ModelsArchitectures & capability
Tencent launches Hy4, a 770B-parameter model with vision and computer use, and says open weights will follow
Tencent has released the full Hy4, a 770B-parameter mixture-of-experts model that adds visual understanding and computer use. It is available through OpenRouter and Tencent's own tools for under $1 per million input tokens. Open weights are promised but not yet published.
From the r/AISEOInsider (via last30days) article of November 7, 2026 and cited sources: The full Hy4 can read charts and documents, reason across several images, and operate command-line tools and graphical interfaces. [4] [5]
SOURCES[4] TechNode: Tencent launches Hy4 technode.com[5] SiliconANGLE: Tencent releases Hy4 siliconangle.com
AT Pulse research deskPublished · Updated · 4 min read · AI-assisted analysisAI-assisted, not human-edited. Methodology Corrections Who owns this site
- What happened
- The full Hy4 can read charts and documents, reason across several images, and operate command-line tools and graphical interfaces. [4] [5]
- Original source
- r/AISEOInsider (via last30days) article, independent perspective
- Brief by
- AT Pulse research desk AI-assisted; publisher and contact on the desk page
- When
- November 7, 2026 article published
- Covered
- Nov 7 edition
- Evidence
- 9 sources across 9 sites
- 1Reddit: This NEW Chinese AI is WILD!reddit.com
- 2Digital Applied: Hy4 confirmed vs notdigitalapplied.com
- 3DataNorth: Hy4 Previewdatanorth.ai
- 4TechNode: Tencent launches Hy4technode.com
- 5SiliconANGLE: Tencent releases Hy4siliconangle.com
- 6Build Fast with AI: 770B under Apache 2.0buildfastwithai.com
Reach: not measured yet
The full Hy4 can read charts and documents, reason across several images, and operate command-line tools and graphical interfaces. Tencent did targeted training on Blender, CAD and workflows that span multiple programs. The model has a 1M-token context window and is offered through WorkBuddy, CodeBuddy and OpenRouter. [4] [5]
Only the Hy4 Preview can be self-hosted so far. It came out in late August under Apache 2.0 and uses a mixture-of-experts design with 770B total and 49B active parameters, a big step up from Hy3's 295B total and 21B active. As of Nov 5, the final model's weights, license and system card had not been published. [2] [3] [6]
Tencent's own benchmark table shows Hy4 trailing the leader on most of twelve agentic and coding tests. It scores 44.4 to Kimi K3.1 Pro's 66.8 on Terminal Bench 4.0, and 78.9 to Claude's 81.8 on OSWorld 2.1. The headline comparisons are Tencent-run expert preference ratings that no outside group has reproduced. [2] [7]
a model that can operate software is now available by API for less than $1 per million input tokens.
Read the full assessment
Implication: if the final weights ship under a permissive license, teams could self-host computer-use agents, though serving 49B active parameters still takes multiple GPUs.
Executive brief
The linked Reddit post's excerpt doesn't name a model. The most prominent new Chinese release in the days before it was Tencent's Hy4, announced on 4 November 2026, so this dossier assumes that is the subject. That link is an inference. The most consequential fact: Tencent says it will release the weights of a 770B-parameter model that can use a computer, at roughly $0.83 per million input tokens. As of 5 November, though, the final weights had not been published, and every benchmark so far comes from Tencent or a partner (Digital Applied).
What changed and event timeline
Hy4 Preview ships with open weights
Tencent released a 770B-total, 49B-active mixture-of-experts (MoE) model under Apache 2.0, with full and FP8 weights on Hugging Face (). Digital Applied gives the date as Aug 27 ().
Full Hy4 launches
The full model adds visual understanding and computer use, and is available through WorkBuddy, CodeBuddy and OpenRouter (;).
Free-usage window
A limited free quota runs through Nov 15. TokenHub API prices are discounted 50% through Dec 31 ().
Final weights still unpublished
The Hugging Face repository for the final model returned an error. Only the Preview could be downloaded ().
Reddit commentary
r/AISEOInsider posted "This NEW Chinese AI is WILD!". The excerpt has no technical content ().
Capabilities and access
- Model: Tencent Hy4, the final release that follows Hy4 Preview. Context window is 1M tokens (SiliconANGLE).
- What it does: reads charts and documents, reasons across multiple images, and operates command-line tools and graphical interfaces.
- Price: reports disagree. TechNode lists $0.834 input / $2.501 output per million tokens. SiliconANGLE lists $0.90 / $2.70, plus $0.045 for cached input.
Read the full section
- Model: Tencent Hy4, the final release that follows Hy4 Preview. Context window is 1M tokens (SiliconANGLE).
- What it does: reads charts and documents, reasons across multiple images, and operates command-line tools and graphical interfaces. Tencent did targeted training on Blender, CAD and workflows that span several programs (TechNode).
- Price: reports disagree. TechNode lists $0.834 input / $2.501 output per million tokens. SiliconANGLE lists $0.90 / $2.70, plus $0.045 for cached input. The gap may come from currency conversion, but that is unconfirmed.
- Planned: open weights, a system card and a cheaper "Hy4 flash" variant.
Technical analysis for researchers and developers
- Architecture: the only documented architecture is the Preview's: MoE with 770B total / 49B active parameters, 78 layers and 256 routed experts.
- Growth from Hy3: Hy3 was 295B total / 21B active with a 262K-token context (Build Fast with AI).
- Deployment: the Preview shipped with vLLM and SGLang recipes and mirrors on ModelScope, GitCode and CNB (DataNorth).
Read the full section
- Architecture: the only documented architecture is the Preview's: MoE with 770B total / 49B active parameters, 78 layers and 256 routed experts. Tencent says the final model had "substantially scaled-up pretraining," so its internals may differ (Digital Applied).
- Growth from Hy3: Hy3 was 295B total / 21B active with a 262K-token context (Build Fast with AI).
- Deployment: the Preview shipped with vLLM and SGLang recipes and mirrors on ModelScope, GitCode and CNB (DataNorth).
- Evaluation method: headline comparisons are expert-preference ratings run by Tencent, not standardized public benchmarks. No one can reproduce the final model's results until the weights and system card are out.
Claims and evidence
All of the following are Tencent's own numbers; none has been independently reproduced (Digital Applied). Independent corroboration of performance is not available.
Read the full section
All of the following are Tencent's own numbers; none has been independently reproduced (Digital Applied).
- Twelve agentic and coding benchmarks: Hy4 trails the leader on most. Examples: Terminal Bench 4.0, 44.4 vs 66.8 (Kimi K3.1 Pro); OSWorld 2.1, 78.9 vs 81.8 (Claude). Explainx compiled these from secondary outlets because Tencent's official page did not load for it (Explainx).
- Finance ratings: 3.04 vs 2.97 for DeepSeek-V4.1-Flash, judged by 213 professionals in a Tencent-run test.
- Hallucination rate: down to 5.45% from 15.76% on an internal test set.
- Game development: +19.1% on GameDev and +9.8% on GameLogic, with no baselines disclosed (SiliconANGLE).
- Preview engineering ratings: 2.99/4 vs GLM-5.3 at 2.92 and Kimi K3 at 2.94, from 163 Tencent experts on 203 tasks (DataNorth).
Independent corroboration of performance is not available.
Context and prior work
Hy4 enters a crowded Chinese open-model field that includes DeepSeek, Qwen, GLM and Kimi (GeoToolbox). In the same week, Zhipu released GLM 5.3 FlashX Legal (Nov 2) (AI Release Tracker). On Tencent's own benchmark table, Kimi K3.1 Pro is the leading Chinese competitor, and Hy4 beats it on six of twelve tests (Explainx).
Limitations, safety and contested findings
- Tencent itself says the Preview can reason longer than necessary and over-verify its own work, which adds latency and token cost (DataNorth).
- The final weights, license and system card had not been published as of Nov 5.
- Sources disagree on the Preview's release date (Aug 27 vs Aug 28) and on API pricing.
Read the full section
- Tencent itself says the Preview can reason longer than necessary and over-verify its own work, which adds latency and token cost (DataNorth).
- The final weights, license and system card had not been published as of Nov 5. That leaves the safety evaluation of the computer-use features undocumented (Digital Applied).
- Sources disagree on the Preview's release date (Aug 27 vs Aug 28) and on API pricing.
- Even on Tencent's own benchmarks, Hy4 is not the leader on most agentic tests.
Business and practitioner implications
- Testing now: the free quota (to Nov 15) and the 50% TokenHub discount make it cheap to trial (TechNode).
- Self-hosting: today only the Apache-2.0 Preview can be self-hosted. Check the final model's license when it ships.
- Computer-use agents: using Hy4 on desktop or CAD workflows needs sandboxing until a system card documents the risks.
Read the full section
- Testing now: the free quota (to Nov 15) and the 50% TokenHub discount make it cheap to trial (TechNode). Run your own evaluations on your own workloads rather than relying on vendor tables.
- Self-hosting: today only the Apache-2.0 Preview can be self-hosted. Check the final model's license when it ships.
- Computer-use agents: using Hy4 on desktop or CAD workflows needs sandboxing until a system card documents the risks.
- Infrastructure: with 49B active parameters, serving still needs multi-GPU, FP8-class hardware.