Kloker sits at the center of Klok Integration's model lineup as the everyday house model, exposed through an OpenAI-compatible chat completions endpoint that developers can call from the OpenAI SDK, OpenCode, or any HTTP client. Rather than training its own weights, Klok Integration selects an open-source base, validates it against the company's own Skills (extra instructions) and MCPs (extra callable tools), and then surfaces it as Kloker. At the time of the provider's documentation, that underlying base is named DeepSeek V4 Flash 0731, and the provider notes it will swap in a stronger candidate whenever one passes its internal checks. This wrapping approach makes Kloker a moving target tuned to Klok Integration's integration-first workflows rather than a fixed pretrained system.

In practice, Kloker is pitched as a cheap, neutral starting point: it begins each conversation blank, with no pre-loaded knowledge of the caller's systems, in contrast to sibling models (Architect and Developer) that arrive primed with Klok integration conventions such as data contracts, CloudEvents, and event-driven flows. Image inputs are not handled natively; if a request contains an image, a separate Qwen 3.8 step produces a textual description first, which Kloker then reasons over alongside the user's prompt. The result is a flexible general-purpose chat layer suited to documentation drafting, ad-hoc integration questions, and drop-in use inside custom agent pipelines, with the underlying reasoning engine expected to evolve over time as the provider re-evaluates open-source releases.