| ▲ | chem83 an hour ago | ||||||||||||||||||||||
Not sure there's a strong use case for one of these $6K laptops yet, considering you can get a mini PC running AMD Ryzen 495 or 395 with 96, 128 and 192 GB of memory for similar amount of money and connect remotely from a cheaper/smaller/more battery-efficient laptop. Microsoft also has this same chip in non-laptop form factor: https://www.microsoft.com/en-us/surface/devices/surface-rtx-.... Coding while flying is often the use case people bring up, but the power brick these laptops come with sometimes trip the plane's power plug in coach and you can't run local AI on battery for long. Also, over time planes will get better connectivity (Starlink etc.) and that particular full-offline scenario will go away. For gaming, there are better options with dedicated GPUs like the Asus Zephyrus and similar. What am I missing? | |||||||||||||||||||||||
| ▲ | radium3d 28 minutes ago | parent | next [-] | ||||||||||||||||||||||
The strong case is pretty much only if you can't wait another 3-4 years for ram prices to come back down. Memory makers are responding with a huge build-out. Building a fab shell and cleanroom takes years, which is why the crunch has lasted so long, but many of these projects are now well underway. New capacity is what ended past memory shortages. New factories going in: SK hynix M15X, Cheongju, Korea: first wafers early 2026 (reported), ramping through 2027 Yongin Y1, Korea: first cleanroom Feb 2027 (company target) Yongin Y2, Korea: groundbreaking planned July 2027, first cleanroom June 2029 Micron ID1, Boise: first wafer output mid-2027 Tongluo, Taiwan: an existing PSMC cleanroom it bought for $1.8B, with meaningful shipments mid-2027 ID2, Boise: late 2028 Hiroshima, Japan: broke ground July 2026, with initial output late 2028 Clay, New York (up to 4 fabs, $100B): broke ground Jan 2026, with first output in 2030 Samsung P5, Pyeongtaek: mass production 2028 (reported) Yongin national complex: site work began Oct 2026, with the first fab targeting Oct 2029 (reported; Samsung hasn't given a date) Nanya Fab 5A, New Taipei: 10nm-class EUV DRAM, with wafer starts in 2H 2027 (reported) Tesla / SpaceX (Terafab) Research fab at Giga Texas, Austin: broke ground April 2026. There's no official output date. Grimes County, Texas (logic, memory, packaging; Phase 1 over $16.8B): land clearing since Aug 2026. Texas filings say commercial operations in 2028, but SemiAnalysis estimates late 2029. The first real supply relief is 2027, a second wave comes in 2028–29, and a lot of that new capacity is aimed at HBM and server memory, so consumer DDR5 and GDDR will likely ease last. Sources: Micron FQ4 2026 call, the SK hynix newsroom, TrendForce, Texas JETI filings via ENR, and Tom's Hardware/SemiAnalysis. | |||||||||||||||||||||||
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| ▲ | MrFlynn an hour ago | parent | prev | next [-] | ||||||||||||||||||||||
The core design is also approaching 3 years old at this point, so it’s not really even that competitive with the latest stuff out of the other chip makers. It’s fine, but nothing to write home about. Certainly not worth the crazy premium Nvidia is charging for it. | |||||||||||||||||||||||
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| ▲ | giancarlostoro an hour ago | parent | prev | next [-] | ||||||||||||||||||||||
The Nvidia based one uses the memory for the GPU allowing you to run AI models on the GPU, the system you're talking about has no such setup. These are Nvidia powered laptops that do what Apple does with their laptops where the system and GPU VRAM are shared as needed, except the idea here is that Nvidia designed these to perform very well for local inference, at least, that's how I understand it. | |||||||||||||||||||||||
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| ▲ | SimianSci an hour ago | parent | prev | next [-] | ||||||||||||||||||||||
The AMD hardware is x86_64, which means lower battery life on average for normal users, and as an architecture, it is very well supported across the Windows ecosystem. The RTX Spark is ARM64, which means more efficient power management at the cost of a small hit to sustained performance loads. But comes at the cost of being less supported when it comes to available software packages. Aside from this, I’m led to believe that the AMD stack when it comes to local models has more overhead related to its need to translate more NVIDIA native instructions and therefore can be less performant than Nvidia. Not sure how true this is anymore, but ive yet to hear otherwise. | |||||||||||||||||||||||
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| ▲ | 5vg an hour ago | parent | prev [-] | ||||||||||||||||||||||
i don’t think they’re flying coach after spending 6k on a laptop… | |||||||||||||||||||||||
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