NVIDIA Releases Nemotron 3.5 Super VL Agent Model

The model is capable of reasoning, calling tools, and writing code within a single architecture. For developers, this open checkpoint replaces the need for separate text and vision models. NVIDIA also introduced two edge models: Nemotron 3.5 Bolt 74B-A9B and Bolt E4B.

Nemotron 3.5 Super VL features a context window of up to 1 million tokens and supports various hardware configurations, including DGX Spark, H200, H100, and GB200 with an NVFP4 checkpoint. A BF16 checkpoint is also available.

NVIDIA claims the model offers up to 5x higher single-GPU throughput compared to open peers, with strong performance in reasoning, agentic coding, and document vision. Its performance on the GPQA-Diamond benchmark is 89.90 with the NVFP4 checkpoint.

The model's weights are distributed under the OpenMDW-1.1 license. NVIDIA has also provided open datasets, training recipes, and reinforcement learning environments in NeMo Gym. The model card specifies text, image, and video inputs, with text output, and video input is limited to MP4 clips up to two minutes.

The architecture interleaves Mamba-2, mixture-of-experts, and attention layers, with each MoE layer containing 512 routed experts. A C-RADIO vision encoder and a connector process visual inputs into the language backbone. Speed enhancements include multi-token prediction, LiLiCorr for faster token generation on DGX Spark, NVFP4 with quantization-aware distillation for efficient processing, and context reuse for prefix caching.