How to run any open model inside DeepSeek Harness

DeepSeek Harness (DSH) is presented as a modular interface for operating multiple AI coding and agent harnesses rather than a single harness, allowing models, tools, file systems, sandboxes, loops, and subagents such as Claude Code or Codex to be swapped and combined through plugins. Its append-only event log supports tracing, forking, replaying, and modifying agent runs, making it useful for debugging failed trajectories, inspecting tool calls, monitoring performance, and collecting post-training or reinforcement-learning data. The platform is also designed to be self-extensible, enabling users to inspect its runtime and add plugins without disrupting existing workflows. The post explains how to connect DSH’s web interface to Baseten’s OpenAI-compatible Model APIs by cloning and building the repository, configuring a custom provider with a Baseten API key, fetching the available model catalog, and selecting open-weight models such as Kimi K3, GLM 5.2, and DeepSeek V4 Pro. Users can then inspect each model run through a timeline that displays event logs and metrics including latency, time to first token, throughput, and cache-hit rates.

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