biddit

haaaaa non-binding to a charity they control?

Smells as genuine is OpenAI is non-profit

My response is not whataboutism.

It is “don’t expect the Democrat party to save us when they come back into power at the Federal level. With regard to erosion of privacy rights, I don’t see a positive track record for them.

Please surface to me what I’m missing and I’m happy to change my mind.

While Republicans certainly have a focus on illegal immigration, support for spying on American citizens is hardly a partisan issue.

ie: 25 years of Patriot Act renewal, Flock rollouts in liberal cities, Obama’s pursuit of Snowden and not the NSA itself

There is certainly liberal leadership concerned with our rights, just as there are conservatives, but they are the minority under both partisan umbrellas.

Strong disagree with the Anthropic being good at all part. This is not defending anyone else, but…

Anthropic leadership repeatedly presents themselves as uniquely morally qualified to steward agi and decide how humanity should get access to it. Yet they have repeatedly failed basic morality tests.

Pirating books for financial gain. The newer Sony/Warner music case shows this is pattern behavior.

Aggressively scraping other people's works, despite the authors' requests not to do so.

Then applying massive usage restrictions on their own work.

And probably the most disqualifying is backing away from their own hard AI safety commitments.

> This means that when this ram hits EOL it -won't- flood the consumer market in a meaningful way. It is disposed of because most people won't put a server GPU into anything. It is like a used big rig, built for purpose and when it reaches end of life it is truly at end of life.

This was true until the last year.

P40, P100, V100, A40, etc are selling like hotcakes and prices have been rapidly increasing.

That ~119 GB optimization is great. Hadn't seen that yet. That pops a 4x-Spark setup to 476 GB, which gives a lot more headroom for running something like GLM 5.2 at 4-bit, which isn't completely terrible.

I should have prefaced my post - I almost bought four Sparks a couple months ago, but ultimately opted to buy two more RTX 6000 Pro Max-Q's.

It was a painful choice because the two 6000's were more expensive than four Sparks, and ultimately gave me only 384 GB VRAM.

It was even more painful when GLM 5.2 was released, and a 4x Spark setup could run it at a decent quant, but 4x 6000's cannot with any headroom.

But the 6k's absolutely destroy the Sparks on prefill and inference speed. Model intelligence is compressing. The smaller VRAM pool will matter less over time than slower prefill/inference speed.

That is to say, I'm sure we'll end up with <500B parameter models that are Fable-level in the next 8 months or so. Performant quants of those will fit comfortably in 384 GB.

Ah yeah, your reaction makes sense. In the circles I run in, there is a lot of hype around Sparks for inference, so my gut reaction is to respond with this type of warning.

I did not intend to imply that the post author was advocating that they're great for inference, as they're obviously not.

Please don’t buy a DGX Spark unless all three of these are true:

  - You value simplicity more than performance or price-to-performance.
  - You accept that the hardware will depreciate rapidly.
  - You’re prepared to buy two or four of them.

OR:

  - You want to run frontier models right now as cheaply as possible
  - You want to run high-parameter models on a 15a breaker/line

Otherwise, get a normal, high-bandwidth GPU.

A single Spark gives you roughly 115 GB of usable memory compared with the 24–32 GB found on many lower-cost GPUs. It's certainly a big increase, but in practice it does not unlock dramatically better models.

  - One Spark: More memory, but mostly enough for poor-quality, extremely low-bit quants of larger models.  
  - Two Sparks: Enough for mid-tier parameter models at reasonable quants, such as DeepSeek V4 Flash and HY3.
  - Four Sparks: Enough for GLM 5.2 at a reasonable quant.  You'll need a $1000+ switch too.

The problem is that Sparks are slow compared with almost everything else in their price range. Many factors affect inference speed, but memory bandwidth is one of the biggest. A $4,000-plus DGX Spark provides only 273 GB/s.

  | GPU                 | Memory bandwidth |           VRAM | Approx. price  |
  | ------------------- | ---------------: | -------------: | ------------:  |
  | DGX Spark           |         273 GB/s | ~115 GB usable |        $4,000+ |
  | RTX 5060            |         448 GB/s |          16 GB |          $600  |
  | Radeon AI Pro R9700 |         640 GB/s |          32 GB |        $1,200  |
  | RTX 4000 Pro        |         672 GB/s |          24 GB |        $2,300  |
  | RTX 4500 Pro        |         896 GB/s |          32 GB |        $3,500  |
  | RTX 3090            |         936 GB/s |          24 GB |        $1,200  |
  | RTX 5000 Pro        |       1,344 GB/s |          48 GB |        $6,000  |
  | RTX 5090            |       1,792 GB/s |          32 GB |        $4,000  |
  | RTX 6000 Pro        |       1,792 GB/s |          96 GB |       $12,000  |

Yes, the Spark has substantially more memory. But going from roughly 24 GB to 115 GB does not necessarily unlock substantially better model quality. In many cases, it only lets you load heavily compressed 2-bit versions of larger models, such as DeepSeek V4 Flash, with serious quality degradation.

24–32 GB is currently a sweet spot. Models such as Qwen 3.6 27B and 35B-A3B:

  - Perform far above what their parameter counts suggest.
  - Fit comfortably within 24–32 GB of VRAM at reasonable quantization levels.

A 4-bit quant of Qwen 3.6 27b (18 GB) will out-perform a 2-bit quant of DeepSeek v4 Flash (90gb).

Instead of the Spark, if I had a roughly $4,000 budget...

Assuming I already had a reasonably modern desktop:

  - One RTX 5090, RTX 5000 Pro, or RTX 4500 Pro.
  - Two RTX 3090s, RTX 4000 Pros, or R9700s, provided the motherboard can bifurcate two physical x16 slots into x8/x8.

If I were building a system from scratch:

  - A DDR4- or PCIe 4.0-era consumer CPU and motherboard that supports x8/x8 bifurcation.
  - Two RTX 3090s, RTX 4000 Pros, or R9700s.

If I were already planning to buy a new Mac:

  - A MacBook Pro M5 with 64 GB or 128 GB of unified memory.

For context, these are the systems I currently run:

  - EPYC Turin with four RTX 6000 Pro Max-Qs.
  - EPYC Milan with four RTX 3090s.
  - AM4 with two RTX 3090s.
  - AM4 with two RTX 3090s.
  - Intel Raptor Lake with two RTX 5060 Ti.
  - MacBook Pro M3 128GB Unified

> cruelly cancelling

This is assigning intent without evidence, as is common in tribal politics. A non-charged assessment might use the phrase "abrupt cancelling."

We cannot create a better republic without constructive discourse, and we cannot have constructive discourse when we default to characterizing the views, concerns, and actions of those we disagree with as rooted in moral failure. Even if it is true from time to time.

> The polarization of politics has become so intense

> The same people who want to paint the Statue of Liberty gold seem to have no clue what it represents

You seem to be lamenting political polarization and in the same breath making character attacks on one side of the isle. Pick one.

I have a similar setup, but separate desks:

- A sitting desk for coding

- A standing desk for thinking and working on paper

There is something magical about standing while working on paper.

I’ve also found that this separation became more important to follow since the arrival of LLMs.

What an entirely unserious company. So glad I dumped Claude Code last summer after being gaslit by Anthropic over service degrades. I was fine with the service degrades, totally understandable. Being lied to, not at all.

OpenAI and Altman present a whole set of different concerns, but Codex does not get in my way of doing what I want to at all. Also let me use pi without a banhammer.

Comparing Apples to Oranges.

Apple only makes disposable devices now. They're a megacorp can negotiate massive discounts at every stage of the supply chain.

I've helped several people in the last few years set up new Macs, replacing ones that were only 1-2 years old, because they ran out of storage.

Additionally, the comparison doesn't even hold true when you need more than the base configs from Apple, given their ridiculous upgrade pricing. I'm writing this on a $6,000USD M3 MBP with 128gb/4tb. It would have been substantially cheaper to build out on a Framework.