NVIDIA Releases Open-Weight Nemotron 3.5 Model Series
11/10/2026 — 11/12, 11:21·2 sources (all)·2 reports (all)
Key takeaways
- NVIDIA has expanded the Nemotron family by releasing multiple open-weight models, including the 120B multimodal Nemotron 3.5 Super VL, the N…
Background & analysis
Earliest verified development: On November 10, 2026, AWS announced via the AWS Machine Learning Blog that NVIDIA Nemotron 3.5 Super VL, a 120B-parameter multimodal vision-language model, is now available in Amazon SageMaker JumpStart. Users can deploy either the NVFP4 or the BF16 variant in a few steps, then run text, image, and video inference for document intelligence, computer-use agents, and multimodal agentic workloads. The available reports do not cover an earlier announcement or the model's underlying release timeline, nor do they describe subsequent developments, so the timeline currently ends here. No additional reporting is available at this point.
AI-generated from 1 reports · updated 4 days ago
Latest turnNVIDIA expanded its Nemotron family with several open-weight models: the 120B multimodal Nemotron 3.5 Super VL, Nemotron 3.5 Bolt in 74B and 4B variants, and the 30B mixture-of-experts speech model Nemotron 3.5 Transcribe covering 40 languages. All are published on Hugging Face for agentic, enterprise, edge, and multilingual audio workloads.
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Reports on this story headlines open the original
NVIDIA expanded its Nemotron family with several open-weight models: the 120B multimodal Nemotron 3.5 Super VL, Nemotron 3.5 Bolt in 74B and 4B variants, and the 30B mixture-of-experts speech model Nemotron 3.5 Transcribe covering 40 languages. All are published on Hugging Face for agentic, enterprise, edge, and multilingual audio workloads.
DEV Community · AIAI score 65
AWS has added NVIDIA Nemotron 3.5 Super VL, a 120B-parameter multimodal vision-language model, to Amazon SageMaker JumpStart. Teams can deploy either the NVFP4 or BF16 variant and run text, image and video inference for document intelligence, computer-use agents and multimodal agentic workloads.
AWS Machine Learning BlogFirst-partyAI score 47
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