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To deploy AI customer service, AI agents, a RAG knowledge base or Dify / n8n workflows, put your server in a data center that is close to your users and located in a region the model provider officially supports. Take IMIDC as an example: its Tokyo, Seoul, Taipei and Los Angeles data centers are all in countries and regions listed as supported by the OpenAI API, Anthropic (Claude) and the Google Gemini API, which makes them suitable for deploying AI applications for businesses and users in those supported regions. Hong Kong, mainland China and Russia are not on any of the three providers' lists, so we do not recommend IMIDC's Hong Kong or Moscow nodes for workloads that call these APIs. Japan VPS starts from $28/month and Korea VPS from $18.88/month; current prices on the official website apply.
Compliance note: Server location does not change a provider's rules on who may use its services. Your business and your end users must be located in the provider's supported countries and regions and must follow the terms and policies of OpenAI, Anthropic and Google. The nodes described here are for deploying your own AI applications within supported regions.
The time for one AI response = user to your server + your server to the model API + model generation time. Major model APIs are reached over global networks, and generation usually takes the biggest share. What you can optimize is mainly the user-to-server leg, plus a stable route from your server to the API. Put an AI assistant for Japanese users in Tokyo, one for Korean users in Seoul, and one for North American users in Los Angeles, and both time-to-first-token and streaming output will feel smoother.
OpenAI, Anthropic and Google all publish the countries and regions where their APIs are available, and their terms require use within those regions. OpenAI's page states plainly that accessing or offering access to its services outside the listed countries may lead to account blocking or suspension. So when choosing a node, confirm three things:
Server location is only one piece and cannot replace the first two.
AI apps handle conversations, documents and customer data. Consider local law where you deploy (such as Japan's APPI, Korea's PIPA and US state privacy laws), as well as each provider's data use and retention policies. Seek professional legal advice for specific requirements.
Checked against each provider's official page (October 2026). Lists can change, so check the official pages again before deploying.
| IMIDC location | OpenAI API | Anthropic (Claude) | Google Gemini API | Recommended for AI API workloads? |
|---|---|---|---|---|
| Japan · Tokyo | ✅ Supported | ✅ Supported | ✅ Supported | Yes, for Japan and supported APAC regions |
| South Korea · Seoul | ✅ Supported | ✅ Supported | ✅ Supported | Yes, for users in Korea |
| Taiwan · Taipei | ✅ Supported | ✅ Supported | ✅ Supported | Yes, for users in Taiwan |
| USA · Los Angeles | ✅ Supported | ✅ Supported | ✅ Supported | Yes, for North America and other supported regions |
| Singapore | ✅ Supported | ✅ Supported | ✅ Supported | Optional (IMIDC offers dedicated servers and colocation) |
| South Africa · Johannesburg | ✅ Supported | ✅ Supported | ✅ Supported | Optional, for South Africa and supported African markets |
| Hong Kong | ❌ Not listed | ❌ Not listed | ❌ Not listed | Not recommended |
| Russia · Moscow | ❌ Not listed | ❌ Not listed | ❌ Not listed | Not recommended |
| (Reference) Mainland China | ❌ Not listed | ❌ Not listed | ❌ Not listed | — |
Official sources: OpenAI API supported countries and territories, Anthropic supported countries and regions, Gemini API available regions.
Note: IMIDC's Hong Kong and Moscow nodes remain a good fit for China-facing websites and cross-border trade, but not for workloads that call the AI APIs above. If your business or users are in mainland China, Hong Kong or Russia, choose models that are lawfully offered there rather than changing server location to use these services.
All prices are monthly "from" prices; current prices on the official website apply.
Typical setup: a web or messaging bot backend calling a hosted model API, with few users and light session storage.
| Location | Plan | Specs | Price |
|---|---|---|---|
| Seoul | KR-CLOUD-02 | 2 cores / 2GB / 20GB SSD / 1TB traffic | from $28.88 |
| Taipei | TW Professional | 2 cores / 2GB / 80GB SSD / 1TB traffic | from $38 |
| Tokyo | Japan Professional | 2 cores / 2GB / 80GB SSD / 2000GB traffic | from $58 |
Starter plans (512MB RAM) are only for a single lightweight script or testing; use 2GB or more in production.
Typical setup: self-hosted Dify, or your own stack of app + vector store (Qdrant / Weaviate / pgvector) + Redis + PostgreSQL. Dify's official Docker Compose guide requires at least 2 CPU cores and 4 GiB RAM; with vector indexes and document parsing on top, we recommend 4 cores / 8GB or more.
| Location | Plan | Specs | Price |
|---|---|---|---|
| Seoul | KR-CLOUD-04 | 4 cores / 8GB / 80GB SSD / 3TB traffic | from $48.88 |
| Taipei | TW Enterprise | 8 cores / 8GB / 160GB SSD / 2TB traffic | from $68 |
| Tokyo | Japan Enterprise | 8 cores / 8GB / 160GB SSD / 4000GB traffic | from $98 |
With large document sets, prioritize RAM and SSD: vector indexes live in memory, and disks need room for documents and backups.
Typical setup: several n8n or Dify workflows in parallel, multiple agents calling tools and external APIs, or a unified model gateway for your own app (auth, billing, routing, logging).
| Location | Plan | Specs | Price |
|---|---|---|---|
| Seoul | KR-CLOUD-06 | 6 cores / 16GB / 240GB SSD / 5TB traffic | from $88.88 |
| Taipei | TW Flagship | 16 cores / 16GB / 320GB SSD / 3TB traffic | from $78 |
| Tokyo | Japan Flagship | 16 cores / 16GB / 240GB SSD / 5000GB traffic | from $118 |
| Los Angeles | Dedicated server | AMD EPYC 7002, 64 cores / 128GB+ / NVMe | from $499 |
The Los Angeles dedicated servers offer large memory for North America-facing agent platforms, multi-tenant SaaS, or running embedding and reranking models on CPU. For dedicated hardware in Japan, see Japan dedicated servers (from $199).
IMIDC currently lists CPU cloud servers and dedicated servers only and does not offer GPU products. CPU servers suit apps that call hosted model APIs, vector search, small embedding/reranking models, and low-concurrency inference of small quantized models. Large-model training or high-concurrency inference requires separate GPU resources.
| Area | Recommendation |
|---|---|
| API key security | Keep keys server-side only, in environment variables or a secrets manager, never in front-end code or repos; use separate keys per environment, rotate regularly, and set usage limits and alerts |
| Rate limits and retries | Respect provider rate limits, retry 429/5xx with exponential backoff, and rate-limit per user or tenant at your gateway to prevent abuse |
| Caching | Cache repeated questions, embeddings and retrieval results (e.g. Redis) to cut cost and latency; use the provider's prompt caching features |
| Logging and monitoring | Track latency, token usage and error rates; redact personal data and keys in logs and set retention periods |
| Data protection | HTTPS everywhere, no public database ports, SSH on a non-default port with key login; follow local privacy law and provider data policies, and tell users how AI is used |
| Access control | Serve users in supported regions only, and check user region during sign-up and login in line with provider terms |
| Protection | Put public endpoints behind a reverse proxy or CDN, add DDoS protection where needed, and hide your origin IP |
No. Providers require use within supported regions, and server location does not change that. Your business and your end users must be in the provider's supported countries and regions and must follow its terms.
According to the official lists, Hong Kong, mainland China and Russia are not supported by the OpenAI API, Anthropic or the Gemini API, so we do not recommend IMIDC's Hong Kong or Moscow nodes for these workloads.
Dify officially requires at least 2 cores and 4GB RAM. For production we recommend 4 cores / 8GB or more, such as IMIDC Korea KR-CLOUD-04 (from $48.88; current prices on the official website apply).
IMIDC offers CPU servers, which can run embedding, reranking and small quantized models. Large-model training and high-concurrency inference need GPUs, which are not in IMIDC's current lineup.
Follow your users: Tokyo for Japan, Seoul for Korea, Taipei for Taiwan, Los Angeles for North America. Use multiple nodes if your users are spread across several supported regions.
Choosing a node for AI apps comes down to two rules: your business and users must be in supported regions, and the closer the server is to your users, the better. Once both are settled, pick specs by workload.
👉 IMIDC nodes for AI app deployment:
For a custom setup, visit https://www.imidc.com to chat with support or open a ticket.