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待翻譯:Introducing Hy4 Preview

AI 服務暫時不可用,以下為來源摘要,待恢復後補全翻譯:<p><strong><a href="https://hy.tencent.ai/research/hy4-preview">Introducing Hy4 Preview</a></strong></p> New open weight text input (no vision) LLM from Chinese company Tencent today: 770B total parameters, 49B active parameters, 1M token context window, <a href="https://huggingface.co/tencent/Hy4-preview">1.56TB on Hugging Face</a>.</p> <p>This is a big size increase from their previous <a href="https://huggingface.co/tencent/Hy3">Hy3</a> in July, which was 295B, 21B active, 256,000 context, 598GB.</p> <p>I recently started using model chat templates to better understand their capabilities. Here's Hy4's <a href="https://huggingface.co/tencent/Hy4-preview/blob/main/chat_template.jinja">chat_template.jinja</a> on Hugging Face, which includes this section:</p> <div class="highlight highlight-text-html-django"><pre><span class="pl-e">{%</span>- <span class="pl-k">if</span> <span class="pl-k">not</span> <span class="pl-s">reasoning_effort</span> <span class="pl-s">is</span> <span class="pl-s">defined</span> <span class="pl-e">%}</span> <span class="pl-e">{%</span>- <span class="pl-s">set</span> <span class="pl-s">reasoning_effort</span> = <span class="pl-s">'high'</span> <span class="pl-e">%}</span> <span class="pl-e">{%</span>- <span class="pl-s">elif</span> <span class="pl-s">reasoning_effort</span> <span class="pl-k">not</span> <span class="pl-k">in</span> [<span class="pl-s">'high'</span>, <span class="pl-s">'no_think'</span>] <span class="pl-e">%}</span> <span class="pl-e">{%</span>- <span class="pl-k">if</span> <span class="pl-s">reasoning_effort</span> <span class="pl-s">is</span> <span class="pl-s">none</span> <span class="pl-e">%}</span> {{- raise_exception('reasoning_effort error : None, should be no_think/high') }} <span class="pl-e">{%</span>- <span class="pl-k">else</span> <span class="pl-e">%}</span> {{- raise_exception('reasoning_effort error : ' + reasoning_effort + ', should be no_think/high') }} <span class="pl-e">{%</span>- <span class="pl-k">endif</span> <span class="pl-e">%}</span> <span class="pl-e">{%</span>- <span class="pl-k">endif</span> <span class="pl-e">%}</span></pre></div> <p>So it looks like there are just two reasoning effort levels: "high" (the default) and "no_think" (reason by disabled).</p> <p>I tried my "Generate an SVG of a pelican riding a bicycle" prompt with the default high reasoning <a href="https://openrouter.ai/tencent/hy4-preview#apps">via OpenRouter</a> and <a href="https://tools.simonwillison.net/markdown-svg-renderer#url=https%3A%2F%2Fgist.github.com%2Fsimonw%2Fcb69816b3fb940f2782569a82a523af1">got this</a>:</p> <p><img alt="Flat vector cartoon illustration of a white pelican with a large orange bill riding a red bicycle to the right along a grey road with a dashed white centre line, its orange webbed feet on the pedals and grey tail feathers fanned out behind, against a pale blue sky with a yellow sun, white clouds and horizontal white motion lines suggesting speed" src="https://static.simonwillison.net/static/2026-08-29/IMG_7725.jpeg" /></p> <p>Quoting the reasoning trace:</p> <blockquote> <p>[...] Let's maybe add a helmet? It could improve riding theme, but may obscure head. Maybe a small cycling cap or helmet? The user didn't ask; can add red helmet? Might be cute. But pelican with big beak; a helmet might obscure. Better maybe no.</p> <p>Maybe add sunglasses? no.</p> <p>Maybe add water? no.</p> </blockquote> <p>It's interesting how the reasoning trace uses slightly truncated English, presumably because perfect grammar isn't useful or token efficient for hidden reasoning text. <p>Tags: <a href="https://simonwillison.net/tags/ai">ai</a>, <a href="https://simonwillison.net/tags/generative-ai">generative-ai</a>, <a href="https://simonwillison.net/tags/llms">llms</a>, <a href="https://simonwillison.net/tags/pelican-riding-a-bicycle">pelican-riding-a-bicycle</a>, <a href="https://simonwillison.net/tags/llm-reasoning">llm-reasoning</a>, <a href="https://simonwillison.net/tags/llm-release">llm-release</a>, <a href="https://simonwillison.net/tags/ai-in-china">ai-in-china</a></p>

AI 服務暫時不可用,以下為來源正文,待恢復後補全翻譯。

Introducing Hy4 Preview Simon Willison’s Weblog Subscribe 29th August 2026 - Link Blog 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 tried my "Generate an SVG of a pelican riding a bicycle" prompt with the default high reasoning via OpenRouter and got this: Quoting the reasoning trace: [...] Let's maybe add a helmet? It could improve riding theme, but may obscure head. Maybe a small cycling cap or helmet? The user didn't ask; can add red helmet? Might be cute. But pelican with big beak; a helmet might obscure. Better maybe no. Maybe add sunglasses? no. Maybe add water? no. It's interesting how the reasoning trace uses slightly truncated English, presumably because perfect grammar isn't useful or token efficient for hidden reasoning text. Recent articles Conceptual integrity and counting lines of code - 19th August 2026 Qwen 3.8 27B is excellent, but it defaults to wildly overthinking things - 16th August 2026 Now we have a timeline of the OpenAI accidental attack against Hugging Face - 7th August 2026 This is a link post by Simon Willison, posted on 29th August 2026. ai 2,206 generative-ai 1,955 llms 1,922 pelican-riding-a-bicycle 137 llm-reasoning 102 llm-release 226 ai-in-china 108 Monthly briefing Sponsor me for $10/month and get a curated email digest of the month's most important LLM developments. Pay me to send you less! Sponsor & subscribe Disclosures Colophon &copy; 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022 2023 2024 2025 2026