体验RTX Spark一周：关于英伟达新款笔记本，我们了解到的一切
内容总结：
英伟达RTX Spark N1X处理器笔记本首测：性能强劲但价格高昂，AI与游戏体验喜忧参半
英伟达全新RTX Spark N1X处理器正式登场，多家科技媒体对搭载该“超级芯片”的高端笔记本进行了为期一周的实测。RTX Spark定位为面向笔记本和小型台式机的高性能Arm架构SoC，配备20个CPU核心、6144个GPU CUDA核心，搭载RTX Blackwell图形核心及大容量统一内存（最高128GB），目标直指苹果、英特尔、AMD和高通的最强产品。
参与测试的机型
- 微软Surface Laptop Ultra：128GB统一内存，售价5899.99美元
- 华硕ProArt P16：128GB版本售价6999.99美元
- 联想Yoga 9n 2-in-1：64GB内存
- 惠普OmniBook Ultra：32GB内存，售价3199.99美元
- 低配版18核/5120 CUDA核心的N1X芯片机型起售价2599.99美元
日常使用体验
Windows on Arm生态已大幅改善。得益于高通骁龙X系列芯片的推动，原生Arm应用日益丰富，x86应用通过微软Prism模拟层也能流畅运行。Adobe Photoshop和Premiere已有原生Arm版本，Lightroom Classic虽仍为x86应用但使用无明显问题。测试者将RTX Spark作为日常主力机使用Signal、Discord、Audacity、CapCut、Evernote、Slack等应用，未遇到实质性障碍。偶有应用加载缓慢或需重试的情况，但总体体验接近传统x86笔记本。
游戏性能：中等画质可玩，但CPU存在瓶颈
在1440p分辨率、中等画质、开启DLSS性能模式下，多数游戏可达稳定60帧。《黑神话：悟空》在原生分辨率下平均70帧，《赛博朋克2077》平均66帧，《极限竞速：地平线6》平均57帧。但CPU密集型游戏表现不佳：《地狱潜者2》即便降至DLSS 1080p也难以保证60帧；《星球大战：零号连队》帧率被限制在37-39帧。VR体验尚不稳定，部分驱动无法安装。
整体而言，RTX Spark的GPU性能介于RTX 5070和5060笔记本GPU之间。与MacBook Pro M5 Max相比，在部分GPU测试中可与之持平甚至领先，但CPU性能差距明显。
续航表现：难以支撑全天工作
华硕ProArt P16配备99.9瓦时电池，实际办公续航约5至5.5小时。网页办公功耗13-17瓦，轻量视频工作20-30瓦，视频导出峰值50瓦，游戏时可达120瓦。从140W USB-C充电，20分钟充至50%，75分钟充至95%。
本地AI：尚处早期，体验不够友好
测试者使用Hermes运行Qwen3.8-27B模型生成新闻简报，耗时10分钟并消耗10%电量，而云端Claude仅需一半时间且结果更优。本地AI在隐私保护方面有优势，但速度慢、功耗高、结果不稳定。在联想Yoga 9n上处理5张图片耗时36分钟，消耗30%电量，且首次处理出现裁剪错误。32GB内存以下机型无法运行推荐模型。Windows 11虽提供Hermes Agent、OpenClaw等一键安装，但后续配置仍需用户自行摸索。
硬件品质：高端配置，做工精良
参与测试的笔记本均配备优秀的触控板、键盘、屏幕和扬声器。金属机身质感出色，OLED屏幕显示效果极佳。华硕ProArt P16接口最丰富（3个USB-C、全尺寸SD卡槽），惠普OmniBook Ultra做工最扎实但重近5磅，联想Yoga 9n作为唯一2-in-1机型灵活性最佳。Surface Laptop Ultra的磁吸USB-C接口获得好评，被认为“苹果早该这么做”。
性能对比：GPU亮眼，CPU落后苹果
在Geekbench 6测试中，RTX Spark N1X单核约3170分，多核约20343分，远低于苹果M5 Max（单核4330、多核29143）。即便是12核M6 Mac Mini（起售价900美元）在多核性能上也能与20核N1X抗衡。GPU方面，N1X在Geekbench 6 OpenCL中得分约147750，略高于M5 Max的145613。在Blender渲染测试中，N1X与M5 Max持平，但在Premiere Pro和DaVinci Resolve基准测试中明显落后。
总结评价
Tom Warren：RTX Spark将提升Windows on Arm在创作和游戏领域的关注度，但需要更亲民的游戏版本，或许就是传闻中的N1芯片。
Sean Hollister：不错但太贵，高负载时又热又吵。更看重其代表的方向而非实际拥有。
Antonio Di Benedetto：乐见笔记本市场增加竞争，但价格令人望而却步。期待更低成本选项和第二代产品提升CPU性能，也希望推动Arm游戏生态发展。在内存价格飞涨的当下，这些笔记本的存在本身已足够有趣。
中文翻译：
Nvidia的RTX Spark N1X处理器终于来了，我们集体测试了一批搭载这款新“超级芯片”的强力笔记本，加起来价值不菲。RTX Spark被设计为一款高性能的Arm架构SoC，面向笔记本和小型台式电脑，对标苹果、英特尔、AMD和高通的最强产品。它拥有大量核心、Nvidia RTX Blackwell图形处理单元，以及足够的算力和统一内存来运行规模可观的本地AI模型。
一周体验RTX Spark：我们使用Nvidia新笔记本所学到的一切
Nvidia基于Arm架构的新款笔记本芯片是一位令人兴奋的新挑战者，但仅限高端市场。
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旗舰配置搭载于微软Surface Laptop Ultra，拥有惊人的128GB统一内存，我们的Tom Warren已对其进行了完整评测。Sean Hollister一直在测试64GB版本的华硕ProArt P16，我也在测试其顶配128GB配置。由于我是这群人里最被宠坏的，我手里还有一台64GB的联想Yoga 9n二合一和一台32GB的惠普OmniBook Ultra在测。
所有这些笔记本都搭载相同的N1X芯片，拥有20个CPU核心和6,144个GPU CUDA核心，而且它们全都贵得离谱——从惠普OmniBook的3,199.99美元到华硕ProArt的6,999.99美元不等。低价配置中有一款18核/5,120 CUDA的N1X芯片，但即便如此，Surface Laptop Ultra或较小的24GB内存华硕ProArt P14最低也要2,599.99美元。
这些是基于新芯片打造的大尺寸、高价格笔记本。它们面向开发者、程序员和内容创作者，这些人可能还想使用本地AI，甚至借助DLSS 5等Nvidia最新技术玩游戏。要测的东西很多，我们并没有大量时间来全部测完。所以以下你不会看到任何一台笔记本的详尽评分评测，而是我们三位作者使用五台笔记本一周后的印象和想法。
Nvidia的“超级芯片”真的有那么超级吗？苹果、英特尔、AMD和高通是否正式收到了警告？我们有人睡过觉吗？
它用起来顺畅吗？
Antonio Di Benedetto：Windows on Arm不再像几年前那样完全是个次等体验了。很大程度上得益于高通Snapdragon X芯片的推动，大量开发工作投入到了Windows原生Arm应用上。许多x86应用通过微软的Prism仿真层也能正常运行。
Adobe已经有一段时间提供原生Arm版本的Photoshop和Premiere了，即使我钟爱的Lightroom Classic仍然是x86应用，我在Arm上使用它也没发现任何问题。到了这个地步，你得依赖专属的x86软件，Windows on Arm才会让你完全无法接受——或者你想无忧无虑地玩任何游戏而不担心兼容性问题。
Sean Hollister：偶尔会有那么一刻，某个应用加载时间比应该的要长，我就会怀疑它到底能不能加载出来。即使如此，它通常还是能加载。偶尔需要多试一次。有一天我Alt-Tab切走时，我的Evernote笔记消失了几次，但强制刷新就解决了。而且应用似乎不尊重我系统设置的深色模式偏好。
但我在很大程度上同意Antonio的看法。我把一台RTX Spark作为日常主力机，装上了我所有典型的工作和个人应用——Signal、Discord、Audacity、CapCut和Evernote、Irfanview、Slack、ScreenToGif等等——到目前为止没有任何东西让我失望。我一次都不需要去想自己运行的是Arm还是x86应用。真正的卡顿出现在游戏和AI方面，你会在下面读到。
Tom Warren：过去两年我每天使用搭载高通芯片的Windows on Arm笔记本，情况已经改善到我再也分不清一个应用是不是原生的了。RTX Spark笔记本上也是如此，我觉得Nvidia进入这个领域只会让创意应用和游戏的故事变得更好。
它能玩游戏吗？
TW：在此之前，Windows on Arm从来都不像是一个认真的游戏平台。虽然原生Arm游戏仍然不多，但Nvidia的GPU有助于强行通过仿真层。你的游戏体验会因游戏而异，但大多数情况下我发现中等画质、1440p分辨率和DLSS性能模式，能让你在大多数游戏中获得稳定的60帧。
我主要在我的台式机上玩游戏，每天在32英寸4K屏幕上用RTX 5090开满画质，已经被惯坏了，但我并不介意15英寸屏幕上中等画质的效果。我能在原生分辨率（3270 x 2180）下以中等画质和DLSS性能模式运行《黑神话：悟空》，平均70帧。我用同样的中等画质和DLSS性能模式运行《赛博朋克2077》，平均66帧，《极限竞速：地平线6》平均57帧。
不过在某些游戏中，你可能需要降低分辨率或画质。这绝对不如专用游戏笔记本，但对于大致相当于MacBook Pro水平的设备来说，出门在外玩游戏已经绰绰有余了。
SH：就像Tom说的，GPU性能是有的——但CPU可能会拖累你的一些游戏。在《死亡回归》（1440p高画质）、《远征33》（DLSS“性能”模式升采样至1200p高画质）、《绝地幸存者》（DLSS“性能”模式升采样至1200p中等画质）和《古墓丽影：暗影》（原生1800p最高画质）中，我有足够的性能跑出流畅的60帧。
但当我启动《地狱潜者2》时，即使降到DLSS升采样至1080p，在最高难度任务中也不保证能跑60帧。屏幕上的敌人太多了，Spark跟不上。《星球大战：零号连队》更是CPU受限——无论我把画质和分辨率调到最高还是最低，Spark都不在乎。不管我怎么试，战斗中帧率通常都卡在37到39帧之间。
即使是老游戏和低配置游戏也可能有奇怪的问题。我试了2003年的《马克思·佩恩2》，在某些情况下帧率会掉到50帧。我甚至在优秀的《UFO 50》（一个2D游戏合集）中也看到了一些卡顿，不过另外几款2D游戏运行得很好。
我也不确定RTX Spark是否适合VR。优秀的《泰坦陨落2》VR模组能用，一开始似乎运行正常，但几分钟后稳定性有所下降。那可能是我的Wi-Fi问题，因为Valve Steam Frame无线适配器的驱动无法在Spark上安装。Steam的流媒体音频方案也装不了，所以音频从Nvidia笔记本而不是头显中输出。
说清楚一点，以上所有都是在假定你愿意让笔记本风扇拉满、往桌上或腿上猛排热量的前提下。这对轻薄游戏本来说并不罕见，但比一台好的台式机或掌机要吵得多、热得多。
| 2560x1600 | 2560x1600 | 2560x1600 | 2560x1600 | |
|---|---|---|---|---|
| 华硕ProArt P16 RTX Spark（20核，6144 CUDA，128GB内存） | 惠普OmniBook Ultra RTX Spark（20核，6144 CUDA，32GB内存） | Framework Laptop 16 5070（2025，8GB显存） | MacBook Pro M5 Max | |
| 黑神话：悟空 TSR | 27 | 27 | 28 | 不兼容 |
| 黑神话：悟空 DLSS | 41 | 44 | 45 | 不兼容 |
| 黑神话：悟空 DLSS帧生成 | 53 | 59 | 71 | 不兼容 |
| 赛博朋克2077 超高画质 | 41 | 46 | 57 | 56 |
| 赛博朋克2077 超高光追 & DLSS质量 | 30 | 35 | 44 | 42（MetalFX质量） |
| 赛博朋克2077 超高光追 & DLSS帧生成x2 | 53 | 56 | 68 | 75（MetalFX质量，FSR 3.1帧生成） |
| 赛博朋克2077 超高光追 & DLSS帧生成x4 | 92 | 103 | 未测试 | 不兼容 |
AD：我一直想要一台既有MacBook Pro质感又能全速玩PC游戏的笔记本，所以我非常期待这些笔记本能在图形方面交出好成绩。第一天晚上，我设置好华硕ProArt P16，它那128GB大得离谱的内存池全部就位，当我启动《Big Walk》准备和朋友们的计划线上之夜时，我的第一个想法是：“嗯，看起来还行吧。大概。”我知道《Big Walk》不是什么3A画质巨兽，但作为“朋友联机休闲”类游戏，它的画面要求还算不低。我以为N1X能把它拉满，或者至少接近拉满，但并没有。
我不得不把P16的4K屏幕降到2560 x 1600，而且没有用《Big Walk》的最高或非常高画质预设，而是降到高画质来维持还算稳定的60帧左右。对于一个和朋友解谜的休闲合作游戏来说，这些真的重要吗？当然不重要。毕竟看起来也还行。但这清醒地提醒了我，这个“超级芯片”并不是什么图形魔法师。
正如Tom和Sean指出的，RTX Spark能做一些不错的游戏，但在某些情况下要降低期望到中等甚至低画质，并准备好依赖DLSS和帧生成。不可否认，更便宜的台式机甚至搭载独立Nvidia显卡的笔记本都能轻松击败N1X。Nvidia声称它相当于把RTX 5070笔记本GPU塞进了SoC里，但在我的测试中，它介于那和RTX 5060笔记本GPU之间——肯定不差，但如果你是游戏优先，你的钱花在传统Nvidia显卡上要划算得多。
续航怎么样？
SH：Nvidia的合作伙伴觉得应该在首批RTX Spark笔记本上配备你能带上飞机而不会被盘问的最大容量电池——但即使是我华硕ProArt P16里那块99.9瓦时的电池，这些笔记本也不会在续航方面获奖。当Tom和Antonio白天在测试各种使用场景时，我把P16作为日常主力机做正常工作，同时像鹰一样盯着电池表。那主要意味着在浏览器里写稿，而它撑不过一天。
我最好的一次是5小时40分钟的真实工作，亮度50%，其中包括与Tom和Antonio的一小时视频通话，商讨我们的RTX Spark报道计划。第二天，充满电后我只用了大约5小时，因为其中两小时我在CapCut里剪辑这个视频。第三次耗尽电池，也是5小时。
做网页工作时，我通常看到笔记本默认设置下功耗为13-17瓦，但轻度视频工作会升到20-30瓦，CapCut视频导出时（短暂地）高达50瓦，而我玩《夺宝奇兵：古老之圈》时让它一路飙到120瓦。电池无法以那种速率持续供电——它慢慢下降，在30%电量时我看到了明显的性能下降，骤降到60瓦。
好消息是华硕从140W USB-C PD电源充电很快。从没电到50%用了20分钟，再15分钟到70%，总共1小时15分钟到95%。
AD：我在插电状态下跑了很多基准测试，所以没能像平时那样花那么多时间测续航。从体感上看，在断断续续的使用中，续航似乎还行。正如Sean所见，除非你刻意追求效率，否则不太可能撑过完整的八小时工作日。如果你启动任何重负载的东西，比如本地AI模型（稍后会详细说），你连午饭都撑不到。我最终会在继续使用这些笔记本的过程中做更彻底的电池测试，包括我们惯常的耗电测试来做一些一对一的比较。
本地AI看起来有用吗？
TW：目前还没有。现在这一切感觉都像是面向开发者的测试版：从AI代理安装过程中弹出的命令提示符和Visual Studio，到最基本查询都会让风扇狂转。
我很难想出很多令人信服的用例来发挥这些芯片在本地AI工作方面的算力。很多任务其实用免费的云端模型就能更快完成，而且笔记本风扇还不会狂转。这里的真正价值在于让代理全速运行一整夜来构建东西，运行开发者会喜欢的任务。
把所有东西放在本地设备上也不错，不必与云服务分享邮件和文件，不用担心隐私问题。尽管如此，我还是会经常关掉OpenClaw或Hermes，不让它们整天在后台运行，尤其是当我给了它们访问本地文件的权限时。我就是还没准备好完全信任AI，不管是不是本地的。
微软和Nvidia都设想了一个AI代理在你的PC上自动化处理事务的未来，但我还没有完全被说服。虽然有些琐碎任务我确实可以自动化，但我喜欢用PC来编辑照片或视频、写作和玩游戏。我不想坐在那里看着机器人替我做所有这些事。对我来说，那是计算乐趣的一部分。
SH：我走出Nvidia编辑日的时候想，也许我终于有理由启动本地AI了。我让运行Qwen3.8-27B的Hermes给我构建一个每日新闻简报，就像Nvidia舞台上演示的那样。它花了10分钟，消耗了我整整99.9瓦时电池的10%，最终生成了一份新闻列表，而基于云的Claude（Opus 5.5）只用了 half 的时间——同时完全占满了我的GPU，让Spark笔记本急剧升温。只要我保持Hermes打开，笔记本就一直很热而且有点卡顿。
Claude还产出了更好的结果，细节更多，来源更好。我猜我“免费”获得了本地AI的token，我不会把邮件交给Claude，我大概可以用一个更小、更轻量的模型。但我用了程序推荐的，结果就是这样。我尝试了干净重装Hermes以确保不是配置错误，但这次提示花了更长时间，消耗了60%的电池。哎。
AD：我在学习使用本地AI的旅程中还处于早期阶段，这些RTX Spark笔记本显然是可行的——尽管昂贵——选择。但即使你有128GB内存来运行一些大模型，对初学者来说仍然不是用户友好的体验。微软在Windows 11中的“入门”引导让你可以一键安装Hermes Agent、OpenClaw和Perplexity。（不知道为什么它们都有ESRB评级？）但之后，你就基本靠自己了。我一直用Hermes，因为那是我在Mac Studio上已经在用的，但如果你在32GB或更少内存的系统上使用它，它会直接告诉你没有足够内存运行它推荐的本地Qwen模型——要么引导你转向云端，要么完全靠你自己去下载一个更小的模型。
使用本地AI相比云端模型有巨大的隐私优势，但确实不太方便，因为本地LLM处理速度慢得多，对系统负担也更大。让本地模型在你的笔记本内存中运转会迅速耗尽这些笔记本的大电池，而且LLM的结果仍然参差不齐。我在36分钟内消耗了联想Yoga 9n 30%的电池，让Qwen 3.8 27B模型来调整五张PNG格式产品图片的尺寸并添加白色背景——结果它裁剪错了图片，把产品切掉了。我又用了几轮后续提示才让它做对，同时赶紧插上电源线防止Hermes在这个过程中把笔记本搞死。
硬件真的很棒吗？
AD：这些笔记本非常贵，但这也意味着厂商大多拿出了他们的最佳状态。在华硕、惠普、联想以及我从Tom对Surface的看法中了解到的情况来看，RTX Spark系列充斥着从优秀到卓越的触控板、键盘、屏幕和扬声器。我测试的三款金属机身摸起来手感极佳。OLED屏幕看起来都很棒。而且每一款对于工作站级笔记本来说都算相当薄。
如果我仅凭硬件为自己选一台，我可能会选华硕ProArt。它最符合我的需求，有三个USB-C接口、超亮屏幕、优越的倒T型方向键和全尺寸SD卡槽。惠普实际上手感最好，机身令人印象深刻地坚固，但近五磅的重量是这堆里最重的，而且它的microSD卡槽对我来说用处小得多。
至于联想，它实际上一直是我暗自最喜欢的。这是我测试的这批中唯一的二合一，这让它更灵活（双关）也更有趣。你可以在屏幕或大触控板上使用它的大号手写笔，为图形和设计工作提供了更多可能性。配合16英寸120Hz OLED的帐篷模式，偶尔玩游戏或看剧看电影都很惬意——只是不如华硕那么亮。
SH：我到目前只真正深度使用了华硕P16，但我在Nvidia编辑日上对RTX Spark首发笔记本全系的做工质量印象深刻。华硕P16可能不是我个人的选择，因为它的屏幕特别反光，触控板过于灵敏。我喜欢在有大量环境光的房间里用笔记本，发现我不得不把这台本来校准出色的OLED屏幕亮度调高。同时，我的手掌老是不小心碰到触控板，导致鼠标光标点到我不想点的东西。
扬声器和摄像头也有些不尽如人意，但Windows Hello面部登录和接近感应非常出色。我一走开，屏幕就变暗，我只要看一眼笔记本就能重新登录。尽管发热，华硕的风扇并不刺耳——游戏时非常响且明显，但至少是呼呼声而不是尖啸声。
TW：虽然我在测试Surface Laptop Ultra时遇到了一些奇怪的bug，但硬件方面我无可挑剔。外观和手感非常像MacBook Pro，磁吸USB-C接口真的感觉是苹果应该做的事情——就是这么好。大号触觉触控板延续了Surface优秀触控板的传统，还额外提供了微妙的触觉反馈，当你移动窗口或在PowerPoint等应用中对齐对象时能感受到。
我本希望Laptop Ultra能有OLED屏幕，但我发现把默认的“鲜艳”色彩选项切换到“增强”后，mini-LED面板的对比度有所改善。我也非常欣赏Laptop Ultra的接口配置，特别是有一个全尺寸SD卡读卡器甚至还有一个USB-A接口。更多想法请查看我的完整评测。
它快吗？能跟苹果M系列芯片掰手腕吗？
| 华硕ProArt P16 / Nvidia RTX Spark N1X / 128GB / 2TB | 惠普OmniBook Ultra / Nvidia RTX Spark N1X / 32GB / 1TB | 微软Surface Laptop Ultra / Nvidia RTX Spark N1X / 128GB / 1TB | MacBook Pro 16 / Apple M5 Max / 128GB / 4TB | Mac Mini (2026) / Apple M5 Pro / 48GB / 1TB / 10G以太网 | Mac Mini (2026) / Apple M6 / 24GB / 512GB | MacBook Pro 14 / Apple M5 / 16GB / 1TB | |
|---|---|---|---|---|---|---|---|
| CPU核心 | 20 | 20 | 20 | 18 | 18 | 12 | 10 |
| GPU（核心） | Nvidia N1X（6,144 CUDA核心） | Nvidia N1X（6,144 CUDA核心） | Nvidia N1X（6,144 CUDA核心） | Apple M5 Max（40核） | Apple M5 Pro（20核） | 12 | Apple M5（10核） |
| Geekbench 6 CPU单核 | 3170 | 3131 | 2864 | 4330 | 4294 | 4653 | 4208 |
| Geekbench 6 CPU多核 | 20343 | 20074 | 19030 | 29143 | 29104 | 21005 | 17948 |
| Geekbench 6 GPU（OpenCL） | 147750 | 146829 | 144352 | 145613 | 88531 | 61462 | 49059 |
| Geekbench 7 CPU单核 | 2728 | 2694 | 2705 | 3693 | 3675 | 4034 | |
| Geekbench 7 CPU多核 | 23659 | 23522 | 23445 | 35439 | 34021 | 22450 | |
| Geekbench 7 GPU（OpenCL） | 117778 | 118629 | 115241 | 153190 | 88763 | 57560 | |
| Cinebench 2026单核 | 560 | 565 | 534 | 734 | 715 | 809 | 736 |
| Cinebench 2026多核 | 6638 | 6879 | 6759 | 8952 | 8059 | 5533 | 4486 |
| Procyon图像生成 | 1301 | 1480 | 1444 | 852 | 未测试 | 未测试 | 未测试 |
| Procyon计算机视觉2 | 3650 | 3894 | 3893 | 未测试 | 未测试 | 未测试 | 未测试 |
| Procyon文本生成Phi 3.5 | 2457 | 2692 | 2555 | 4426 | 未测试 | 未测试 | 未测试 |
| Procyon文本生成Mistral 7B | 2184 | 2313 | 2233 | 3715 | 未测试 | 未测试 | 未测试 |
| Procyon文本生成Llama 3.1 8B | 2114 | 2263 | 2183 | 3498 | 未测试 | 未测试 | 未测试 |
| Procyon文本生成Llama 2 13B | 2023 | 2128 | 2078 | 3313 | 未测试 | 未测试 | 未测试 |
| PugetBench Photoshop | 未测试 | 未测试 | 13399 | 15716 | 17726 | 16739 | 12354 |
| PugetBench Premiere Pro（2.0.0+） | 未测试 | 未测试 | 82107 | 154829 | 105041 | 75108 | 71122 |
| PugetBench DaVinci Resolve（2.0.0+） | 未测试 | 未测试 | 90257 | 124942 | 85624 | 50882 | |
| Blender classroom测试（秒，越低越好） | 15 | 15 | 15 | 15 | 24 | 33 | 44 |
| Blender cosmos测试（秒，越低越好） | 62 | 61 | 62 | 35 | 51 | 84 | 未测试 |
| Premiere 4K导出（越低越好） | 未测试 | 未测试 | 2分18秒 | 1分10秒 | 1分51秒 | 2分34秒 | 2分47秒 |
| 持续SSD读取（MB/s） | 7189.07 | 10373.83 | 14537.29 | 13638.91 | 12218.07 | 6759.86 | 7049.45 |
| 持续SSD写入（MB/s） | 6719.82 | 9246.89 | 12582.13 | 17814.19 | 15420.95 | 7537.38 | 7317.6 |
| 测试价格 | $6,999.99 | $3,199.99 | $5,899.99 | $8,149 | $2,899 | $1,299 | $2,149 |
AD：是的，RTX Spark N1X是一颗强大的芯片。我们一直在测试的这些搭载大量统一内存的高端笔记本配置，是为了与苹果MacBook Pro中的Pro和Max芯片竞争。虽然它们在一些GPU性能测试中能跟上，比如在Blender渲染中与顶配M5 Max持平，但苹果的CPU要强大得多。
苹果在其自研处理器以及M6、M5 Pro和M5 Max芯片的超快“超级核心”上投入了大量开发。坦率地说，在单核性能方面没有什么能跟那些芯片竞争——甚至Nvidia的“超级芯片”也不行。（说真的，我们能不用“超级”这个词了吗？）但RTX Spark的20核CPU最让人扎心的地方在于，即使是一台低端的12核M6 Mac Mini也能在多核性能上与它竞争——而Mac Mini起价只要900美元。
不需要独立GPU就能看到这种图形性能真是太棒了，这让系统设计可以更薄，风扇噪音更小。我很喜欢，就像我喜欢AMD的Strix Halo APU一样——但和Strix Halo一样，Nvidia的RTX Spark是一颗昂贵的部件。不可否认，苹果的产品是更全面的选手，只要你不那么在乎游戏。
TW：它肯定排得上号，但我认为高通在CPU方面更接近苹果的M系列芯片。高通在收购Nuvia之前也在Windows on Arm上进行了多年实验，最终用Snapdragon X系列打造出了一款有竞争力的芯片。
我认为Nvidia在未来的RTX Spark芯片上需要在CPU方面做类似量的工作才能赶上。RTX Spark的开发至少花了三年，我从熟悉Nvidia计划的消息源那里听说芯片本应在去年推出。所以工作一直在进行，但CPU方面仍然有点令人失望。
Nvidia为其Arm架构CPU选择了联发科，这是一家更出名于笔记本Wi-Fi硬件而非CPU的芯片制造商。我真希望下一代能更强大。我在测试Surface Laptop Ultra的整个过程中忍不住想，那个禁忌之梦就是高通CPU加Nvidia GPU的组合。我看不到这在现实中会发生，但看到的话肯定会很有趣。
那我们对RTX Spark目前怎么看？
TW：我认为它会提升人们对Windows on Arm在创意和游戏任务方面的兴趣，因为在此之前我们还没有真正能玩游戏的Arm架构Windows笔记本。Nvidia首轮RTX Spark笔记本瞄准的是创作者和开发者，但这里肯定有一个更实惠、专注游戏的版本的空缺。也许那就是我们听说过传闻的N1芯片。
SH：不错，但太贵了。当你做那些理论上能证明这个价格合理的事情时，又太热太吵。我在乎它们代表什么、指向什么方向，远胜于我在乎拥有一台。
AD：我喜欢笔记本领域现在有了更多竞争，但超高的价格让RTX Spark笔记本大多遥不可及。我希望看到更便宜的选项出现，以及最终第二代产品带来更高的CPU性能，希望能进一步缩小与苹果的差距。我也希望这能推动Arm架构和Arm兼容游戏的开发向前发展。也许有一天甚至意味着游戏更容易移植到macOS。那岂不是个有趣的结果？
虽然继续测试这些超高端RTX Spark型号会很酷，但我最兴奋的是拿到一台基础版Surface Laptop Ultra或24GB内存的华硕ProArt P14，看看它们与入门级14英寸M5 MacBook Pro相比如何。那是我个人认为苹果产品线中的甜蜜点——人民的MacBook Pro。（好吧，如今起价两千美元后就不那么是了。）
在芯片选择方面，这是计算机领域激动人心的时刻，但也是绝对被诅咒的时刻，拜内存末日和天价所赐。我一直在想，如果AI需求没有推高内存和存储的价格，像这些RTX Spark甚至Googlebook这样的笔记本会卖多少钱。我不知道当PC整体销量似乎呈下降趋势时，谁会花高达7,000美元买这些笔记本，但它们存在还是很酷的。
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英文来源：
| Nvidia’s RTX Spark N1X processor is finally here, and we’ve been collectively testing a small fortune’s worth of powerful laptops sporting this new “superchip.” RTX Spark is designed to be a high-performing Arm-based SoC for laptops and small desktop computers, rivaling the best from Apple, Intel, AMD, and Qualcomm. It has loads of cores, Nvidia RTX Blackwell graphics, and enough power and unified memory to run sizable local AI models. A week with RTX Spark: everything we’ve learned using Nvidia’s new laptops Nvidia’s new Arm-based laptop chip is an exciting new challenger, but exclusively for the high-end. If you buy something from a link, The Verge may earn a commission. See our ethics statement. The flagship placement is inside Microsoft’s Surface Laptop Ultra with a staggering 128GB of unified memory, which our own Tom Warren fully reviewed. Sean Hollister has been testing a 64GB version of the Asus ProArt P16, which I’ve also been testing in its top-spec 128GB config. Since I’m the most spoiled of the lot, I also have a 64GB Lenovo Yoga 9n 2-in-1 and a 32GB HP OmniBook Ultra in for testing. All of these laptops have the same N1X chip with 20 CPU cores and 6,144 GPU CUDA cores, and they’re all wildly expensive — ranging from the HP OmniBook at $3,199.99 to the Asus ProArt’s $6,999.99. There’s an 18-core / 5,120 CUDA N1X chip in lower cost configs, but that only gets as cheap as $2,599.99 for a Surface Laptop Ultra or a smaller Asus ProArt P14 with 24GB of RAM. These are big and expensive laptops built on new chips. They’re meant for developers, coders, and content creators who might also want the ability to use local AI and even play games using the latest Nvidia tech like DLSS 5. There’s a lot to test, and we have not had a ton of time to test it all. So below you won’t find an exhaustive scored review of any one laptop, but instead our impressions and thoughts from three writers using five laptops for a week. Is Nvidia’s “superchip” really all that super? Are Apple, Intel, AMD, and Qualcomm officially on notice? Have any of us gotten any sleep? Does it just work? Antonio Di Benedetto: Windows on Arm is no longer a wholly subpar experience like it was a few years ago. Thanks in large part to the push around Qualcomm’s Snapdragon X chips, lots of development has been put into native Arm-based apps for Windows. And many x86 apps work fine via Microsoft’s Prism emulation layer. Adobe has had native Arm versions of Photoshop and Premiere for some time now, and even though my precious Lightroom Classic is still an x86-based app I don’t notice any issues using it on Arm. At this point, you’ve gotta be relying on specialized software that’s exclusively x86 based for Windows on Arm to be a non-starter — or you want to freely play any games out there without any worry of incompatibilities. Sean Hollister: Every so often, there’s that moment when an app takes longer to load than it should, and I wonder whether it’ll load at all. Even then, it typically loads. Occasionally, it takes more than one try. My Evernote notes disappeared a few times one day when I alt-tabbed away, but a force refresh fixed that. And apps don’t seem to respect my system preference for dark mode. But I largely agree with Antonio. I made an RTX Spark my daily driver, with all my typical work and personal apps — Signal, Discord, Audacity, CapCut and Evernote, Irfanview, Slack, ScreenToGif and more — and nothing has failed me so far. I never once needed to think whether I was running an Arm or an x86 app. The real hitches came with gaming and AI, as you’ll read below. Tom Warren: I’ve been using a Windows on Arm laptop with a Qualcomm chip daily for the past two years and things have improved to the point that I can’t tell if an app is native or not anymore. That’s the same story on the RTX Spark laptops, and I feel like Nvidia’s entry into this category will only improve the story for creative apps and gaming. Can it game? TW: Windows on Arm never looked like a serious gaming platform before now. While there still aren’t many native Arm games, Nvidia’s GPU helps bruteforce through the emulation layer. Your mileage in gaming is going to vary depending on the title, but for the most part I’ve found that medium settings, running at 1440p and DLSS performance, will get you to a stable 60fps in most games. I mostly game on my desktop, where I’m spoiled by using an RTX 5090 on a 32-inch 4K screen every day with maxed-out game settings, but I didn’t mind the look of medium settings on a 15-inch display. I was able to run Black Myth: Wukong at 70fps on average at native resolution (3270 x 2180) with medium settings and DLSS performance mode enabled. I ran the same medium settings and DLSS performance in Cyberpunk 2077 and averaged 66fps, and Forza Horizon 6 managed an average of 57fps. In some titles you may need to drop the resolution or settings lower, though. This definitely isn’t as good as a dedicated gaming laptop, but for something that’s roughly on the level of a MacBook Pro it’s more than good enough for gaming on the go. SH: Like Tom says, the GPU power is there — but the CPU might hold back some of your games. I had plenty of power for a smooth 60fps in Returnal (at 1440p with high settings), Expedition 33 (at a DLSS “Performance” upscaled 1200p with high settings), Jedi Survivor (DLSS “Performance” upscaled 1200p with medium settings), and Shadow of the Tomb Raider (at native 1800p and highest spec). But when I fired up Helldivers 2, even dipping down to a DLSS-upscaled 1080p was no guarantee of 60fps in the highest difficulty missions. There are just too many enemies on screen for the Spark to keep up. Star Wars Zero Company is even more CPU-bound — the Spark didn’t care whether I was maximizing or minimizing the graphics and screen resolution. No matter what I tried, I typically saw my framerate capped between 37fps and 39fps in battle. Even ancient and low-powered games can have quirks. I tried the 2003 title Max Payne 2 and saw situations where framerate dipped to 50fps. I even saw a few hitches in the excellent UFO 50, a collection of 2D games, though a couple other 2D games ran great. I’m also not sure if RTX Spark is suitable for VR yet. The excellent Titanfall 2 VR mod worked, and it seemed to run fine at first, but lost a little stability after a few minutes. That could be my Wi-Fi, because the driver for Valve’s Steam Frame wireless adapter wouldn’t install on the Spark. Neither did Steam’s streaming audio solution, so the audio came out of the Nvidia laptop instead of the headset. Just so we’re clear, all of this is assuming you want a laptop maxing out its fans and positively dumping heat on your desk or lap. That’s not unusual for thin gaming notebooks, but it’s way louder and hotter than a good desktop or handheld. 2560x1600 |
2560x1600 | 2560x1600 | 2560x1600 | |
|---|---|---|---|---|
| Asus ProArt P16 RTX Spark (20-core, 6144 CUDA, 128GB RAM) | HP OmniBook Ultra RTX Spark (20-core, 6144 CUDA, 32GB RAM) | Framework Laptop 16 5070 (2025, 8GB VRAM) | MacBook Pro M5 Max | |
| Black Myth: Wukong TSR | 27 | 27 | 28 | Not compatible |
| Black Myth: Wukong DLSS | 41 | 44 | 45 | Not compatible |
| Black Myth: Wukong DLSS FG | 53 | 59 | 71 | Not compatible |
| Cyberpunk 2077 Ultra | 41 | 46 | 57 | 56 |
| Cyberpunk 2077 Ultra RT & DLSS quality | 30 | 35 | 44 | 42 (MetalFX Quality) |
| Cyberpunk 2077 Ultra RT & DLSS Frame Gen x2 | 53 | 56 | 68 | 75 (MetalFX Quality, FSR 3.1 FG) |
| Cyberpunk 2077 Ultra RT & DLSS Frame Gen x4 | 92 | 103 | Not tested | Not compatible |
| AD: I’ve wanted a MacBook Pro-like laptop with full PC gaming chops for as long as I can remember, so I was hyped for these laptops to deliver the goods in graphics. The first night, I set up the Asus ProArt P16, with all 128GB of its ridiculously large pool of memory, and when I booted up Big Walk for my planned online evening with some friends my first thought was, “Well, that looks okay. I guess.” I know Big Walk isn’t some triple-A graphical titan, but it has some fairly demanding graphics for the “friend slop” genre. I expected the N1X to max it out, or at least get close, but not really. I had to bump the P16’s 4K display down to 2560 x 1600, and instead of Big Walk’s Highest or Very high graphics presets, I brought it down to High to maintain a decently solid 60-ish fps. Does any of that really matter for this silly co-op game about solving puzzles with your buddies? Of course not. It looked fine, after all. But it was a sobering reminder that this “superchip” is no graphical magician. As Tom and Sean point out, RTX Spark can do some decent gaming, but temper your expectations for medium or even low settings in some cases, and be ready to rely on DLSS and frame gen. There’s no denying that cheaper desktops and even laptops with discrete Nvidia graphics cards can easily beat out an N1X. Nvidia claims it’s like having an RTX 5070 Laptop GPU in an SoC, but in my testing it was somewhere between that and an RTX 5060 Laptop GPU — not a slouch, for sure, but if you’re a gamer first your money goes much further with traditional Nvidia graphics cards. How’s the battery life? SH: Nvidia’s partners saw fit to equip their first wave of RTX Spark laptops with some of the biggest batteries you can bring on an airplane with no questions asked — but even with a 99.9 watt-hour pack like the one in my Asus ProArt P16, these laptops won’t be winning awards for longevity. While Tom and Antonio spent their days testing every use case under the sun, I made the P16 my daily driver for normal work while watching the battery meter like a hawk. That mostly means writing stories in a web browser, and it’s not quite lasting the day. My best run was 5 hours and 40 minutes of real-world work at 50 percent brightness, including an hour-long video call with Tom and Antonio to strategize our RTX Spark coverage plan. The next day, I got only about 5 hours from a full charge because I spent two of them editing this video in Capcut. The third time I drained the battery, it took 5 hours, too. With web work, I’m typically seeing 13-17 watt battery drain on the laptop’s default settings, but that climbs to 20-30 watts with light video work, up to 50 watts during the (brief) Capcut video export, and I made it jump all the way to 120 watts playing Indiana Jones and the Great Circle. The battery couldn’t keep feeding at that rate — it slowly went down, and at 30 percent charge I saw a big performance hit as it dropped dramatically to 60 watts. The good news is the Asus charges fast from a 140W USB-C PD power source. It took 20 minutes to go from dead to 50 percent battery, another 15 minutes to get to 70 percent, and a total of 1 hour, 15 minutes to reach 95 percent charge. AD: I’ve had to run lots of benchmarks while plugged in, so I haven’t been able to spend as much time testing battery life as I’d normally like. Anecdotally, in lots of fits and starts, battery life seems solid. As Sean saw, you’re unlikely to get through a full eight hour work day unless you’re going out of your way to be efficient. And if you fire up anything heavy, like a local AI model (more on that in a minute), you won’t even make it to lunch. I’ll eventually do more thorough battery testing as I continue using these laptops, including our usual rundown tests for a bit of 1:1 comparisons. Does local AI seem useful? TW: Not yet. It all feels like a beta aimed at developers right now: from the install experience of AI agents flashing up command prompts and Visual Studio, to the fans blasting away for the most basic of queries. I struggled to come up with many compelling use cases for the power of these chips for local AI work. A lot of tasks could simply be done far more quickly and without the laptop fans spinning up by using a free cloud model. The power here is really in leaving the agent running at full throttle to build something overnight, running tasks that developers would favor. It’s also nice to have this all on a local device, without having to share emails and files with a cloud service and worry about the privacy aspects. Still, I would regularly close OpenClaw or Hermes and not let them run in the background all day, especially if I had given them permissions to access local files. I’m just not ready to trust AI fully, local or not. Microsoft and Nvidia both envision a future where AI agents automate things on your PC, but I’m still not fully convinced. While there are some mundane tasks I could certainly automate, I like using my PC to edit photos or videos, write, and play games. I don’t want to sit there and watch a robot do all of that for me. That’s part of the joy of computing to me. SH: I walked out of Nvidia’s Editor’s Day thinking I might finally have a reason to fire up local AI. I asked Hermes, running Qwen3.8-27B, to build me a daily news briefing much like the one in Nvidia’s on-stage demo. It took 10 minutes, and 10 percent of my entire 99.9 watt-hour battery, to finally produce a list of stories that took the cloud-based Claude (Opus 5.5) half as long — while utterly monopolizing my GPU and dramatically heating up the Spark laptop. The laptop stayed hot and a little sluggish as long as I kept Hermes open. Claude also produced better results, with more detail and better sourcing. I guess I got the local AI tokens for “free,” I wouldn’t trust Claude with my email, and I probably could have used a smaller, lighter model. But I went with what the program recommended, and that was the result. I tried a clean reinstall of Hermes to make sure it wasn’t a misconfiguration, but this time, the prompt took even longer and used 60 percent of my battery. Ouch. AD: I’m still early in my journey of learning to use local AI, and these RTX Spark laptops are obviously a viable — albeit, expensive — option. But even if you have 128GB of memory to use some chunky models, it’s still not a user-friendly experience for beginners. Microsoft’s Get Started intro in Windows 11 gives you easy one-click installs for Hermes Agent, OpenClaw, and Perplexity. (Which all have ESRB ratings for some reason?) But after that, you’re kind of on your own. I stuck with Hermes, since that’s what I was already using on the Mac Studio, but if you’re using it on a system with 32GB of RAM or less it just tells you there isn’t enough memory for its recommended local Qwen models — either routing you towards the cloud or fully relying on you to go fetch a smaller model on your own. Using local AI has major privacy advantages over cloud models, but it’s definitely less convenient since local LLMs are much slower to process and more taxing on your system. Churning a local model through your laptop’s memory tears through any of these laptops’ large batteries, and the results from LLMs are still mixed. I burned through 30 percent of the Lenovo Yoga 9n’s battery in 36 minutes to get a Qwen 3.8 27B model to resize and add a white background to five product images in PNG format — and it cropped the images wrong and cut off the products. I got it to do it right after a couple follow-up prompts, and grabbing the power cable to prevent Hermes from killing the laptop in the process. Is the hardware truly great? AD: These laptops are very expensive, but that also means the manufacturers are mostly bringing their A-games. Across the Asus, HP, Lenovo, and what I gathered from Tom’s thoughts on the Surface, the RTX Spark line is awash in great-to-excellent haptic trackpads, keyboards, screens, and speakers. The metal builds of the three I’m testing feel great to the touch. The OLED displays all look fantastic. And each of these are decently thin for the kind of workstation-class laptops that they are. If I had to pick one for myself based on hardware alone I’d probably choose the Asus ProArt. It ticks the most boxes for me with its three USB-C ports, super bright display, superior inverted-T arrow cluster, and full SD card slot. The HP actually feels the nicest, with an impressively rock-solid chassis, but at nearly five pounds it’s the heaviest of the bunch, and its microSD card slot is much less useful to me. As for the Lenovo, it’s actually been my sleeper favorite. It’s the only 2-in-1 in this crop I’ve been testing, and that just makes it more flexible (pun intended) and fun. You can use its large stylus on either the screen or the large trackpad, giving it lots more potential for graphics and design work. And tent mode with a large 16-inch 120Hz OLED is a delight for the occasional gaming session or watching shows and movies — it’s just not as bright as the Asus. SH: I’ve only truly driven the Asus P16 so far, but I was impressed with the build quality of the whole spectrum of RTX Spark launch laptops at Nvidia’s Editor’s Day. The Asus P16 probably wouldn’t be my pick personally because of its extra glossy screen and oversensitive touchpad. I like to use my laptops in rooms with lots of ambient light, and find I have to crank up the brightness of this machine’s otherwise excellent calibrated OLED screen. Meanwhile, my palms keep tapping my mouse cursor on things I didn’t mean to tap, just because they accidentally brush the touchpad while typing. The speakers and webcam also leave something to be desired, but the Windows Hello face login and proximity sensing are excellent. As soon as I walk away, the screen dims, and I’m logged right back in just by looking at my laptop. Despite the heat, Asus’ fans aren’t shrill — they’re very loud and noticeable while gaming, but at least it’s whoosh rather than whine. TW: While I ran into some weird bugs with the Surface Laptop Ultra during testing, I can’t fault the hardware. The look and feel is very similar to a MacBook Pro, and the magnetic USB-C port really feels like something Apple should have done — it’s that good. The large haptic trackpad carries on the tradition of great Surface trackpads, with the added benefit of subtle haptic feedback when you move windows around or align objects in apps like PowerPoint. I would have preferred an OLED display on the Laptop Ultra, but I found switching away from the default “Vivid” color option to “Enhanced” improved the contrast on the mini-LED panel. I also really appreciate the port section on the Laptop Ultra, especially that there’s a full SD card reader and even a USB-A port. Check out my full review for more thoughts. Is it fast? Does it hang with Apple M-series chips? Asus ProArt P16 / Nvidia RTX Spark N1X / 128GB / 2TB |
HP OmniBook Ultra / Nvidia RTX Spark N1X / 32GB / 1TB | Microsoft Surface Laptop Ultra / Nvidia RTX Spark N1X / 128GB / 1TB | MacBook Pro 16 / Apple M5 Max / 128GB / 4TB | Mac Mini (2026) / Apple M5 Pro / 48GB / 1TB / 10G Ethernet | Mac Mini (2026) / Apple M6 / 24GB / 512GB | MacBook Pro 14 / Apple M5 / 16GB / 1TB | |
|---|---|---|---|---|---|---|---|
| CPU cores | 20 | 20 | 20 | 18 | 18 | 12 | 10 |
| GPU (cores) | Nvidia N1X (6,144 CUDA cores) | Nvidia N1X (6,144 CUDA cores) | Nvidia N1X (6,144 CUDA cores) | Apple M5 Max (40 cores) | Apple M5 Pro (20 cores) | 12 | Apple M5 (10 cores) |
| Geekbench 6 CPU Single | 3170 | 3131 | 2864 | 4330 | 4294 | 4653 | 4208 |
| Geekbench 6 CPU Multi | 20343 | 20074 | 19030 | 29143 | 29104 | 21005 | 17948 |
| Geekbench 6 GPU (OpenCL) | 147750 | 146829 | 144352 | 145613 | 88531 | 61462 | 49059 |
| Geekbench 7 CPU Single | 2728 | 2694 | 2705 | 3693 | 3675 | 4034 | |
| Geekbench 7 CPU Multi | 23659 | 23522 | 23445 | 35439 | 34021 | 22450 | |
| Geekbench 7 GPU (OpenCL) | 117778 | 118629 | 115241 | 153190 | 88763 | 57560 | |
| Cinebench 2026 Single | 560 | 565 | 534 | 734 | 715 | 809 | 736 |
| Cinebench 2026 Multi | 6638 | 6879 | 6759 | 8952 | 8059 | 5533 | 4486 |
| Procyon image gen | 1301 | 1480 | 1444 | 852 | Not tested | Not tested | Not tested |
| Procyon computer vision 2 | 3650 | 3894 | 3893 | Not tested | Not tested | Not tested | Not tested |
| Procyon text gen Phi 3.5 | 2457 | 2692 | 2555 | 4426 | Not tested | Not tested | Not tested |
| Procyon text gen Mistral 7B | 2184 | 2313 | 2233 | 3715 | Not tested | Not tested | Not tested |
| Procyon text gen Llama 3.1 8B | 2114 | 2263 | 2183 | 3498 | Not tested | Not tested | Not tested |
| Procyon text gen Llama 2 13B | 2023 | 2128 | 2078 | 3313 | Not tested | Not tested | Not tested |
| PugetBench for Photoshop | Not tested | Not tested | 13399 | 15716 | 17726 | 16739 | 12354 |
| PugetBench for Premiere Pro (2.0.0+) | Not tested | Not tested | 82107 | 154829 | 105041 | 75108 | 71122 |
| PugetBench for DaVinci Resolve (2.0.0+) | Not tested | Not tested | 90257 | 124942 | 85624 | 50882 | |
| Blender classroom test (seconds, lower is better) | 15 | 15 | 15 | 15 | 24 | 33 | 44 |
| Blender cosmos test (seconds, lower is better) | 62 | 61 | 62 | 35 | 51 | 84 | Not tested |
| Premiere 4K Export (lower is better) | Not tested | Not tested | 2 minutes 18 seconds | 1 minute, 10 seconds | 1 minute, 51 seconds | 2 minutes, 34 seconds | 2 minutes, 47 seconds |
| Sustained SSD reads (MB/s) | 7189.07 | 10373.83 | 14537.29 | 13638.91 | 12218.07 | 6759.86 | 7049.45 |
| Sustained SSD writes (MB/s) | 6719.82 | 9246.89 | 12582.13 | 17814.19 | 15420.95 | 7537.38 | 7317.6 |
| Price as tested | $6,999.99 | $3,199.99 | $5,899.99 | $8,149 | $2,899 | $1,299 | $2,149 |
AD: Yes, the RTX Spark N1X is a powerful chip. These high-end laptop configurations we’ve been testing with lots of unified memory are meant to compete with the Pro and Max chips in Apple’s MacBook Pros. And while they can hang in some GPU performance tests, like tying the top spec M5 Max in a Blender render, Apple’s CPUs are much more powerful.
Apple has put lots of development into its in-house processors and the extra-fast “super cores” of its M6, M5 Pro, and M5 Max chips. And, frankly, nothing competes with those chips in single core performance — not even Nvidia’s “superchip.” (Seriously, can we stop with the word super?) But the part that stings most about the RTX Spark’s 20-core CPU is that even a lowly 12-core M6 Mac Mini competes with it in multicore performance — and a Mac Mini starts at just $900.
It’s awesome to see this kind of graphics performance without the need for a discrete GPU, allowing for thinner system designs with less noisy fans. I’m into it, just as I was with AMD’s Strix Halo APU — but like Strix Halo, Nvidia’s RTX Spark is a pricey part. And there’s no denying that Apple’s offerings are more well-rounded performers, so long as you don’t care as much about games.
TW: It’s definitely up there, but I think Qualcomm comes closer to Apple’s M-series chips on the CPU side. Qualcomm also had years of experimentation with Windows on Arm before it acquired Nuvia and managed to create a competitive chip with the Snapdragon X series.
I think Nvidia will need a similar amount of work to catch up on the CPU side for future RTX Spark chips. The development of the RTX Spark took at least three years, and I had heard from sources familiar with Nvidia’s plans that the chips were supposed to launch last year. So work has been ongoing, but the CPU side is still a little disappointing.
Nvidia picked MediaTek for its Arm-based CPU, a chipmaker that is better known for the Wi-Fi hardware in laptops, not the CPUs. I sure hope the next-generation is more powerful. The whole time I’ve been testing the Surface Laptop Ultra I couldn’t help but think the forbidden dream would be a combination of a Qualcomm CPU and Nvidia GPU. I can’t see that ever happening in reality, but it would certainly be interesting to see.
So what’s our take on RTX Spark so far?
TW: I think it will elevate interest in Windows on Arm for creative and gaming tasks, simply because we haven’t had Arm-based Windows laptops that are really capable of running games until now. Nvidia is targeting creators and developers with its first round of RTX Spark laptops, but there’s definitely a gap here for a more affordable version focused on gaming. Perhaps that’s the N1 chips we’ve heard rumors about.
SH: Nice, but too pricey. Too hot and loud when you’re doing the things that would theoretically justify that price. I care what they stand for, and the direction they’re pointed, far more than I care to own one.
AD: I love that there is now even more competition in the laptop space, but the super high prices makes RTX Spark laptops mostly unattainable. I want to see lower cost options come around, as well as an eventual second generation with higher CPU performance to hopefully close the gap further with Apple. I also hope this helps push development for Arm-based and Arm-compatible games forward. Maybe it could even one day mean easier porting of games to macOS. Wouldn’t that be a fun outcome?
As cool as it will be to keep testing these super high-end RTX Spark models, I’m most hyped to get my hands on a base Surface Laptop Ultra or Asus ProArt P14 with 24GB of RAM and see how they stack up to the entry-level 14-inch M5 MacBook Pro. That’s my personal sweet spot for Apple’s lineup — the people’s MacBook Pro. (Well, okay, less these days now that it starts at two-grand.)
It’s an exciting time in computing when it comes to chip choice, but it’s also an absolutely cursed time thanks to RAMageddon and sky high prices. I’m constantly wondering what laptops like these RTX Sparks or even Googlebooks might have cost if AI demands didn’t drive up the prices of RAM and storage. I have no idea who is going to spend up to $7,000 on these laptops when PC sales as a whole seem on a downward trend, but it’s cool they exist.
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