---
title: "Introducing Hy4 Preview"
type: signal
url: https://frontiernewswire.com/s/introducing-hy4-preview-v6ef15d8f
published: 2026-08-29T23:53:13.000Z
byline: "Source: Simon Willison"
---

# Introducing Hy4 Preview

Source: Simon Willison · Published 2026-08-29 · Canonical: https://frontiernewswire.com/s/introducing-hy4-preview-v6ef15d8f

Introducing Hy4 Preview New open weight text input (no vision) LLM from Chinese company Tencent today: 770B total parameters, 49B active parameters, 1M token context window, 1.56TB on Hugging Face . This is a big size increase from their previous Hy3 in July, which was 295B, 21B active, 256,000 context, 598GB. I recently started using model chat templates to better understand their capabilities. Here's Hy4's chat\_template.jinja on Hugging Face, which includes this section: {% - if not reasoning\_effort is defined %} {% - set reasoning\_effort = 'high' %} {% - elif reasoning\_effort not in \[ 'high' , 'no\_think' \] %} {% - if reasoning\_effort is none %} {{- raise\_exception('reasoning\_effort error : None, should be no\_think/high') }} {% - else %} {{- raise\_exception('reasoning\_effort error : ' + reasoning\_effort + ', should be no\_think/high') }} {% - endif %} {% - endif %} So it looks like there are just two reasoning effort levels: "high" (the default) and "no\_think" (reason by disabled). I

In this story: [Tencent](https://frontiernewswire.com/companies/tencent), [Hy4 Preview](https://frontiernewswire.com/models/hy4-preview)

## Sources

- [Read the original at Simon Willison](https://simonwillison.net/2026/Aug/29/hy4/)

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