GamingAgent

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GamingAgent is an AI Agents & Automation tool that enables and tests LLM/VLM-based agents in standardized interactive gaming environments. It provides a platform for evaluating state-of-the-art models and deploying customized gaming agents.

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At a glance

Pricing

Open Source

Free tier

Yes

API

Yes

Skill level

Technical

About

What is GamingAgent?

GamingAgent is a comprehensive platform designed for the development and evaluation of LLM/VLM-based agents within interactive gaming environments. It facilitates the testing of state-of-the-art models across a diverse suite of video games, both in vanilla single-model VLM settings and with a customized GamingAgent workflow that enhances model gaming performance. The tool supports a wide range of models including those from OpenAI, Anthropic, Gemini, xAI, Deepseek, and Qwen. It also offers an easy solution for deploying computer use agents (CUAs) for gaming directly on PCs and laptops. Researchers and developers can utilize GamingAgent to benchmark model performance, analyze game performance, and generate replay videos, making it an invaluable resource for AI research in gaming.

Best used for

Ideal for developers and data scientists who need to evaluate the performance of LLM/VLM agents in various video games, deploy customized gaming agents, and analyze AI model behavior. Especially valuable for AI researchers and game developers looking to push the boundaries of AI in interactive entertainment.

Common actions

evaluate AI models

develop gaming agents

benchmark AI performance

deploy computer agents

github copilot"AI Agents"face swappingdeepfakeautomated workflowworkflowscollaborationopen-sourcelow-code/no-code

Capabilities

Key features

LLM/VLM agent evaluation
Gaming harness deployment
Computer-use agents
Diverse game environments
Performance benchmarking
Video replay generation
API key integration

Target Audience

developerdata scientistgamer

Integrations

Not yet documented

Pricing & Plans

Open Source

Free

FAQs

What types of AI models does GamingAgent support for evaluation?

GamingAgent supports a wide range of state-of-the-art models, including those from OpenAI (e.g., gpt-4o, gpt-4o-mini), Anthropic (e.g., claude-4-opus), Gemini (e.g., gemini-2.5-pro), xAI (grok-3-mini), Deepseek (reasoner), and Qwen (Qwen3). This allows for comprehensive comparative analysis across different LLM/VLM architectures.

Can I integrate my own custom games or environments into GamingAgent?

Yes, GamingAgent is designed to be extensible. You can integrate your own game implementations by following Gymnasium or Stable Retro instructions. This involves setting up your gaming environment to connect with an LLM/VLM agent by implementing observation making and agent action processing methods, and adding agent configurations.

How does GamingAgent help in understanding game performance?

GamingAgent provides tools for performance analysis, including a Colab notebook for reproducing analysis from their paper and visualizing model performance against benchmarks. It also allows for the generation of replay videos for games like Sokoban and Tetris, using agent config files and episode logs, to visually understand agent behavior.

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