A curated configuration guide and technical resource for accessing high-performance, free AI models specifically optimized for users in the Russian Federation.
The fastest way to install a skill directly from the registry.
npx clawhub@latest install free-models-ru
Copy the skill folder to one of these locations
~/.openclaw/skills/ <project>/skills/ Priority: Workspace > Local > Bundled
Copy this prompt to OpenClaw to install it automatically.
Help me install free-models-ru using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).
Get the raw skill files in a ZIP archive.
The Russian Free AI Models skill provides a technical bridge for developers and users looking to bypass regional restrictions and high subscription costs. It consolidates access to over 100 free LLMs through providers like OpenRouter, SiliconFlow, and Groq, specifically curated to work without a VPN or specialized hardware. By utilizing Openclaw Skills, developers can integrate powerful models such as DeepSeek-R1 and Nvidia Nemotron directly into their local environments.
This resource focuses on providing stable, high-context (up to 262k) endpoints for coding, reasoning, and general-purpose AI tasks. It simplifies the authentication process and provides ready-to-use configuration templates for seamless integration with AI coding agents.
To configure your environment with free models, update your profile settings as follows:
# Get your keys at:
# OpenRouter: https://openrouter.ai/keys
# Groq: https://console.groq.com
# SiliconFlow: https://cloud.siliconflow.cn/
Add this to your OpenClaw configuration file:
{
"auth": {
"profiles": {
"openrouter:default": {
"provider": "openrouter",
"mode": "api_key",
"apiKey": "sk-or-v1-YOUR_KEY"
}
}
},
"agents": {
"defaults": {
"model": {
"primary": "openrouter/nvidia/nemotron-3-super-120b-a12b:free"
}
}
}
}
The skill facilitates access to various model architectures organized by provider and context capacity. Use the following table for reference within Openclaw Skills:
| Provider | Model Example | Context Window | Use Case |
|---|---|---|---|
| OpenRouter | nvidia/nemotron-3-super | 262k | General Purpose |
| SiliconFlow | DeepSeek-R1-8B | 128k+ | Reasoning/Logic |
| Groq | GPT-OSS 120B | 40 RPM | High Speed |
| OpenRouter | qwen/qwen3-coder | 262k | Coding |
Data is managed via standard API request/response cycles without storing user prompts on the local bridge.
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