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Rwkv Runner

Rwkv Runner is a desktop application for setting up, managing and starting RWKV language models. It provides a chat interface and an OpenAI API-compatible interface so supported clients can connect to a started model.

Explore the practical guide ↓

Independent OpenViST project profile, based on linked sources.

Rwkv Runner — OpenViST project profile in Local & Self-hosted AI.
OpenViST project illustration. See the linked sources for product details.
Understand the project

Practical overview

When it fits

Use Rwkv Runner when you want to start an RWKV model and access it through its built-in interface or an OpenAI API-compatible client.

Who it is for

  • People who want a desktop workflow for starting and configuring RWKV models.
  • RWKV users who want to connect an OpenAI API-compatible chat client.
  • Operators who want to separate the client interface from the Python inference backend.

Documented uses

  • Install dependencies and start an RWKV model through a desktop tool.
  • Connect an OpenAI-compatible client to a running RWKV model.
  • Manage model downloads, conversion and inference settings.
  • Use the documented Python backend separately from the desktop client.
Before you choose

Requirements & limits

The repository lists installation references for Windows, macOS and Linux and specifies the MIT license.

  • The application exposes an OpenAI API-compatible interface; the README directs users to set the API URL and API key in client settings.
  • The README describes a server-backend option where Runner is used as a client by entering the server address under API URL.
  • The default configuration enables a custom CUDA kernel; the README suggests disabling it or updating the GPU driver if output is garbled.
  • The README says the WebGPU strategy can be selected for AMD, Intel and other graphics cards.
  • One-click LoRA fine-tuning is identified as Windows-only.

Check current requirements in the official documentation. Source-based guidance does not mean OpenViST has run or independently tested this project.

Source-based practical guide

Start the RWKV-Runner inference backend from a clone

Launch the backend inference service using the repository’s simple deployment example.

Before you start

  • A cloned RWKV-Runner repository.
  • Python available to run the documented backend script.

Steps

  1. Clone the repository with the command below.

    Documented command
    git clone https://github.com/josStorer/RWKV-Runner

  2. Change into the repository directory with cd RWKV-Runner.

  3. Start the inference backend with the command below.

    Documented command
    python ./backend-python/main.py

  4. To load a model, request the /switch-model API; consult the API documentation at http://127.0.0.1:8000/docs.

Expected outcome

The backend inference service is started, and the README identifies the API documentation and model-loading request.

Guide limitations

  • The guide documents starting the backend and requesting model loading, but does not provide the /switch-model request format.
  • For public services, the README advises limiting request size and max_tokens to control resource use.
Documentation 1 ↗
Source-based practical guide

Build and start the separate frontend service

Compile the frontend and start its service separately from the inference backend.

Before you start

  • A cloned RWKV-Runner repository.
  • Python and npm available to run the documented commands.

Steps

  1. Clone the repository with the command below, then enter it with cd RWKV-Runner.

    Documented command
    git clone https://github.com/josStorer/RWKV-Runner

  2. Enter the frontend directory with cd RWKV-Runner/frontend.

  3. Install frontend dependencies using the command below, then compile the frontend using the command below.

    Documented command
    npm ci
    Documented command
    npm run build

  4. Return to the repository root with cd .. and start the frontend service with the command below.

    Documented command
    python ./backend-python/webui_server.py

Expected outcome

The frontend is compiled and its service is started separately.

Guide limitations

  • This procedure covers frontend build and service startup; it does not document starting the inference backend alongside it.
Documentation 1 ↗
Evidence and transparency

Sources & review

Official repository ↗
Source record details
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Sources checked
7 October 2026
Original website title
josStorer/RWKV-Runner · Official homepage title · retained in its source language
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