Altynai's AI Hardware Co.

Model Advisor

Three real, current open-source models — all MIT-licensed, all currently on the arena.ai agent leaderboard. For each one we show the memory math out loud, then match it to what's actually on our shelf.

DeepSeek V4 Flash

284B parameters MIT license on arena.ai leaderboard

Confirmed on DeepSeek's official Hugging Face model card: 284B total parameters (13B "active" per response -- MoE models like this only wake up part of themselves for any given answer, but the whole 284B still has to sit in memory).

Minimum GPU memory needed

284B params × 1 GB = 284.0 GB + 20% working room = 340.8 GB minimum

The 20% extra isn't optional padding — running a model also needs working memory for the conversation itself and temporary calculations, on top of the model's own weights.

What actually runs it

Recommended 4x RTX PRO 6000 Blackwell $48,000

Four workstation cards clear the memory bar for far less than any datacenter server -- the cheapest way to run this model on our shelf. See the honest note on clustering below before you buy four of anything.

Combined memory384 GB (needs 340.8 GB)
Combined power2,400 W

This is a cluster

A cluster just means multiple GPUs or machines working together on one job instead of one machine doing it alone. Real datacenter clustering connects GPUs with NVIDIA's NVLink — extremely fast, direct links that let them share memory and act like one giant GPU. Simply owning several separate cards side by side isn't the same thing: without NVLink between them, they talk over a much slower general-purpose connection and can't pool memory as seamlessly. It works, but it's not true datacenter-grade clustering.

Combined memory384 GB
Combined power2,400 W
Combined price$48,000
Total power draw 2,400 W

≈ 2.0 average homes running continuously (an average home draws about 1,200 watts around the clock). Over one full day that's 57.6 kWh — about 0.64× a typical electric car battery (roughly 90 kWh).

Alternative: 1x HGX B200 Server

Massive headroom, pre-clustered with NVLink out of the box, but far pricier than it needs to be for this model alone.

Combined memory1,440 GB
Combined power14,300 W
Price$394,406

GLM-5.2 (Max)

753B parameters MIT license on arena.ai leaderboard

Z.ai's official Hugging Face page lists 753B total parameters (the exact figure computed from the model's own files). Their official GitHub architecture spec describes it as 744B total / 40B active -- a small ~1% discrepancy between two official sources for the same model. We use 753B here since it's the number on the model's own Hugging Face card.

Minimum GPU memory needed

753B params × 1 GB = 753.0 GB + 20% working room = 903.6 GB minimum

The 20% extra isn't optional padding — running a model also needs working memory for the conversation itself and temporary calculations, on top of the model's own weights.

What actually runs it

Recommended 1x HGX B200 Server $394,406

One server alone clears the memory bar with room to spare -- and because its 8 GPUs are NVLink-connected inside the box, this is genuine datacenter-grade clustering, not several separate cards.

Combined memory1,440 GB (needs 903.6 GB)
Combined power14,300 W
Total power draw 14,300 W

≈ 11.92 average homes running continuously (an average home draws about 1,200 watts around the clock). Over one full day that's 343.2 kWh — about 3.81× a typical electric car battery (roughly 90 kWh).

DeepSeek V4 Pro

1,600B parameters MIT license on arena.ai leaderboard

Confirmed on DeepSeek's official Hugging Face model card: 1.6 trillion (1,600B) total parameters (49B active per response).

Minimum GPU memory needed

1,600B params × 1 GB = 1,600.0 GB + 20% working room = 1,920.0 GB minimum

The 20% extra isn't optional padding — running a model also needs working memory for the conversation itself and temporary calculations, on top of the model's own weights.

What actually runs it

Recommended 2x HGX B200 Servers $788,812

One server's 1,440GB falls short of the ~1,920GB this model needs, so it takes two full servers networked together to clear the bar.

Combined memory2,880 GB (needs 1,920.0 GB)
Combined power28,600 W

This is a cluster

A cluster just means multiple GPUs or machines working together on one job instead of one machine doing it alone. Real datacenter clustering connects GPUs with NVIDIA's NVLink — extremely fast, direct links that let them share memory and act like one giant GPU. Simply owning several separate cards side by side isn't the same thing: without NVLink between them, they talk over a much slower general-purpose connection and can't pool memory as seamlessly. It works, but it's not true datacenter-grade clustering.

Combined memory2,880 GB
Combined power28,600 W
Combined price$788,812
Total power draw 28,600 W

≈ 23.83 average homes running continuously (an average home draws about 1,200 watts around the clock) — this build is so power-hungry the gauge above is maxed out. Over one full day that's 686.4 kWh — about 7.63× a typical electric car battery (roughly 90 kWh).

Alternative: 1x GB300 NVL72 Rack

Enormous overkill for this model alone, but the natural next step up if you plan to run even bigger models later.

Combined memory20,000 GB
Combined power142,000 W
Price$3,800,000