Nemotron 3.5 Super VL
Nemotron 3.5 Super VL is a member of NVIDIA's Nemotron 3 family of open models with open weights, training data, and recipes. It combines visual understanding, reasoning, and tool use in a single model and is described as delivering highest in-class efficiency and accuracy for specialized domains. It can be deployed from local infrastructure to the cloud and is accessible via OpenRouter, NVIDIA NIM API, and Hugging Face.
Key facts
What is Nemotron 3.5 Super VL?
One open multimodal model that combines visual understanding, reasoning, and tool use with high in-class efficiency and accuracy for specialized domains.
Who is Nemotron 3.5 Super VL best for?
AI developers and enterprises building specialized multimodal AI agents
What are its main limitations?
- No published pricing information on the site; the pricing page returns a 'page not found' message
- Deployment targets NVIDIA GPUs
- Performance claims such as 'highest in-class efficiency' are vendor-stated
Limitations are based on product materials or editorial synthesis; confirm on the official site.
When was this information verified?
October 16, 2026
Sources
- Official homepageofficial homepage · Oct 16, 2026
Key features
- ✓Combines visual understanding, reasoning, and tool use in one model
- ✓Highest in-class efficiency and highest accuracy for specialized domains (per NVIDIA)
- ✓Part of the Nemotron 3 family built on hybrid Mamba-Transformer MoE with 1M-token context
- ✓Deployable from local infrastructure to the cloud using open frameworks such as vLLM, SGLang, Ollama, and llama.cpp on NVIDIA GPUs
- ✓Available as NVIDIA NIM microservice endpoints on GPU-accelerated systems
- ✓Open weights, training data, and recipes published on Hugging Face with a freely available technical report
- ✓Released alongside a synthetic Indic pretraining corpus of about 2.83T tokens in 22 languages co-created with IIT Madras
Use cases
- →Building specialized agentic AI applications that need multimodal reasoning and tool calling
- →Visual understanding tasks in specialized domains
- →Deploying agents on local infrastructure for privacy and security
- →Running high-throughput agentic workloads where inference cost matters
- →Evaluating and reproducing models using openly published weights, data, and technical reports
Pros
- +Open weights, training data, and recipes are published for evaluation before production deployment
- +Deployable across edge, cloud, and data center on NVIDIA GPUs with popular open frameworks
- +Combines visual understanding, reasoning, and tool use in a single model
- +Available through multiple access paths: OpenRouter demo, NVIDIA NIM API, and Hugging Face download
- +NVIDIA states the Nemotron models provide high throughput, lowering inference cost
Cons
- −No published pricing information on the site; the pricing page returns a 'page not found' message
- −Deployment targets NVIDIA GPUs
- −Performance claims such as 'highest in-class efficiency' are vendor-stated
Positioning
- Core value: One open multimodal model that combines visual understanding, reasoning, and tool use with high in-class efficiency and accuracy for specialized domains.
- Ideal for: AI developers and enterprises building specialized multimodal AI agents
- Product type: Open-weight model downloadable on Hugging Face; NVIDIA NIM API microservice; demo on OpenRouter
Frequently asked questions
What is Nemotron 3.5 Super VL?
It is a model in NVIDIA's Nemotron 3 family that combines visual understanding, reasoning, and tool use in one model, with what NVIDIA describes as highest in-class efficiency and highest accuracy for specialized domains.
Is Nemotron 3.5 Super VL open?
NVIDIA states that Nemotron models are transparent: the training data and weights are open and available on Hugging Face, and technical reports describing how to recreate the models are freely available.
How can I access Nemotron 3.5 Super VL?
According to the Nemotron page, you can demo the model on OpenRouter, experience it as an NVIDIA NIM API, download it on Hugging Face, and read the technical report.
Where can Nemotron 3.5 Super VL be deployed?
It can be deployed anywhere from local infrastructure to the cloud using open frameworks such as vLLM, SGLang, Ollama, and llama.cpp on NVIDIA GPUs, with NVIDIA NIM microservice endpoints also available.
How much does Nemotron 3.5 Super VL cost?
No pricing is published on the site; the pricing page linked from the site returns a 'page not found' message.
What data was released with Nemotron 3.5 Super VL?
NVIDIA states that a synthetic Indic pretraining corpus of about 2.83T tokens in 22 languages, co-created with IIT Madras, was released with Nemotron 3.5 Super VL.
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