CRAB (Cross-environment Agent Benchmark) is an open-source framework developed by CAMEL-AI for constructing and evaluating environments designed for large language model (LLM) agents. It supports the creation of cross-platform environments, enabling deployment across in-memory systems, Docker-hosted environments, virtual machines, or distributed physical machines. CRAB introduces a graph-based fine-grained evaluation method and an efficient mechanism for task and evaluator construction, facilitating comprehensive assessment of agent performance across diverse settings.

crab-cross-environment-agent-benchmark

An open-source framework for building and benchmarking environments tailored for large language model (LLM) agents across multiple platforms.

CRAB: Cross-environment Agent Benchmark

LM Studio is a user-friendly desktop application designed to facilitate the local execution of large language models (LLMs) on personal computers. Supporting macOS, Windows, and Linux, it allows users to download and run models such as Llama, Mistral, Phi, Gemma, and StarCoder directly on their devices without relying on cloud services. LM Studio offers a familiar chat interface for interacting with models and includes features like document chat, an OpenAI-compatible local server, and seamless integration with models from Hugging Face. By operating entirely offline, LM Studio ensures data privacy and security, making it an ideal solution for users seeking to leverage AI capabilities locally.

lm-studio

A cross-platform desktop application enabling users to discover, download, and run large language models (LLMs) locally on their devices.

LM Studio

Ollama is a platform that allows users to run large language models (LLMs) directly on their local devices, providing access to models such as Llama 3.2, Phi 3, and Mistral. It supports macOS, Linux, and Windows, enabling users to download and run models without relying on cloud services. Ollama offers a command-line interface for precise control and supports third-party graphical user interfaces for a more visual experience. By running models locally, users maintain full data ownership, reduce latency, and avoid potential security risks associated with cloud storage.

ollama

A platform enabling users to run large language models (LLMs) locally on their devices, offering access to models like Llama 3.2, Phi 3, and Mistral.

AI Agents Tagged with: cross-platform

CRAB: Cross-environment Agent Benchmark

LM Studio

Ollama