NVIDIA31.6B (3.5B active)~20 GB VRAM at Q4_K_M

Nemotron-Cascade 2 30B-A3B — VRAM, speed & local setup

Written by Jakub Rusinowski · Last updated

31.6B parameters resident — about 19.9 GB at Q4_K_M, so a 24 GB card holds it — with 3.5B active per token, which is why it decodes far faster than its size suggests. 52 layers: 23 Mamba-2 state-space, 23 MoE, and 6 GQA attention. Each MoE layer carries 128 routed experts plus one shared, six routed activated per token. Gold-medal level at IMO 2025, IOI and the ICPC World Finals, reached through post-training rather than scale — and NVIDIA published that recipe. 1M-token context, NVIDIA Open Model License.

Nemotron-Cascade 2 30B-A3B needs about 20 GB of VRAM at Q4_K_M — quantized weights plus framework overhead, before any KV cache. On Apple Silicon that figure comes out of unified memory.

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VRAM and speed by quantization

Quoted against NVIDIA RTX 4090 (24 GB). Weights plus overhead only: this model's architecture is unpublished, so no KV cache is added.

QuantVRAMSpeed (est.)Fit
Q2_K
2.63 bpw
11.2 GB~201 tok/sFits
Q3_K_M
3.41 bpw
14.3 GB~185 tok/sFits
Q4_K_M
4.83 bpw
19.9 GB~160 tok/sFits
Q5_K_M
5.67 bpw
23.2 GB~149 tok/sTight
Q6_K
6.56 bpw
26.7 GB~21 tok/sOffload
Q8_0
8.50 bpw
34.4 GB~18 tok/sOffload
F16
16.00 bpw
64 GB—Too big

Black marker = usable memory on the NVIDIA RTX 4090 (24 GB). Estimates from the memory-bandwidth roofline on the methodology page. Nemotron-Cascade 2 30B-A3B VRAM calculator →

Get Nemotron-Cascade 2 30B-A3B running

The cheapest catalogued GPU that runs Nemotron-Cascade 2 30B-A3B is the AMD Radeon RX 7900 XTX (24 GB).

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AMD Radeon RX 7900 XTX 24GB
24 GB VRAM · 355 W board power
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How to run Nemotron-Cascade 2 30B-A3B

Install Ollama, then run:

ollama run nemotron-cascade-2:30b
Weights on Hugging Face: nvidia/Nemotron-Cascade-2-30B-A3B ↗

Specifications

Verified — Checked against the primary source — the model card or the vendor spec page — and corroborated by a second independent source.

Parameters
31.6 Billion (3.5B active)
Context window
1,048,576
Architecture
Hybrid Mamba-2 + MoE + GQA attention
Provider
NVIDIA
Licence
NVIDIA Open Model License
Practical deployment
Single consumer GPU
Specified at
Q4_K_M
System RAM
32 GB
Record updated
2026-09-11
LicenceNVIDIA Open Model LicenseCommercial use permitted

Weights are downloadable and commercial use is permitted, subject to the licence’s acceptable-use terms.

Quality and use cases

Scores as published by the model’s authors or an independent evaluator — quality, not throughput, and not measured by us.

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Can I run Nemotron-Cascade 2 30B-A3B on my GPU?

Nemotron-Cascade 2 30B-A3B — frequently asked questions

How much VRAM does Nemotron-Cascade 2 30B-A3B need?

About 20 GB at Q4_K_M — quantized weights plus framework overhead, before any KV cache. The cache grows with context length and is added on top; the table above folds it in. Apple Silicon counts unified memory toward the same figure.

Does Nemotron-Cascade 2 30B-A3B run on an RTX 4090 (24 GB)?

Yes. Nemotron-Cascade 2 30B-A3B needs about 20 GB at Q4_K_M, inside a 24 GB card, at an estimated 160 tokens/sec.

How do I run Nemotron-Cascade 2 30B-A3B locally?

Install Ollama and run `ollama run nemotron-cascade-2:30b`. That pulls the weights and starts a local OpenAI-compatible endpoint; after the download nothing leaves the machine.

What other sizes does Nemotron Cascade 2 come in?

Nemotron-Cascade 2 30B-A3B (20 GB), Nemotron Cascade 2 70B (43 GB). Every size shares the family's training and licence; the larger ones score higher and need proportionally more memory.