M2 MacBook Air: The Best Entry Ticket to the AI Era at Around $400
The M2 MacBook Air is the best budget entry ticket to cloud-based AI tools, not local model power.
A Bilibili tech creator spent two weeks using the M2 MacBook Air on set and came away unexpectedly converted. His core argument: AI evolves faster than hardware, so most users should buy a "theme park ticket" — a thin-and-light laptop with great cloud AI access — rather than overspending on local compute. The M2 Air brings a full redesign, a larger brighter display, and a ProRes hardware codec the M1 lacks. macOS is more open than most expect, and tools like ChatGPT, Claude, and Doubao consistently land on Mac first. Paired with a real AI-assisted creative workflow and 6–8 hours of unplugged battery life, the M2 Air is a genuinely practical choice in its price range.
An Unexpected Change of Heart
In mid-2025, Apple's across-the-board price increases on entry-level Macs and iPads made waves in the tech community. The move put the newly launched MacBook (the new entry-level model priced at 5,499 RMB) in an awkward position — for the same budget, you could pick up an M1 Pro MacBook Pro on the second-hand market, or even an M4 MacBook Air. The value equation shifted instantly.
So the question returns to the ~3,000 RMB price range: Is there a MacBook that can handle everyday tasks like work, browsing, and media consumption, hold its own in the AI era, and even manage more demanding workloads like video editing and encoding?
One Bilibili tech creator's answer is a resounding yes — the M2 MacBook Air. He openly admits he's the type who "wouldn't give an Air a second glance," but after spending more than two weeks using the M2 Air on set, he was completely won over. This article draws on his real-world experience to explore why this seemingly unremarkable machine might just be the entry ticket to the AI era.
Why Choose the M2 MacBook Air Over the Cheaper M1?
Many people ask: if you're buying an Air, why not go with the cheaper M1 version? The creator's reasoning is refreshingly practical.
A Ground-Up Redesign
The M2 Air ditches the old wedge-shaped chassis for a new flat, boxy design that echoes the higher-end MacBook Pro lineup. The screen grows from 13.3 to 13.6 inches, brightness jumps from 400 to 500 nits, and a MagSafe 2 magnetic charging port is added to the mix.
The Hardware Upgrade That Actually Matters for Video Creators
For video creators, the most significant M2 upgrade is the addition of a ProRes hardware encode/decode engine — something the M1 entirely lacks. Combined with memory bandwidth jumping from 68 GB/s to 100 GB/s, editing and export performance sees a meaningful improvement. In the creator's words, the price premium over M1 buys you "an Air redesigned from the ground up for this era."
Cloud vs. Local AI Models: How to Think About Hardware in the AI Age
The most valuable insight in this video is the creator's perspective on hardware selection in the AI era.
You Don't Need to Build Your Own Theme Park
The creator is direct: unless you're an enthusiast who loves tinkering with AI models, or a privacy-focused power user, spending more money to run large models locally just doesn't make sense. The reason is simple — AI evolves faster than hardware can keep up. A model you can run locally today might be obsolete in a year or two.
He offers a clever analogy: all you need is a ticket to enter the theme park — you don't need to build one yourself. For the vast majority of users, the smarter move is to lean into cloud-based AI tools and invest in a stable, efficient software ecosystem. This is precisely why he made the switch from Windows PC to Mac — minimizing hardware costs and reserving budget for cloud capabilities that can be continuously upgraded.
macOS's AI App Ecosystem Advantage
Many users coming from Windows harbor a kind of unfamiliarity-driven fear of macOS, mistakenly assuming it's as locked down as iOS.
More Open Than You Think
In reality, macOS is quite open. Enable the right permissions and you can install third-party software just like on Windows, without any extra hassle. And thanks to its consistent hardware configurations, macOS is often the first platform developers target when building desktop AI applications.
AI Apps Land on Mac First
The creator points to several examples: ChatGPT, Claude, and Gemini — the world's most capable generative AI apps — typically roll out new features on Mac first. At the time of writing, Doubao's voice input method hadn't even launched on Windows yet, with the desktop version exclusive to macOS. Even some of Bilibili's own tools have Mac-native apps. He also finds Microsoft's Office suite to deliver a better experience on Mac than Windows, particularly when it comes to text rendering at high resolutions — no fuzzy fonts.
A Complete AI-Assisted Creative Workflow on the M2 MacBook Air
To demonstrate the machine's real-world productivity, the creator walks through his full scriptwriting and editing process — the most practically useful section of the video.
From Research to Finished Script
- Before writing, use a notes app to gather research and build a video outline;
- Use GPT, Grok, and similar tools to assist with research and fact-checking;
- Draft using Doubao's voice input method for faster text entry;
- Use the Claude plugin in Word for a second pass — proofreading, polishing sentences, fixing typos, and tightening phrasing;
- Finally, hand the script to Claude to organize editing notes and a rough shot list.
AI-Assisted Editing: From Footage to Final Cut
For AI-generated content, the old workflow meant writing a prompt in GPT and sending it to Midjourney. Now that ChatGPT ships with a commercially usable image generation model, the whole process happens inside a single app. Sketches and illustrations are generated as keyframes in ChatGPT, imported into tools like Jimeng for simple animations, color-graded and frame-interpolated in CapCut, and finally assembled into a complete video in DaVinci Resolve.
Battery Life: The Confidence to Work Anywhere
Thanks to the impressive unplugged performance of the ARM architecture, every step of this workflow can happen not just in a studio, but at the office, a café, a restaurant, or on a high-speed train. The creator's M2 Air gets a casual 6–8 hours of real-world use off the charger, while his M1 Pro with 81% battery health barely manages 4–5. That kind of stamina is what enables genuinely flexible work in the AI age.
Final Thoughts: A Practical Buying Strategy for the AI Era
This video isn't a rigorous hardware review — it's more of a thought-provoking take meant to spark discussion. Its real value isn't in benchmark scores; it's in proposing a purchasing philosophy worth considering: in an era of rapid AI iteration, rather than spending a fortune chasing local compute power, it makes more sense to buy an affordable, capable laptop that gives you stable access to cloud-based AI tools.
For users with a limited budget who still want meaningful productivity in the AI age, the M2 MacBook Air genuinely delivers a practical balance of battery life, ecosystem access, and price. Whether it's the right call for you ultimately depends on your own workflows and how comfortable you are living in the macOS ecosystem.
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