Nex N2 Mini — Hardware Requirements & GPU Compatibility
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Nex N2 Mini is a 35.1B-parameter open language model from nex-agi. It supports a context window of up to 262,144 tokens. At BF16 it needs about 70.60 GB of VRAM — see which GPUs and Macs can run it below.
190 downloads
22 likesSpecifications
- Publisher
- nex-agi
- Parameters
- 35.1B
- Architecture
- Qwen3_5MoeForConditionalGeneration
- Context Length
- 262,144 tokens
- Vocabulary Size
- 248,320
- Release Date
- 2026-06-04
- License
- Apache 2.0
Get Started
HuggingFace
How Much VRAM Does Nex N2 Mini Need?
Select a quantization to see compatible GPUs below.
| Quantization | Bits | VRAM | + Context | File Size | Quality |
|---|---|---|---|---|---|
| BF16 | 16.00 | 70.6 GB | 81.3 GB | 70.21 GB | Brain floating point 16 — preferred for training |
Which GPUs Can Run Nex N2 Mini?
BF16 · 70.6 GBNex N2 Mini (BF16) requires 70.6 GB of VRAM to load the model weights. For comfortable inference with headroom for KV cache and system overhead, 92+ GB is recommended. Using the full 262K context window can add up to 10.7 GB, bringing total usage to 81.3 GB. No single GPU has enough memory — multi-GPU or cluster setups are needed.
Which Devices Can Run Nex N2 Mini?
BF16 · 70.6 GB5 devices with unified memory can run Nex N2 Mini, including NVIDIA DGX H100, NVIDIA DGX A100 640GB.
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Frequently Asked Questions
- How much VRAM does Nex N2 Mini need?
Nex N2 Mini requires 70.6 GB of VRAM at BF16. Full 262K context adds up to 10.7 GB (81.3 GB total).
VRAM = Weights + KV Cache + Overhead
Weights = 35.1B × 16 bits ÷ 8 = 70.2 GB
KV Cache + Overhead ≈ 0.4 GB (at 2K context + ~0.3 GB framework)
KV Cache + Overhead ≈ 11 GB (at full 262K context)
VRAM usage by quantization
BF1670.6 GBBF16 + full context81.3 GB- Can NVIDIA GeForce RTX 5090 run Nex N2 Mini?
No — Nex N2 Mini requires at least 70.6 GB at BF16, which exceeds the NVIDIA GeForce RTX 5090's 32 GB of VRAM.
- Can I run Nex N2 Mini on a Mac?
Nex N2 Mini requires at least 70.6 GB at BF16, which exceeds the unified memory of most consumer Macs. You would need a Mac Studio or Mac Pro with a high-memory configuration.
- Can I run Nex N2 Mini locally?
Yes — Nex N2 Mini can run locally on consumer hardware. At BF16 quantization it needs 70.6 GB of VRAM. Popular tools include Ollama, LM Studio, and llama.cpp.
- How fast is Nex N2 Mini?
At BF16, Nex N2 Mini can reach ~41 tok/s on AMD Instinct MI300X. Speed depends mainly on GPU memory bandwidth. Real-world results typically within ±20%.
tok/s = (bandwidth GB/s ÷ model GB) × efficiency
Example: AMD Instinct MI300X → 5300 ÷ 70.6 × 0.55 = ~41 tok/s
Estimated speed at BF16 (70.6 GB)
~41 tok/s~31 tok/s~26 tok/sReal-world results typically within ±20%. Speed depends on batch size, quantization kernel, and software stack.
- What's the download size of Nex N2 Mini?
At BF16, the download is about 70.21 GB.
- Which GPUs can run Nex N2 Mini?
No single consumer GPU has enough VRAM to run Nex N2 Mini at BF16 (70.6 GB). Multi-GPU or professional hardware is required.
- Which devices can run Nex N2 Mini?
5 devices with unified memory can run Nex N2 Mini at BF16 (70.6 GB), including Mac Pro M2 Ultra (192 GB), Mac Studio M2 Ultra (192 GB), Mac Studio M4 Max (128 GB), NVIDIA DGX A100 640GB. Apple Silicon Macs use unified memory shared between CPU and GPU, making them well-suited for local LLM inference.