Can you run Nemotron 3 Super 120B A12B locally?
Nemotron 3 family · 2026 · 123.6B parameters (12B activated per token) · Hugging Face model card
NVIDIA Nemotron 3 Super is a 120B-total / 12B-active hybrid model (vendor card: Total Parameters 120B, 12B active, designated 120B-A12B). The HF safetensors total is 123,611,012,096 in bfloat16, slightly above the announced 120B because the checkpoint includes the multi-token-prediction head. config.json declares 512 routed experts with 22 active per token plus 1 shared expert (shared intermediate 5376), 88 layers, hidden size 4096, 32 attention heads, only 2 KV heads, head dim 128, vocab 131072, on the nemotron_h hybrid Mamba/attention architecture. Native context is 262,144 tokens. Licensed under NVIDIA's model license (other). Local VRAM fit uses the 12B active count: roughly 8 GB at Q4-class quantization (calculated). Measured speeds: not yet published here.
Minimum: 8 GB+ memory (Q4-class on 12B active, calculated) · Recommended: 16 GB+ for comfortable context headroom (Q4-class, calculated)
How much VRAM does Nemotron 3 Super 120B A12B need at each quantization?
Nemotron 3 Super 120B A12B needs 82.0 GB of VRAM at Q4_K_M. The table below lists weights-only size and total VRAM including overhead for each common quantization level with 4k and 32k token contexts.
| Quantization | Bits / weight | Weights only | Total + KV @4k ctx | Total + KV @32k ctx |
|---|---|---|---|---|
| Q4_K_M | 4.8 | 74.2 GB | 82.0 GB | 84.5 GB |
| Q5_K_M | 5.7 | 88.1 GB | 97.3 GB | 99.8 GB |
| Q6_K | 6.6 | 102.0 GB | 112.6 GB | 115.1 GB |
| Q8_0 | 8.5 | 131.3 GB | 144.8 GB | 147.4 GB |
| FP16 | 16 | 247.2 GB | 272.3 GB | 274.9 GB |
Hybrid Mamba/attention stack (nemotron_h) with only 2 KV heads; config also sets mamba_hidden/mamba_num_heads for the SSM layers. Ships a built-in MTP head.
Method: weights = parameters × bits-per-weight (Q4_K_M ≈ 4.8, Q5_K_M ≈ 5.7, Q6_K ≈ 6.6, Q8_0 ≈ 8.5, FP16 = 16), plus 10% loading overhead, plus KV cache from the verified architecture config (88 layers, 2 KV heads, 128 head dim). Source: HF-verified 2026-09-30 via plain api (gated=false safetensors.total=123611012096 params=123.61B ctx=262144 license=other repo=nvidia/NVIDIA-Nemotron-3-Super-120B-A12B-BF16@2dc98e2afe4face0e4ce40972a915c45368bd34a layers=88 hidden=4096 kv_heads=2 heads=32 vocab=131072). MoE: num_experts=512 num_experts_per_tok=22 active_params_b=12.0 (vendor model card (Total 120B, 12B active); config n_routed_experts=512, 22 per token). VRAM figures are documented calculations (Q4-class ~0.6 GB per B params, on active params for MoE rows), not measurements. release_date is the HF repo lastModified date observed on the verification pass. No tok/s or benchmark scores invented.
Which GPUs can run Nemotron 3 Super 120B A12B locally?
At Q4_K_M with a 4k context, Nemotron 3 Super 120B A12B needs 82.0 GB of VRAM. The lists below are computed live from our GPU database and grouped by how much headroom the card has. Disclosure: CompareAIHardware.com participates in the Amazon Associates program and earns from qualifying purchases through links on this page. Affiliate relationships do not influence our recommendations.
Runs Nemotron 3 Super 120B A12B comfortably (25%+ VRAM headroom)
| GPU | VRAM | Bandwidth | Type | |
|---|---|---|---|---|
| H200 SXM | 141 GB | 4800 GB/s | Data Center GPU | |
| AMD Instinct MI300X | 192 GB | 5300 GB/s | Data Center GPU | |
| NVIDIA B200 | 192 GB | 8000 GB/s | Data Center GPU | |
| AMD Instinct MI325X | 256 GB | 6000 GB/s | Data Center GPU | |
| AMD Instinct MI355X | 288 GB | 8000 GB/s | Data Center GPU | |
| NVIDIA B300 (Blackwell Ultra) | 288 GB | 8000 GB/s | Data Center GPU |
Minimum GPUs that fit Nemotron 3 Super 120B A12B at Q4_K_M
These GPUs hold the model but leave little headroom — keep contexts short.
| GPU | VRAM | Bandwidth | Type | |
|---|---|---|---|---|
| NVIDIA RTX PRO 6000 Blackwell | 96 GB | 1792 GB/s | Pro GPU | Check price |
Needs 2+ GPUs to run Nemotron 3 Super 120B A12B
One of these cards is too small on its own, but a pair (tensor or pipeline parallel, ~90% efficiency) covers the 82.0 GB requirement. See our multi-GPU guide for setup.
| GPU | VRAM | Bandwidth | Type | |
|---|---|---|---|---|
| AMD Radeon Pro W7900 | 48 GB ×2 | 864 GB/s | Pro GPU | Check price |
| NVIDIA RTX PRO 5000 Blackwell | 48 GB ×2 | 1344 GB/s | Pro GPU | |
| RTX 6000 Ada | 48 GB ×2 | 960 GB/s | Pro GPU | Check price |
| RTX A6000 | 48 GB ×2 | 768 GB/s | Pro GPU | Check price |
| H100 SXM | 80 GB ×2 | 3350 GB/s | Data Center GPU | |
| NVIDIA A100 80GB SXM | 80 GB ×2 | 2039 GB/s | Data Center GPU | |
| NVIDIA H100 PCIe 80GB | 80 GB ×2 | 2039 GB/s | Data Center GPU |
Can a Mac run Nemotron 3 Super 120B A12B?
Yes — these Apple Silicon machines fit Nemotron 3 Super 120B A12B at Q4_K_M, since macOS lets the GPU use about 75% of unified memory. Generation speed is bound by memory bandwidth, so the GB/s column matters as much as capacity.
| Apple Silicon | Unified memory | Usable by GPU (~75%) | Bandwidth |
|---|---|---|---|
| Apple M3 Max | 128 GB | 96 GB | 400 GB/s |
| M4 Max (MacBook Pro) | 128 GB | 96 GB | 546 GB/s |
| M5 Max (Mac Studio) | 128 GB | 96 GB | — |
| M5 Ultra (Mac Studio) | 512 GB | 384 GB | 1200 GB/s |
Can Nemotron 3 Super 120B A12B run on mini PCs, Jetson, or NPU devices?
These edge and NPU devices from our database have enough memory for Nemotron 3 Super 120B A12B at Q4_K_M. Their memory bandwidth is far below discrete GPUs, so expect a fraction of desktop generation speed.
| Device | Memory | Bandwidth | Type |
|---|---|---|---|
| AMD Ryzen AI 9 HX 370 (Strix Point) | 96 GB | 120 GB/s | NPU Chip |
Which pre-built systems can run Nemotron 3 Super 120B A12B?
These mini PCs and workstations from our database fit Nemotron 3 Super 120B A12B at Q4_K_M. Usable-memory figures are conservative: Windows shares about half of system RAM with the GPU by default (Linux can expose more), macOS lets Apple Silicon GPUs use about 75% of unified memory, and Linux unified-memory systems such as GB10 expose roughly 90%. Generation speed is bound by memory bandwidth, so compare the GB/s column before buying.
| System | Type | Memory | Usable for AI | Bandwidth | GPUs |
|---|---|---|---|---|---|
| ACEMAGIC F9A (Ryzen AI Max+ PRO 495) | Mini PC | 192 GB | 96 GB | — | — |
| BOXX APEXX 8R (1x RTX PRO 6000 Blackwell) | Workstation | 96 GB | 96 GB | 1792 GB/s | 1 |
| Chuwi UniBox AI495 Pro (Ryzen AI Max+ PRO 495) | Mini PC | 192 GB | 96 GB | 273 GB/s | — |
| GEEKOM A9 Mega AI Workstation | Workstation | 128 GB | 96 GB | — | 1 |
| GMKtec EVO-X5 Pro (Ryzen AI Max+ PRO 495) | Mini PC | 192 GB | 96 GB | — | — |
| NOVATECH RTX PRO 6000 AI Workstation | Workstation | 96 GB | 96 GB | — | 1 |
| System76 Thelio Major (1x RTX PRO 6000 Blackwell) | Workstation | 96 GB | 96 GB | 1792 GB/s | 1 |
| System76 Thelio Major (2x RTX 6000 Ada) | Workstation | 96 GB | 96 GB | 960 GB/s | 2 |
| Lenovo ThinkStation PGX | Workstation | 128 GB | 115.2 GB | 273 GB/s | 1 |
| NVIDIA DGX Spark | Workstation | 128 GB | 115.2 GB | 273 GB/s | 1 |
| BIZON G3000 G2 (4x RTX 5090) | Workstation | 128 GB | 128 GB | 1792 GB/s | 4 |
| Apple Mac Studio M2 Ultra (192GB) | Workstation | 192 GB | 144 GB | 800 GB/s | 1 |
| HP Z8 Fury G5 (4x RTX 6000 Ada) | Workstation | 192 GB | 192 GB | 960 GB/s | 4 |