AICodeKing introduces Hy-4 Preview as an open-weight mixture-of-experts model intended for coding, planning, tool use and extended document tasks. The video describes its large context window and hardware requirements, while explicitly treating Tencent’s internal engineering evaluation as a vendor result that warrants caution.
The first coding task asks for a platform game built with native HTML canvas and JavaScript, including drawn pixel art, collision detection, acceleration and variable jump height. The narrator reports that the generated game handles these mechanics. A second task requests a neon street-racing game with a chase camera, drifting, boost effects, opponents and lap tracking. An unnamed comparison model reportedly omits some requested mechanics, so the example supports a limited task comparison rather than a general ranking.
The document task combines 24 reimbursement claims with dated policy versions, employee records, budgets, invoices and emails. The narrator describes a report and spreadsheet that classify claims, cite policy clauses and supporting evidence, flag potential duplicate invoices and exhausted allowances, and identify claims using an outdated policy. The narrator reports manually checking the total deductions; the video does not establish independent audit accuracy.
A final task turns research on open-weight coding models into a presentation and comparison table, with selected figures checked against sources by the narrator. Across these examples, the focus is on planning, meeting multiple constraints and maintaining consistency across files. The account remains a creator’s demonstration, with no comprehensive independent validation of the outputs or basis for treating one successful run as reliable performance on every task.
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