NVIDIA Nemotron 3.5 Super VL
An open-source multimodal vision-language model from NVIDIA built on a Mixture-of-Experts architecture. It integrates visual understanding, reasoning chains and tool calling into a single set of weights, and supports post-training through the NeMo toolchain.
Core Facts
Timeline (last 90 days)
NVIDIA Nemotron 3.5 Super VL can be called directly through LangChain's ChatNVIDIA interface.
According to the author of the original Reddit post, NVIDIA Nemotron 3.5 Super VL achieved an average pass rate of 87% in a self-built Deep Agents behavior test suite.
On the Harbor Unified-lite benchmark, NVIDIA Nemotron 3.5 Super VL took 55% less total task time than DeepSeek V4.1 Flash, with similar task success rates.
NVIDIA Nemotron 3.5 Super VL is a 120B-parameter MoE model with 12B active parameters, supporting up to a 1 million token context, aimed at document understanding, computer use and agent scenarios.
The official statement says that at a 100K input length, Nemotron 3.5 Super VL generates about 5 times faster than Inkling Small, with similar intelligence levels.
All Facts (5)
NVIDIA Nemotron 3.5 Super VL is a 120B-parameter MoE model with 12B active parameters, supporting up to a 1 million token context, aimed at document understanding, computer use and agent scenarios.
90%UnverifiedNVIDIA Nemotron 3.5 Super VL can be called directly through LangChain's ChatNVIDIA interface.
50%UnverifiedAccording to the author of the original Reddit post, NVIDIA Nemotron 3.5 Super VL achieved an average pass rate of 87% in a self-built Deep Agents behavior test suite.
50%UnverifiedOn the Harbor Unified-lite benchmark, NVIDIA Nemotron 3.5 Super VL took 55% less total task time than DeepSeek V4.1 Flash, with similar task success rates.
50%UnverifiedThe official statement says that at a 100K input length, Nemotron 3.5 Super VL generates about 5 times faster than Inkling Small, with similar intelligence levels.
50%