Private model endpoints,built for agents.

From zero to first inference

Five steps. Pick your language. Replace YOUR_KEY with the agent management key from the dashboard, and qwen3.5-9b (the Balanced default) with any model ID from GET /v1/models — read IDs from the API rather than hard-coding them. Upgrading older code? See the migration guide.

Pay-as-you-go, by the minute

One billing model. Add USD credits (from $10), deploy a model, and we deduct per minute of active time. Pause or delete and the meter stops. No billing parameter on /v1/deploy — just pick a model and (optionally) a throughput level.

Prices are under review and may change; live rates are always on the pricing page.

MCP and agent frameworks

Auxen exposes a Model Context Protocol server at https://api.auxen.ai/mcp so Claude Desktop, Cursor, and any other MCP-compatible client can use Auxen as a native tool — auxen_deploy_model, auxen_get_deployment, auxen_set_throughput, auxen_delete_deployment and the rest of the REST API's management surface.

{
  "mcpServers": {
    "auxen": {
      "command": "npx",
      "args": [
        "-y",
        "mcp-remote",
        "https://api.auxen.ai/mcp",
        "--header",
        "Authorization: Bearer auxen_live_xxx"
      ]
    }
  }
}

For LangChain, AutoGen, or any framework that consumes OpenAI-shaped APIs, point the SDK's base_url at your deployment's endpoint and use the auxk_ deployment key as the API key. See the OpenAI compatibility section below.

Already using OpenAI? Switch in one line.

Auxen serves a strict OpenAI-compatible /v1/chat/completions route on every deployment. Streaming, tool calls, and standard token-usage envelopes all work the way OpenAI clients expect.

from openai import OpenAI

client = OpenAI(
  base_url="https://api.openai.com/v1",
  api_key="sk-..."
)

resp = client.chat.completions.create(
  model="<your-frontier-model>",
  messages=[{"role":"user","content":"Hi"}]
)

from openai import OpenAI

client = OpenAI(
  base_url="https://api.auxen.ai/v1/inst_xxx/v1",
  api_key="auxk_..."
)

resp = client.chat.completions.create(
  model="auxen",  # ignored
  messages=[{"role":"user","content":"Hi"}]
)

The model parameter is ignored — the model is determined by which deployment you're calling. Pass anything; we keep it in the response for clients that introspect.

Step-by-step reasoning is off by default for faster answers. Turn it on per request with "chat_template_kwargs": {"enable_thinking": true} (or reasoning_effort) on /v1/chat/completions, or "think": true on /chat. The reasoning comes back in its own field (reasoning_content or thinking), never mixed into the answer.

Errors and rate limits

Every error returns a stable code you can branch on, plus a human message and a docs link. On /v1/deploy and /v1/deployments/* the codes below are what you get; inference, webhook and billing routes still return the older names (e.g. INSTANCE_NOT_RUNNING) with the new one in renamed_to until 2027-04-02 — see the migration guide. Rate limit: 1,000 requests/minute per key. On 429s, read the Retry-After header.