Let's Try Hy4 Open Weight Model - is it Better than GLM 5.3? 😳

Let's Try Hy4 Open Weight Model - is it Better than GLM 5.3? 😳

🎙 xCreate 👥 26K 📅 September 3, 2026 ⏱ 14 min 👁 11K 📄 opinion experte 🧭 2026-09-10
Available in: English (current) Français

Keywords

Hy4GLM 5.3open-sourceWorkBuddylocal inference

Summary

This video reviews Tencent’s new open-weight Hy4 model, comparing it to GLM 5.3 and other frontier models. The host tests Hy4 through Tencent’s official WorkBuddy app, which offers free access until September 10th. He runs various coding and image-generation tasks, noting the model’s ability to create complex artifacts like a Photoshop clone and a solar-system shoot-em-up game. He also demonstrates how to connect a locally running model (Qwen 3.8 via Inferencer) to WorkBuddy for hybrid local-cloud usage. The video includes benchmark highlights from the model card, showing Hy4 scoring near Claude Opus 5 on some tests. Overall, the host finds Hy4 impressive but notes the token-hungry nature of some competitors like GLM 5.3. He emphasizes the commercial-friendly Apache 2.0 license and the potential cost advantage over Claude/Codex.

127 words

Critical Evaluation

Value of the Information & Strength of the Argument

The value lies in the practical demonstration of Hy4’s capabilities, showcasing real-world performance beyond synthetic benchmarks. The argumentation is anecdotal rather than rigorous; the host relies on personal experience and subjective comparisons. He does provide concrete examples of generated outputs, which lend some credibility, but lacks systematic evaluation or statistical evidence. The discussion of local vs cloud integration adds practical utility, but the overall assessment is impressionistic.

Scientific Rigor, Source Quality, Title Accuracy

The video is a product review without citations to scientific literature. Sources are limited to the official WorkBuddy app, OpenRouter, and Inferencer links in the description. The title is appropriate and not misleading, though ‘better than GLM 5.3’ is a strong claim not fully substantiated by the informal tests. No comments analysis is possible as no comment data was provided.

142 words

Title / Content Match

Title accurately reflects the content: a direct comparison attempt against GLM 5.3 through practical tests.

Quality & Reliability

6/10

Video is a practical hands-on review of the Hy4 model with subjective assessments and some benchmark references. No rigorous methodology or verification of claims, but useful for real-world impressions.

Key Moments

Cited Sources

  • WorkBuddy AI — Official Tencent application used for testing Hy4 preview, offering free access until September 10th.
  • Inferencer — Local LLM server software used to run Qwen 3.8 and connect to WorkBuddy.
  • OpenRouter Hy4 Preview — API access point for the Hy4 preview model mentioned in the description.
  • Hy3 companion video — Previous video covering Hy3 for comparison purposes.
  • GLM 5.3 companion video — Previous video testing GLM 5.3 to compare with Hy4.

External References

Contribution & Novelties

The video provides a first-hand look at Hy4’s practical capabilities, especially its code generation and multi-file workspace handling. It demonstrates the integration of local models with a cloud-based agent environment, which is a novel workflow. The ‘Pour aller plus loin’ section suggests deeper exploration:

  • Mixture of experts — Relevant to Hy4’s architecture, which likely uses MoE for efficiency.
  • Apache License 2.0 — The license under which Hy4 is released, important for commercial use.
  • Open-weight model — Discusses the concept of open-weight AI models and their implications.

86 words

Radar Profile

The profile shows moderate scores with a slight edge in technical level (7) reflecting the practical setup and local integration demonstrations. Information quality and reliability are moderate (6), as the review is subjective but grounded in hands-on testing. Overall, the video is more illustrative than analytical.

Reliability 6/10