FreeLLMTencent launches Hy4, a 770‑billion‑parameter LLM with visual and computer‑use abilities
Tencent announced Hy4, its newest large language model, on 4 November 2026.
Tencent announced Hy4, its newest large language model, on 4 November 2026. The model contains 770 billion total parameters and 49 billion active parameters, and offers a 1 million‑token context window.
Hy4 introduces visual understanding, fine‑grained image processing, chart analysis and mathematical visual reasoning, plus the ability to interact with command‑line and graphical user interfaces for real‑world tasks.
The model shows a 19.1 % gain on the GameDev benchmark and a 9.8 % gain on the GameLogic benchmark over the earlier Hy4 Preview, while also achieving the highest score among open‑source models in a financial‑task evaluation of 579 tasks.
Tencent makes Hy4 available via Tencent Cloud services such as TokenHub, WorkBuddy, CodeBuddy and WeCom’s AI Assistant, and through third‑party platforms like OpenRouter and Hermes.
Cosa significa per te
For AI users, Hy4 provides a high‑parameter model that can handle visual inputs and automate software tasks without higher costs. For developers of free or locally hosted models, the upcoming open‑source release offers a new benchmark to compare against, while the pricing details show that large‑scale capabilities can remain affordable.
Su FreeLLMArena
From our rankings on 4 Nov 2026, based on Arena's blind votes:
- Hy4 preview: #4 among free coding models
Fonti
- Tencent releases Hy4, a powerful frontier AI model introducing visual understanding and computer use, SiliconANGLE, 4 Nov 2026
- Tencent Launches Hy4, Joining the Ranks of the World's Leading Open-Source AI Models - Tencent, tencent.com (official), 4 Nov 2026
Scritto automaticamente dalle fonti sopra, poi controllato dal nostro codice: ogni numero e nome deve comparire, e nessuna frase può copiare una fonte. Hai trovato un errore? Segnalalo.
Quale AI puoi usare gratis oggi?
Tutti i modelli AI gratuiti, classificati da voti umani anonimi, con la memoria e la velocità necessarie sulla tua GPU.