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Your RTX workstation already runs the model. The hard part is reaching it from your laptop, a coding agent, or a teammate’s machine without exposing your gaming PC to the internet. Run the Tokios connector next to your runtime and you get one authenticated endpoint at https://api.tokios.com that speaks both OpenAI and Anthropic request formats, so Claude Code, an OpenAI SDK script, or anyone you invite can reach the box without touching your router.

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After it runs: the endpoint gap

Desktop RTX owners — 5090, 4090, 3090, and similar cards — typically get a model answering locally with Ollama, LM Studio, llama.cpp, or vLLM, then hit the next problem: using that model from somewhere other than the desktop itself.
  • An endpoint reachable from elsewhere. The runtime binds to 127.0.0.1 by default. Reaching it from a laptop, a coding agent running elsewhere, or a teammate’s machine means binding to 0.0.0.0, forwarding a port on your home router, or standing up a tunnel — each with its own setup and no per-client auth in front of it.
  • API shape. Claude Code speaks the Anthropic Messages format; Ollama, LM Studio, llama.cpp, and vLLM speak OpenAI Chat Completions. Bridging the two usually means writing and maintaining a small proxy.
  • A stable place to point tools. Swapping between Ollama, LM Studio, llama.cpp, or vLLM on the same box, or changing which model is loaded, shouldn’t mean reconfiguring every client that talks to it.
Tokios is the connect layer that sits on top of the runtime you already run — it does not replace Ollama, LM Studio, llama.cpp, or vLLM.

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Set it up on your workstation

1

Start your runtime on the workstation

Run your model server as you normally would, for example:
or with LM Studio’s local server, llama.cpp, or vLLM:
Confirm it answers on its own OpenAI-compatible /v1 API before adding the connector.
2

Get a claim code and pair the connector

In the dashboard, open the Setup tab and select Start pairing to get a one-time claim code shaped TKS-XXXX-XXXX (valid for about 15 minutes).On Windows (PowerShell):
On Linux:
Back in the dashboard, approve the device on the Setup or Connectors tab. The connector’s token is delivered over the tunnel — you never paste it into a file.
3

Point the connector at your runtime's /v1 endpoint

The connector’s upstream is the runtime’s own OpenAI-compatible API on the workstation, not a port you forward on your router. Default ports: Ollama 11434, LM Studio 1234, llama.cpp 8080, vLLM 8000 (all with /v1 appended; for Ollama use its /v1 OpenAI-compatible API, not the native /api). No inbound firewall rule or port forward is needed — the connector only dials out.
4

Register a deployment

On the Models tab, map your upstream model id to a public deployment name such as rtx-coder. Clients send this deployment name in the model field, not the upstream id.
5

Create an API key

On the Keys tab, create a key. Keys are sk-tok-… Bearer tokens, shown once, and can be scoped to specific deployment name patterns.

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Use it from your laptop or agent

Once the connector is paired and a deployment is registered, point your client at Tokios instead of your workstation’s local network address.
Claude Code’s model picker only lists claude* ids, so your Tokios deployment won’t appear in the list — pass --model rtx-coder explicitly.
If you run more than one backend on the workstation — say Ollama for one model and vLLM for another — use the connector config file to define multiple routes and upstreams instead of the single-upstream pairing flow. See Model routing for how to register and switch between several deployments behind the same endpoint.

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How big a model can I run?

Your VRAM decides which model sizes and quantizations are realistic on a 5090, 4090, or 3090, and that’s a hardware question, not a Tokios one. See Choose a local model for sizing guidance, and Benchmark a Tokios deployment for how to compare latency and throughput across deployments once traffic is flowing through Tokios.

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Why one endpoint

  • Swap backends without touching client config. Move from Ollama to LM Studio or vLLM on the same box, and every agent and script that already targets rtx-coder keeps working — you only change the connector’s upstream, not the client.
  • No inbound ports on a home gaming PC. The connector only makes outbound connections, so you don’t forward a port on your router, bind the runtime to 0.0.0.0, or maintain your own tunnel just to reach it from a laptop or coding agent.
  • Scoped keys instead of a shared bind address. Give a teammate a key limited to specific deployment patterns instead of opening your runtime’s port to your network.

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Next steps

Quickstart

Go from zero to a working connector, deployment, and API key.

Install the connector

Full connector install and pairing reference for all platforms.

Use Claude Code

Configure ANTHROPIC_BASE_URL and ANTHROPIC_API_KEY in detail.

Connector config reference

Serve multiple models from one workstation with tokios-connector.json.