Nex-N2 Pro — VRAM, Speed & Local Setup

Autor: Jakub Rusinowski · Ostatnia aktualizacja: 8 września 2026

Model library → Nex-N2 → Nex-N2 Pro

397B total, 17B active, Apache 2.0 — 240 GB at Q4_K_M, so datacenter or nothing. Terminal-Bench 2.1 at 75.3, SWE-bench Verified at 80.8, GPQA Diamond at 90.7, GDPval at 1585. Accepts image input as well as text. The permissive licence is the notable part: a 397B model you may deploy commercially without asking anyone.

Nex-N2 Pro needs about 240 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.

Specifications

Parameters397 Billion (17B active)
Context window262,144
ArchitectureMixture-of-Experts (Qwen3.5-397B-A17B post-train, multimodal)
ProviderNex-AGI
LicenceApache 2.0
Specified atQ4_K_M
System RAM256 GB
Record updated2026-09-08

Licence

Apache-2.0 — commercial use permitted. Commercial use permitted. No usage restrictions beyond attribution.

VRAM and Speed by Quantization

Modelled on a reference NVIDIA RTX 4090 (24 GB), with no KV cache (this record has no published architecture). Speed figures are ESTIMATES from the memory-bandwidth roofline described on the methodology page, not benchmarks we ran — rows marked measured come from published or reader-submitted runs. VRAM here includes the KV cache, so it reads higher than the headline figure above, which does not.

QuantWeightsVRAM neededEst. speedFit on 24 GB
Q2_K130.5 GB131.3 GB—Won't fit
Q3_K_M169.2 GB170.0 GB—Won't fit
Q4_K_M239.7 GB240.5 GB—Won't fit
Q5_K_M281.4 GB282.2 GB—Won't fit
Q6_K325.5 GB326.3 GB—Won't fit
Q8_0421.8 GB422.6 GB—Won't fit
F16794.0 GB794.8 GB—Won't fit

Want the memory numbers alone, at every quantization level and your own context length? Use the Nex-N2 Pro VRAM calculator.

Buy This HardwareApple Mac Studio M3 Ultra — 512 GB VRAM · 60 W board powerDeploy in the Cloud NowRunPod

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Recommended GPU

The cheapest catalogued GPU that runs Nex-N2 Pro is the Apple M3 Ultra (512 GB).

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Apple Mac Studio M3 Ultra
512 GB VRAM · 60 W board power
Ceny w 2026 są niestabilne — sprawdź aktualną ofertę.
Sprawdź cenę na Amazon

How to Run Nex-N2 Pro

Install Ollama, then run:

ollama run nex-n2

Weights on Hugging Face: nex-agi/Nex-N2-Pro.

Best for: agentic tasks, software engineering, enterprise, research.

Can I Run Nex-N2 Pro on My GPU?

Other Nex-N2 Sizes

Nex-N2 Pro — Frequently Asked Questions

How much VRAM does Nex-N2 Pro need?
About 240 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 Nex-N2 Pro run on an RTX 4090 (24 GB)?
No. Nex-N2 Pro needs about 240 GB at Q4_K_M, more than a single RTX 4090's 24 GB. It needs a larger card, several GPUs, or Apple Silicon with enough unified memory — or it runs with part of the weights offloaded to system RAM, which is much slower.
How do I run Nex-N2 Pro locally?
Install Ollama and run `ollama run nex-n2`. That pulls the weights and starts a local OpenAI-compatible endpoint; after the download nothing leaves the machine.
What other sizes does Nex-N2 come in?
Nex-N2 mini (22 GB), Nex-N2 Pro (240 GB). Every size shares the family's training and licence; the larger ones score higher and need proportionally more memory.

← All Nex-N2 models | VRAM calculator | Check your own hardware