4x DGX Spark cluster running GLM-5.2 (unpruned)
| GPU(s) | 4x Nvidia GB10 (unified, DGX Spark) |
|---|---|
| VRAM / unified memory (GB) | 512 |
| CPU | Nvidia Grace (per node) Amazon · eBay (used) · Newegg |
| Motherboard | |
| RAM | 128 GB unified per node |
| PSU | |
| Other | ConnectX-7 RoCE between nodes; vLLM multi-node TP4, MTP k=5 |
| Reported total cost | |
| Power |
Measured speed (generation tokens/sec)
📏 How measured: reported by the original source; RigBase re-checked the numbers at that source
| Model | Quant | Engine | tok/s | Details |
|---|---|---|---|---|
| GLM-5.2 | QuantTrio Int4-Int8Mix | vLLM TP4 + MTP, single-stream mean | 32.5 | ⚡ spec-decode (MTP)context: 200K max📏 Single-stream mean (source config of 2026-07-17) |
2026-07-17 config: 32.5 tok/s single-stream mean, 36.0 peak, 65-75 tok/s aggregate at 6 concurrent, 200K context. vram_gb is aggregate unified memory. Found via localmaxxing (discovery only); numbers re-checked at the original source on 2026-10-24.
Source: https://github.com/tonyd2wild/GLM-5.2-QuantTrio-200K-4x-DGX-Spark
Blank fields = not stated in the source. We never estimate build data; GPU street prices above are separately sourced and dated.
Rent before you buy: try this model on a cloud GPU for a few dollars first: Runpod (referral link; sign up with Google to get the new-user bonus)
Quick answers: Can 4x DGX Spark (GB10) run GLM-5.2?