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LLM API ​

OpenAI-compatible chat completions API hosted in EU datacenters. Change the base URL and API key in your existing OpenAI SDK code and it works immediately.

Best for: applications that need language model inference with EU data residency, per-token billing, and no minimum commitment.

Activate LLM API | LLM API reference

What this is ​

WAYSCloud LLM is an OpenAI-compatible inference API at https://api.wayscloud.services/v1/llm. It implements the /v1/chat/completions and /v1/models endpoints with the same request and response format as the OpenAI API. You authenticate with a Bearer token, pick a model, and send messages. Responses can be streamed or returned as a single block. All inference runs in EU datacenters. No data leaves Europe.

When to use it ​

Use this when:

  • You need language model inference with EU data residency
  • You want to use existing OpenAI SDK code with a different provider
  • You need per-token billing without a fixed monthly commitment
  • You want access to multiple models (flagship, balanced and light chat models) through one API

Consider something else when:

What you get ​

  • OpenAI-compatible endpoint at https://api.wayscloud.services/v1/llm
  • 11 chat models: from cheap light models to flagship models with 1M-token context, all through the same endpoint
  • Streaming with server-sent events for real-time token delivery
  • EU data residency: all inference runs in European datacenters
  • Per-token billing with no minimum commitment
  • 3 plan tiers with different rate limits: Starter (60 RPM), Pro (120 RPM), Enterprise (300 RPM)

Pricing ​

All prices exclude VAT. Per-token billing.

chat/light ​

ModelMetricEUR/M tokensNOK/M tokensSEK/M tokensDKK/M tokens
deepseek-v4-flashinput tokens1.3015.4014.629.66
glm-5.3-flashinput tokens2.3327.5026.1017.25

chat/processing ​

ModelMetricEUR/M tokensNOK/M tokensSEK/M tokensDKK/M tokens
deepseek-v4.1-flashinput tokens5.586662.6441.40
glm-5.3input tokens20.46242229.68151.80
gpt-oss-120binput tokens1.6719.8018.7912.42
inklinginput tokens18.83222.75211.41139.72
kimi-k3input tokens69.75825783517.50
llama-3.3-70binput tokens2.9034.3232.5721.53
minimax-m3input tokens5.586662.6441.40
muse-glimmer-30binput tokens6.9782.5078.3051.75
qwen3.8-2.4tinput tokens27.90330313.20207

View all plans in dashboard

How it works ​

  1. Activate the LLM service in the dashboard and choose a plan (Starter, Pro, or Enterprise).
  2. Copy your API key. It is shown only once.
  3. Set the base URL to https://api.wayscloud.services/v1/llm in your OpenAI SDK or HTTP client.
  4. Send a chat completion request with your chosen model and messages array.
  5. Receive the response as a single JSON object or as a stream of server-sent events.
  6. Monitor usage in the dashboard: tokens consumed, cost by model, and recent requests.

What you see in the dashboard ​

  • Tokens this month: input + output token count with progress toward plan limit
  • Cost this month: broken down by model
  • Models used: list with per-model token consumption and average latency
  • Recent requests: timestamp, model, token count, latency, status
  • Plan details: current tier, rate limit, included tokens

Fastest way to get started ​

Dashboard ​

  1. Open my.wayscloud.services and go to AI & Machine Learning then LLM API
  2. Click Activate, choose Starter plan, and copy your API key

API ​

bash
curl -X POST https://api.wayscloud.services/v1/llm/chat/completions \
  -H "Authorization: Bearer wayscloud_llm_abc12_YOUR_SECRET" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "glm-5.3",
    "messages": [{"role": "user", "content": "What is the capital of Norway?"}],
    "max_tokens": 128
  }'

Example request and response ​

Request: Chat completion with system prompt

bash
curl -X POST https://api.wayscloud.services/v1/llm/chat/completions \
  -H "Authorization: Bearer wayscloud_llm_abc12_YOUR_SECRET" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "glm-5.3",
    "messages": [
      {"role": "system", "content": "You are a concise technical writer."},
      {"role": "user", "content": "Explain the difference between TCP and UDP in two sentences."}
    ],
    "temperature": 0.3,
    "max_tokens": 256
  }'

Response:

json
{
  "id": "chatcmpl-9f2a7b3c",
  "object": "chat.completion",
  "model": "glm-5.3",
  "choices": [
    {
      "index": 0,
      "message": {
        "role": "assistant",
        "content": "TCP is a connection-oriented protocol that guarantees ordered, reliable delivery of data through acknowledgments and retransmissions. UDP is connectionless and sends datagrams without delivery guarantees, which makes it faster but suitable only when occasional packet loss is acceptable."
      },
      "finish_reason": "stop"
    }
  ],
  "usage": {
    "prompt_tokens": 31,
    "completion_tokens": 47,
    "total_tokens": 78
  }
}

Python with OpenAI SDK:

python
from openai import OpenAI

client = OpenAI(
    base_url="https://api.wayscloud.services/v1/llm",
    api_key="wayscloud_llm_abc12_YOUR_SECRET"
)

response = client.chat.completions.create(
    model="llama-3.3-70b",
    messages=[{"role": "user", "content": "Summarize GDPR Article 17 in plain language."}],
    stream=True
)

for chunk in response:
    if chunk.choices[0].delta.content:
        print(chunk.choices[0].delta.content, end="")

Available models (prices are in the pricing section above):

ModelBest forContext
glm-5.3-flashCheapest: classification, extraction, summaries at volume1M
deepseek-v4-flashCheapest bulk processing (allow generous max_tokens)1M
deepseek-v4.1-flashFast answers, summaries, high throughput1M
minimax-m3Conversation, writing, content524k
muse-glimmer-30bCompact, fast, cost-effective chat131k
llama-3.3-70bEnterprise chat without hidden reasoning; short outputs131k
gpt-oss-120bOpen-weight general purpose131k
inklingEveryday assistants, structured extraction524k
glm-5.3Flagship: long documents, analysis, multi-step tasks1M
qwen3.8-2.4tVery large MoE: demanding analysis, long-form writing1M
kimi-k3Premium: agentic workflows, large codebases1M

Prices per model are listed in the pricing section above (input and output rates per 1M tokens, excluding VAT).

Common use cases ​

  • Customer support — draft replies, summarize tickets, classify intent
  • Content generation — blog posts, product descriptions, email templates
  • Code assistance — code review, generation, documentation, bug explanation
  • Data extraction — parse unstructured text into structured fields
  • Translation — translate text between languages with context awareness

Open in dashboard