Text model · Nemotron 3
NE Nemotron Cascade 2 30B-A3B: RAM and VRAM requirements
Nemotron Cascade 2 30B-A3B needs about 25.1 GB to run at Q4_K_M (the Q4_K_M GGUF file is ~23.03 GB to download; KV cache and overhead add the rest), or about 33.4 GB at Q8_0. The lightest hardware that runs it is Nvidia GeForce RTX 5090 (32GB).
Nemotron 3 family · 30B params (Mixture-of-Experts: activates only 3B of 30B params per token, so generation is faster than the total size suggests) · released Mar 2026.
Shopping for hardware? See what runs Nemotron Cascade 2 30B-A3B →
Q4_K_M and Q8_0 are GGUF download (file) sizes. Memory @ Q4 includes the KV cache and overhead, so it runs larger than the file on disk.
Will it run on your device?
Nemotron Cascade 2 30B-A3B runs on 9 of 40 tracked devices at Q4_K_M.
Memory breakdown
How context length changes it
Longer context grows the KV cache, which for Nemotron Cascade 2 30B-A3B is sized by its 3B active params, not the full 30B. It needs ~25.1 GB at 4k and ~65.9 GB at 128k.
Quantization sizes
| Quantization | Size on disk |
|---|---|
| Q2_K | 12.6 GB est |
| Q3_K_M | 14.7 GB est |
| Q4_K_M (default) | 23.03 GB |
| Q5_K_M | 21.4 GB est |
| Q6_K | 24.6 GB est |
| Q8_0 | 31.28 GB |
| FP16 | 60 GB est |
Lower quant = smaller and faster, slightly lower quality. Q4_K_M is the common default.
Run it
ollama run nemotron-cascade-2:30b llama-cli -hf bartowski/nvidia_Nemotron-Cascade-2-30B-A3B-GGUF:Q4_K_M lms get bartowski/nvidia_Nemotron-Cascade-2-30B-A3B-GGUF Which devices can run Nemotron Cascade 2 30B-A3B?
Apple Silicon Macs
- Apple M1 (8GB) No
- Apple M2 (16GB) No
- Apple M4 (16GB) No
- Apple M5 (16GB) No
- Apple M3 Pro (18GB) No
- Apple M4 (24GB) No
- Apple M4 Pro (24GB) No
- Apple M5 (32GB) No
- Apple M4 Pro (48GB) Yes
- Apple M5 Pro (48GB) Yes
- Apple M4 Max (64GB) Yes
- Apple M4 Max (128GB) Yes
- Apple M5 Max (128GB) Yes
- Apple M3 Ultra (256GB) Yes
RAM-only laptops
iPhone & iPad
Android
NVIDIA GPUs
Same job, different size
Pick by what fits your memory: step down to free up VRAM, or step up if you have headroom.
Similar models
Head-to-head
FAQ
How much VRAM or RAM does Nemotron Cascade 2 30B-A3B need?
At Q4_K_M, Nemotron Cascade 2 30B-A3B needs about 25.1 GB (weights ~23.03 GB + KV cache + overhead) at a 4k context. At Q8_0 budget ~33.4 GB.
What is the Q4_K_M GGUF file size of Nemotron Cascade 2 30B-A3B?
The Q4_K_M GGUF file is about 23.03 GB to download, and the Q8_0 GGUF is about 31.28 GB. That is the weights file on disk; to run it you also need room for the KV cache and overhead, so budget ~25.1 GB of memory at Q4_K_M.
Can Nemotron Cascade 2 30B-A3B run on a laptop?
Nemotron Cascade 2 30B-A3B is large; you need a high-memory Mac or multi-GPU setup at Q4_K_M.
Is Nemotron Cascade 2 30B-A3B cheaper to run because it is a MoE model?
It is faster, not lighter. Nemotron Cascade 2 30B-A3B activates only 3B of 30B params per token (so it runs quickly), but all experts must stay in memory, so it still needs memory for the full 30B.
Can I use Nemotron Cascade 2 30B-A3B commercially?
Conditionally. NVIDIA Open Model License; check the terms for commercial use.
Understand the numbers
Short guides to the ideas behind Nemotron Cascade 2 30B-A3B's memory and quant figures.
Post-trained (SFT+RL) from the Nemotron-3-Nano-30B-A3B base for reasoning and agentic tasks; NVIDIA reports gold-medal IMO/IOI results. Same 30B MoE architecture as Nemotron-3-Nano-30B-A3B (its own card rounds active params to 3B vs the base's 3.5B) but a distinct checkpoint, not a duplicate listing. Up to 1M context. Sizes from bartowski's GGUF repo. NVIDIA Open Model License.
Sources
Last validated 2026-08-03. Memory figures are estimates. See methodology.