Model ID
nex-agi/Nex-N2.5-Pro
Capabilities
Nex N2.5 Pro
Nex N2.5 Pro is a multimodal agentic model designed for long-horizon tasks, computer use, web browsing, scientific research, knowledge work, and visually grounded workflows. The 397B model uses a 60-layer architecture with 4,096 hidden size, 32 attention heads, and 2 KV heads, combining linear attention with full attention every fourth layer. The architecture employs 512 routed experts, 10 activated per token, and a shared expert, with 1,024-dimensional MoE layers and SiLU activation. Supporting a native 262,144-token context, it incorporates a 27-layer vision encoder for image and video understanding.
About this model
Nex N2.5 Pro is a multimodal agentic model designed for long-horizon tasks, computer use, web browsing, scientific research, knowledge work, and visually grounded workflows. The 397B model uses a 60-layer architecture with 4,096 hidden size, 32 attention heads, and 2 KV heads, combining linear attention with full attention every fourth layer. The architecture employs 512 routed experts, 10 activated per token, and a shared expert, with 1,024-dimensional MoE layers and SiLU activation. Supporting a native 262,144-token context, it incorporates a 27-layer vision encoder for image and video understanding.
Model specifications and capabilities are published by the model author and reproduced here from HF Model Card (nex-agi/Nex-N2.5-Pro). Released under Apache 2.0.
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Hardware
B200
1,440 GB
Engine
vLLM
SGLang
Deployment code
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Performance under load
Tokens/s (total)
Benchmarks measured by Vultr on B200 · SGLang. Throughput and latency vary with concurrency, input length and engine configuration, so treat these as a comparison baseline, not a service guarantee.
NVIDIA HGX B200
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