment. Network issue reports should include the runtime environment, target service, failure stage, whether streaming was involved, whether a container was used and the current exit region, but not subscription addresses or keys.

Development environments should also separate internal services from external AI services. Internal repositories, databases and local debugging addresses generally should not use external routes; exclusion rules can keep them direct. Rules that are too broad send internal requests on detours, while rules that are too narrow may omit domains required by the AI platform. After each change, test internal resources and external services separately so that fixing one does not break the other.

Account Stability

Account Risk Checks, Suspensions & Rate Limits

First distinguish network errors, rate limits and account restrictions

All three can appear as failed requests, but they require completely different responses. A network error means the request did not reach the service reliably or the response did not return completely. A rate limit usually means the platform recognized the request but the current frequency, concurrency or quota does not meet its rules. An account restriction may affect login, feature access or credential use. Only after identifying the layer of the error can you know whether to change routes, reduce request pressure, check billing or contact platform support.

Do not call every failure a suspension. If the web app still allows login but one model is unavailable, the cause may be product permissions or regional differences. An API usage notice may indicate a quota issue. An explicit message that the account is restricted belongs to account support. Accurate classification avoids unnecessary account switching and repeated account creation, and helps preserve complete appeal materials.

Frequent region changes weaken environmental continuity

Logging into the same account from several widely separated regions in a short period may trigger extra checks. The issue is not that one route is inherently faulty, but that the session history becomes difficult to explain. After login, keep a relatively consistent exit region, especially when changing account settings, creating API credentials or authorizing access. Mobile work does change the network environment, but avoid switching regions repeatedly during one operation.

If you must change regions, stop critical tasks first, wait for current uploads and generation jobs to finish, then change routes and establish a new session. Do not leave one browser tab with an old-exit session while another submits sensitive actions through a new exit. For long-running development tasks, use a stable exit and manage personal browsing separately to reduce interference between the two traffic types.

Shared exits and unusual behavior are not the same thing

Shared exits are common in network services, and platform risk decisions generally also consider the account's own behavior. Normal human interaction, a steady request pace and a clear application purpose differ from large bursts of failed requests, automatic session creation, repeated verification or abuse caused by leaked credentials. You cannot predict an account outcome from whether an exit is shared, nor attribute every restriction to a network address.

Manage the factors you control: never commit API keys to public repositories, give account cookies to unknown plugins or let automation retry indefinitely after errors, and do not run uninformed tasks simultaneously from multiple regions. If a key is being used unexpectedly, revoke and recreate it in the platform dashboard, then inspect logs and repositories instead of merely changing routes.

Rate limits usually call for less pressure, not a new exit

A platform may apply rate limits by account, model, project, credential or time window. Changing the exit may not affect these dimensions and can add more environmental change. Applications should read the returned error type and wait guidance, then control requests with queues, backoff and concurrency caps. If usage genuinely exceeds the account configuration, adjust the plan according to platform rules instead of treating rate limiting as a connection failure.

Backoff strategies need stop conditions. Infinite retries amplify failures and may prolong a temporary restriction. Generation tasks also carry the cost of duplicate execution, so record task status and request IDs when possible. The interface should distinguish “retry after waiting,” “invalid credential,” “account restricted” and “network unreachable,” preventing users from taking the wrong action.

Account appeals need verifiable information

If the platform explicitly restricts an account, use its official support channel and provide the account identifier, time of occurrence, error notice and normal use case. Do not submit network subscription links, browser cookies or API keys. Mentioning recent work-region changes, automated tasks or signs of credential exposure can help the platform assess the case. A network service cannot replace platform review or promise that an account restriction will be removed.

After account recovery, do not immediately resume high-concurrency tasks. First complete login and ordinary requests in a fixed environment, confirm that the account is stable and then restore automation gradually. If the cause was an exposed key, rotate it and review permissions first; if it was faulty retry logic, change the program first. Restoring the network without addressing the root cause is likely to reproduce the failure.

The core of risk reduction is not finding a magical exit that never changes. It is maintaining an explainable environment, controlled credentials, a reasonable request pace and bounded error handling. A fixed route is only one part; account security and application engineering matter just as much.

Runbook

AI ToolsSystematic Troubleshooting

Establish a known-good baseline

Systematic troubleshooting starts with a baseline. Choose a verified platform account, a device with a known state, a browser profile without complex extensions and a stable route. Complete login, send ordinary text, receive a full response and reopen the session. This combination is your control environment. When an application later fails, test the baseline first to determine whether the platform is broadly unavailable or the issue is limited to a particular device, application or route.

Validate the baseline periodically, but do not rebuild it constantly. Once the account, browser and route all change, the baseline loses its value for comparison. Teams can briefly record the baseline environment and the result of the latest test without recording credentials or conversation content. Focus on device type, application entry point, exit region, failure stage and error category.

Narrow the scope layer by layer

Layer one checks local access: whether ordinary networking works, the system clock is correct and the client has established a connection. Layer two checks the target entry point: whether the product homepage, authentication page and account data load. Layer three checks core features: text requests, streaming, attachments and generated tasks. Layer four checks the application environment: whether CLI, IDE, container or CI actually uses the expected path. Only layer five checks account permissions, quotas and platform risk controls.

Each layer should have a comparison. If the web app works but the CLI fails, the route itself is not entirely unavailable; focus on the program's proxy configuration. If several platforms cannot keep you signed in within the same browser, prioritize cookies and exit changes. If only one account fails while others work, inspect that account's status. Comparison tests are more effective than collecting large amounts of unrelated logs.

Change one variable at a time

A common inefficient approach is to change the route, browser, cache, DNS and login state all at once. Even if service returns, you will not know which action helped and will have to start over next time. Keep the account and browser unchanged, switch only to the baseline route first; if that fails, use a separate browser profile; if it still fails, check the account and platform notices. Record the result at every step and the scope will gradually narrow.

Clear site data later in the process because it removes session state that may help identify the cause. Reinstalling the client is not a first choice unless local configuration is confirmed damaged. Many issues occur at the target platform, browser-extension or application-proxy layer, and reinstalling the network client does not change those conditions.

Build a symptom matrix

Collect enough diagnostic information, but keep it restrained

A useful incident report should state the target platform, entry point, device OS, failure stage, current exit region, whether streaming was involved, whether it occurs only on a particular network and the error type returned by the page or program. Sanitized network logs can help, but remove authorization headers, cookies, API keys, subscription links and user content. If the error is reproducible, document the steps instead of saying only that it “often does not work.”

Timing information also matters because it can show whether a failure relates to a temporary platform state or local network fluctuation. Record when it occurred without guessing the cause. If the issue resolves itself, record the one change made before recovery; if nothing changed, mark it as temporary rather than crediting an action that was never performed.

Include service facts in your usage planning

RBVPN provides 100+ countries and 190+ routes, with support for Windows, macOS, iOS, Android and Linux and unlimited devices. Monthly plans include ¥9.9/month for 60GB, ¥18/month for 250GB and ¥28/month for 500GB. Traffic resets monthly on the activation date, and mid-cycle upgrades are prorated by the remaining days. Traffic packs cost ¥158/300GB, ¥358/1000GB and ¥658/3000GB; they remain available until used and never expire.

Choose a plan according to actual traffic needs across web chats, attachment tasks, code completion and API calls instead of estimating long-term usage from one short test. Verify every option on the Plan Pricing page. Payment methods are Alipay, WeChat Pay and USDT, with a 60-day no-questions-asked refund. No email address is required; a username and password are enough.

When to stop network troubleshooting

When multiple routes, access networks and separate browser profiles produce the same notice for one platform account, move to account support and the platform. When the platform clearly returns permission, quota, rate-limit or content-policy information, handle it as a business error. When only an organization-managed device fails and its policy is visible, contact the internal administrator. Aimless route switching will not produce useful information.

If the issue centers on client connections, subscription import or route selection, visit the Help Center for the relevant category. For route-selection logic for remote work and meetings, see Recommended VPN for Remote Work. This page explains the system relationships in AI scenarios; specific client actions should follow the Quick Guide and user panel.

Reliable AI tool use depends on four conditions working together: an account and region permitted by the platform, a continuous and explainable network exit, a correctly configured browser or development environment and bounded retries with controlled credentials. Managing these separately turns problems with ChatGPT, Claude, Gemini, Copilot, Midjourney and Cursor from repeated guesswork into reproducible, verifiable engineering troubleshooting.