Nex-AGI's second-generation agentic family, released September 8, 2026 in three sizes. mini and Pro continue the multimodal Nex-N2 line with focused gains in computer use, web browsing, and visually grounded agent work: their configs are Qwen3.5 MoE shapes (mini 256 experts, 8 active; Pro 60 layers, 512 experts, 10 active; 262K context), so they are post-trained on Qwen3.5 bases. Max is new: a text-only model on the DeepSeek-V4 architecture (61 layers, 384 routed experts, 6 active, 1M context) that Nex-AGI describes as its first "systematic post-training at trillion-parameter scale," which places it on DeepSeek-V4-Pro. All three ship under Apache 2.0 on HuggingFace and ModelScope, with hosted access on OpenRouter.

Self-reported (NexAU harness for coding, NexCUA for computer use): Max reaches 86.1 on Terminal-Bench 2.1, 65.7 on SWE-Bench Pro, 65.6 on DeepSWE v1.1, 50.2 on AutomationBench (level with Claude Opus 5's 50.3), 74.7 on Toolathlon Verified, 1713 GDPval-AA Elo, and 92.6 on BrowseComp, the top figure in its comparison table; Pro scores 82.2 on OSWorld-Verified, 87.4 on OSWorld-G, and 89.7 on BrowseComp. The NexCUA computer-use harness is promised as open source. Parameter counts are not stated on the cards; the weights inherit the bases' sizes. Not yet scored by Artificial Analysis at filing.

Model Details

Architecture MOE
Context window 262,144
License Apache 2.0
Base model qwen3.5

Variants

Name Parameters Notes
Nex-N2.5-mini — Qwen3.5 MoE shape (256 experts, 8 active), 262K context; multimodal; OpenRouter free tier
Nex-N2.5-Pro 397B Qwen3.5 MoE shape (60 layers, 512 experts, 10 active), 262K context; multimodal; the file's anchor. Weights published 17 Sep 2026 (397B, Apache 2.0, BF16 and FP8).
Nex-N2.5-Max — DeepSeek-V4 architecture (61 layers, 384 experts, 6 active), 1M context; text-only; post-trained from DeepSeek-V4-Pro
agenticmultimodalmoeopen-weight

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