DeepSeek 公式ハーネスでローカルLLM gemma4 をAIエージェント化｜OpenClaw と同じ3課題で ◎◎○、Windows は1回目に転んだ｜ローカルLLM検証

This video presents a comparative evaluation of DeepSeek's official agent harness (dsh) with a local LLM (Gemma4) on Windows, testing it against three standardized challenges previously used with OpenClaw. The evaluation shows mixed results (◎◎○ scoring), with the first Windows attempt encountering issues. This is the 13th installment in an agent harness validation series, focusing on practical local LLM agent deployment.

Key Points

• •DeepSeek Harness (dsh) is an MIT-licensed official agent framework for deploying local LLMs as AI agents
• •Gemma4 local LLM was tested as the agent backbone using the same three standardized evaluation tasks
• •Comparative scoring system shows strong performance on 2 tasks (◎◎) and moderate on 1 task (○) relative to OpenClaw baseline
• •Windows deployment encountered initial failures on first attempt, indicating platform-specific compatibility challenges
• •Local LLM agent deployment requires careful harness selection and environment configuration for optimal performance
• •Standardized multi-task evaluation enables fair comparison across different agent frameworks and LLM backends
• •DeepSeek Harness provides an open-source alternative to proprietary agent platforms for local model deployment

Workflow Diagram

Concepts