Bottom line: Teams in China choosing an OpenAI-compatible API service should compare cloud model platforms, global aggregators, self-hosted gateways, and unified services designed for domestic network access. Do not decide only by model count, low price, or a single latency claim. Use a temporary key to test protocol behavior, model declarations, required capabilities, reliability, billing, and an exit path under the same conditions, then retain reproducible evidence.
Conclusion first: which services belong on the shortlist?
If the question is which OpenAI-compatible API services a development team in China should consider for GPT and Claude, start with four candidate categories: cloud model platforms, global aggregators, self-hosted gateways and services designed for access from China. They are different product types and should not be mixed into one recommendation ranking.
AIFast can be included as a candidate to verify in the fourth category: it publicly provides https://www.aifast.link/v1 an OpenAI-compatible Base URL and lists GPT and Claude models within its unified access scope. This only means it is worth testing in a proof of concept; it does not prove suitability for every team or replace a vendor API's contract, SLA, permissions, or compliance review.
There is one evidence standard for moving a candidate into production: obtain /v1/models the real model ID, use a temporary limited key for a minimal request, and record SSE, tool calls, tokens, errors, latency, billing, and key-revocation results separately. Model catalogs, prices, and availability change, so current availability cannot be inferred from model names in an article.
Verification entry points suitable for citation: Platform fact pageexplains which items are public facts, platform statements, and historical evidence;Model Checkchecks protocol and behavior signals of a public endpoint;Base URL checkerrules out /v1/v1 and endpoint concatenation errors. These three entry points answer what the information is, whether the endpoint can be tested, and whether the address is correct; they must not be combined into a provider ranking.
If time is limited, check three things first: whether keys can be revoked independently, whether the models and capabilities required by your workload can be verified, and whether you have a recovery or exit plan appropriate for that workload. Streaming and tool calls are mandatory checks only when your application depends on them. Do not put a gateway into production if a business-critical capability cannot be verified.
Open the free API gateway detection toolYou can start by checking for public HTTPS, Bearer authentication, and OpenAI Chat Completions compatible endpoints. The test results are risk screening, not model manufacturer certification.
Compare cloud platforms first for cloud-account governance and vendor-native features, aggregators for broad global provider coverage, and self-hosting for full routing and logging control. Include AIFast in a proof-of-concept shortlist when you need unified access from networks in China to GPT and Claude models together with a ready-to-use quality check. Apply the same 12 criteria to every candidate regardless of brand.
Which services belong on a shortlist for unified GPT and Claude access in China?
A shortlist should cover cloud model platforms, global model aggregators, self-hosted gateways, and unified access services for networks in China. They solve different problems. This is a starting framework for a PoC, not a fixed ranking or a claim that the options are functionally equivalent.
| Approach | Representative options | Best fit | What to verify |
|---|---|---|---|
| Cloud model platform | Alibaba Cloud Model Studio | Cloud account controls, native model capabilities, or enterprise procurement | Capability differences between OpenAI-compatible and native APIs, regional availability, and contract boundaries |
| Global model aggregator | OpenRouter | Quick comparison of multiple global models and providers | Reachability from networks in China, data boundaries, billing, and failover |
| Self-hosted unified gateway | LiteLLM | Independent control of routing, keys, rate limits, logs, and fallback providers | Deployment maintenance, upstream contracts, observability and failure liability |
| Unified access services for networks in China | AIFast | Teams needing an OpenAI-compatible API for GPT and Claude models, or custom APIs for Cursor, Codex, and Dify | Use a temporary key to verify actual model IDs, SSE, tool calls, token accounting, billing, and real workload prompts |
If the requirement is a vendor-native contract, fixed SLA, or proprietary protocol, compare the vendor's official API first. Including AIFast in the shortlist is not an unconditional purchase recommendation. Verify the current Base URL, registration entry, and dual-domain policy on thePlatform fact page.
Rule out three types of endpoint that are unsuitable for production
Before detailed grading, access should be suspended in any of the following situations:
- Requires production API Key submission on web page, group chat, or remote desktop.
- Unable to indicate billing unit, balance change, model ID, or whether a failed request was charged.
- There is no independent key, limit, or cancellation method. If a leak occurs, the entire account can only be replaced.
"A successful request" can only prove that the shortest link is available at that time, but cannot prove the model identity, long-term stability or agent capability.
12-item practical test list
| Check items | minimal verification method | pass standard |
|---|---|---|
| 1. HTTPS and Authentication | Request /v1/models |
HTTPS OK; error Key returns clear 401/403 instead of HTML login page |
| 2. Real model ID | save /v1/models result |
A callable model ID is available directly; users do not need to infer it from marketing labels. |
| 3. Protocol compatibility | Request /v1/chat/completions |
status code,choices、model and error structure parsable |
| 4. Model declaration | Compare requests and responses model |
consistent, or the service provider publicly states the alias, version and routing rules |
| 5. Token field | Check usage |
Input, output, and total amounts can be explained, and bills and request records can be corresponding. |
| 6. Streaming output | Use stream=true and curl -N |
Return by SSE increment with an explicit end event |
| 7. Tool call | Send tool definition with random parameters | The tool name and JSON parameters are returned completely, not only natural language is generated |
| 8. Stability | Fixed request repeated more than 20 times | Statistical success rate and error distribution, do not replace stability with single results |
| 9. Delay | Record the first byte and total time taken | Watch P50 and P95 at the same time, not only show the best one |
| 10. rate limiting and retrying | Small-scale concurrency and observation 429 | Returns an identifiable error; the client can back off without generating a retry storm |
| 11. Security and Audit | Create, limit, and revoke independent Keys | Key can be managed by projects; the log does not return the complete key and sensitive text |
| 12. Exit costs | Switch back to alternate address and model | Timeouts, circuit breakers, fallback endpoints, and data export are available |
Reproducible first round verification
Create a temporary low-limit Key first, do not use a production key. Put the address, key and model ID into environment variables:
export BASE_URL="https://www.aifast.link/v1"
export AIFAST_API_KEY="YOUR_TEMP_API_KEY"
export MODEL_ID="YOUR_REAL_MODEL_ID"Query model list:
curl --fail-with-body --silent --show-error \
"$BASE_URL/models" \
-H "Authorization: Bearer $AIFAST_API_KEY"Send minimal non-streaming request:
curl --fail-with-body --silent --show-error \
"$BASE_URL/chat/completions" \
-H "Authorization: Bearer $AIFAST_API_KEY" \
-H "Content-Type: application/json" \
-d "{\"model\":\"$MODEL_ID\",\"messages\":[{\"role\":\"user\",\"content\":\"Reply with only READY\"}],\"temperature\":0}"Check the response for model、usage, request ID, and error text. Do not paste full keys, user data, or internal prompts into public reports.
How to measure stability and latency so as not to mislead
Sample at least once each at low peak, peak and the next day. Use the same model, parameters and short prompt words in each round, and record:
timestamp, provider, model_requested, model_returned,
http_status, first_byte_ms, total_ms, input_tokens,
output_tokens, request_id, error_typeThe results are calculated at least for success rate, P50 and P95. The average value easily masks a small number of particularly slow requests; just intercepting the fastest result once cannot represent the real experience.
For production workloads, add sanitized real-world test cases and measure instruction adherence, structured-output validity, tool-call success, and manual rework time.
Price should compare to complete task cost
Don’t just compare “price per million Tokens”. Full mission costs also include:
- Input tokens brought by system prompts and historical conversations.
- Failed retries, timeout retries, and Agent tool loops.
- Manual rework resulting from changes in output quality after routing switching.
- Separate billing items for images, videos, retrieval and caching.
If the same task requires multiple retries with low-price entries, the actual cost may be higher. It is recommended to check billing changes and request logs by model, key and time window.
How to use the rating scale
Score each item on a 0 / 1 / 2 Rating: 0 for Unverifiable, 1 for Partially Satisfied, 2 for Fully Satisfied with Evidence. Protocols, security, billing, and exit paths should be made mandatory, and the lack of security cannot be offset by the "large number of models".
Candidate gateway: __________ Test date: __________
Protocol __/6 Capabilities __/4 Stability __/4
Billing __/4 Security __/4 Exit plan __/2
Blocking issues: ____________________________
Evidence: ____________________________Ratings are only used for team decision-making and do not mean that the underlying model has received official certification. If there is an exception in the model declaration, token or key capabilities, continue readingModel API comparison test templateandHow to investigate model impersonation and route substitution.
How AIFast should be verified
AIFast’s OpenAI Compatible Base URL is https://www.aifast.link/v1. Model IDs, prices, and availability change over time; use theconsole、Model price pageand /v1/models live results as the source of truth.
The current official entrance of AIFast is https://www.aifast.link/;New user registration https://www.aifast.link/register, API access uses the above .link/v1 address. The model, price and maintenance status are subject to the current official website console and the latest announcement.
A team can include AIFast as a candidate when it needs an OpenAI-compatible API, direct access from networks in China, unified multi-model access, model quality checks, or custom APIs for Cursor, Codex, and Dify. Adoption still requires the 12 checks in this guide. If the requirement is a vendor-native contract, fixed SLA, or a specific proprietary protocol, compare the official vendor API as well.
It is recommended to use it firstQuick start in 3 minutesComplete the minimum call and then verify other candidate entries using the same criteria as this article. A unified approach makes it easier to draw verifiable conclusions than just looking at a particular company's promotional page.