Hunyuan Hy4 + WorkBuddy: 6 Real-World Agent Tests Reveal Strong Multimodal Coding & Reasoning
The author tests Tencent's Hunyuan Hy4 model across six demanding agent workflows in WorkBuddy — video generation from docs, lecture-to-webpage conversion, game cloning, 3D teardown simulators, industry report generation, and templated PPT creation — finding Hy4 handles 30-40 minute long-horizon tasks with solid code, vision, and planning at $0.55/task, 62% cheaper than Kimi K3.1 Pro.
The article presents a hands-on evaluation of Tencent's Hunyuan Hy4 (official release) integrated with WorkBuddy, an agent orchestration platform. The author, Lao Zhang, previously used Hy4 preview extensively and now tests the GA version across six production-grade scenarios.
Benchmark Context
Agent Arena data shows Hy4 ranked 14th overall. Among open-source models, it ties Kimi K3.1 Pro for first place once weights are released. On 8,500+ real long-horizon agent tasks, Hy4 achieves a +4.7% net gain and sits on the Pareto frontier. Cost per task is $0.55 versus Kimi K3.1 Pro (Max) at $1.46 — a 62% reduction — with scores within 1 percentage point. Tencent's own technical blog acknowledges Hy4 still trails top closed-source models on frontier math, long-horizon development, model iteration, and visual QA benchmarks.
Test 1: Documentation to Video Pipeline
Input: WorkBuddy official getting-started guide URL. Process: Z-web-pack skill scrapes page text and images; Z-article-to-video skill extracts narration script and TTS segment; Hy4 generates a complete Remotion project in pure code; final render produces a video with background music. The full pipeline (described as far more complex than the linear summary) completed in ~30 minutes, yielding the author's first 10+ minute video using this method.
Test 2: 54-Minute Lecture to Interactive Knowledge Page
Source: A 54-minute talk by "Potato Sister" titled "Teaching Agents to Work Like Real Engineers." Method: Audio transcribed to text; video frames extracted every 10 seconds; both transcript and frames fed to Hy4's new vision capability; output structured as an interactive web page with section summaries, key frames, Q&A, and full transcript. Execution time ~40 minutes. Result captured video highlights, detailed section breakdowns, and key visuals.
Test 3: Cute Web Mini-Game Clone
Inspired by a Kris Yang creation built with Opus 5.5. Author provided a screenshot from Peppa Pig (hilltop house) as visual reference. Hy4 iterated through multiple versions, demonstrating understanding, planning, coding, and aesthetic sense. The final game replicates the original's details and design touches.
Test 4: 3D Teardown Simulators as Single-File HTML
Using a previously arena-winning "teardown" skill, the author tasked Hy4 with building interactive 3D exploded-view simulators — camera aperture blades, combination lock mechanism — delivered as self-contained offline HTML files. Features: part explosion, cross-section cuts, view switching, auto-tour. All test cases produced working results.
Test 5: AI Short-Drama Industry Deep Research Report
Prompt: Write a data-rich, well-argued, illustrated PDF report on the AI short-drama sector within A-share listed companies, formatted for mobile reading. Hy4 spent ~30 minutes retrieving latest data from credible sources. Output: a multi-decade-page PDF with detailed analysis, charts, and mobile-friendly layout.
Test 6: Templated PPT Generation
Requirement: Strict adherence to a specific visual template (author notes >80% of office workers need this). Workflow: Provide company template to Hy4 first, then generate slides on top. Output: both an HTML preview and an editable PPTX file. The author's PPT-generation skill on Skillhub nears 10,000 downloads.
Conclusion
Across six heavyweight tests — 30-40 minute long chains, multimodal frame analysis, pure-code 3D/engineering builds, and research synthesis — Hy4 in WorkBuddy delivered consistently. The combination of WorkBuddy's agent framework and Hy4's newly added vision capability proves effective for real productivity tasks. The author recommends others run their own heavy workloads to verify.
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Old Zhang's AI Learning
AI practitioner specializing in large-model evaluation and on-premise deployment, agents, AI programming, Vibe Coding, general AI, and broader tech trends, with daily original technical articles.
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