Nex-AGI1.6T (49B active)Q4_K_M 下约 967 GB 显存

Nex-N2.5 Max — 显存、速度与本地部署

作者： Jakub Rusinowski · 最后更新：

A 1.6-trillion-parameter text-only MoE on a DeepSeek-V4-Pro base — 967 GB at Q4_K_M, which Nex serves on 16x H200 across two nodes. The best BrowseComp score in Nex's table at 92.6, plus 86.1 on Terminal-Bench 2.1 and 65.7 on SWE-Bench Pro. Listed here as a reference point for what frontier open weights now cost to hold, not as a local recommendation. DeepSeek lineage means MLA compressed KV cache, so its context is far cheaper than the parameter count suggests.

Nex-N2.5 Max 在 Q4_K_M 下约需 967 GB 显存——量化权重加框架开销，不含 KV 缓存。在 Apple Silicon 上，这部分来自统一内存。

逻辑95
创意90
编程95

按量化级别的显存与速度

计算基准：NVIDIA RTX 4090 (24 GB)。仅含权重与开销：该模型架构未公开，因此未计入 KV 缓存。

量化显存速度（估算）适配
Q2_K
2.63 bpw
526.8 GB—放不下
Q3_K_M
3.41 bpw
682.8 GB—放不下
Q4_K_M
4.83 bpw
966.8 GB—放不下
Q5_K_M
5.67 bpw
1134.8 GB—放不下
Q6_K
6.56 bpw
1312.8 GB—放不下
Q8_0
8.50 bpw
1700.8 GB—放不下
F16
16.00 bpw
3200.8 GB—放不下

黑色标记 = NVIDIA RTX 4090 (24 GB) 上的可用显存。 估算来自内存带宽屋顶线模型，详见 方法说明页. Nex-N2.5 Max 显存计算器 →

运行 Nex-N2.5 Max

Nex-N2.5 Max is not practical on a single consumer GPU: it needs about 966.8 GB at Q4_K_M, more than any single device in our catalogue holds with headroom. How multi-GPU inference works, or rent a multi-GPU server by the hour:

立即云端部署 RunPod

或在 Vast.ai 比较

作为亚马逊联盟成员，我们从符合条件的购买中获得收入。云 GPU 链接为推荐链接——我们可能获得佣金，您无需额外付费。

如何运行 Nex-N2.5 Max

安装 Ollama，然后运行：

ollama run nex-n2-5
Hugging Face 上的权重： nex-agi/Nex-N2.5-Max ↗

规格

Preview — The model is released, but these specs are thin or rest on a single source. Individual fields may be wrong.

Preview — The model is released, but these specs are thin or rest on a single source. Individual fields may be wrong.

参数量
1.6 Trillion (49B active)
上下文窗口
262,144
架构
Mixture-of-Experts (DeepSeek-V4-Pro base, MLA attention, text-only)
提供商
Nex-AGI
许可证
Open-weight (terms unpublished)
Practical deployment
Private cloud / datacenter cluster
规格量化
Q4_K_M
系统内存
1024 GB
记录更新于
2026-09-08
许可证Custom Open-Weight允许商业使用

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

质量与使用场景

评分由模型作者或独立评测方发布——衡量质量而非吞吐量，并非我们实测。

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我的 GPU 能运行 Nex-N2.5 Max 吗？

Nex-N2.5 的其他尺寸

Nex-N2.5 Max — 常见问题

How much VRAM does Nex-N2.5 Max need?

About 967 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-N2.5 Max run on an RTX 4090 (24 GB)?

No. Nex-N2.5 Max needs about 967 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-N2.5 Max locally?

Install Ollama and run `ollama run nex-n2-5`. That pulls the weights and starts a local OpenAI-compatible endpoint; after the download nothing leaves the machine.

What other sizes does Nex-N2.5 come in?

Nex-N2.5 mini (22 GB), Nex-N2.5 Pro (240 GB), Nex-N2.5 Max (967 GB). Every size shares the family's training and licence; the larger ones score higher and need proportionally more memory.