Nemotron 3.5 Super VL: Nvidia’s Free Vision Model for AI Agents
Nemotron 3.5 Super VL is Nvidia’s new free, open AI model that can read your screenshots, PDFs and charts — and then actually do the work from there. On Hermes Bench, a test built for Hermes Agent, it beat Nvidia’s own bigger model, Nemotron 3 Ultra, and you can use it free in OpenCode and Hermes today. I show it in the video below. Here’s what it is, the numbers that matter, and where it fits in your agent stack.
Key takeaways
120B parameters, 12B active — big-model brains, small-model speed.
Reads text, images, documents and short videos in one model.
63.44% on Hermes Bench vs 56.33% for Nemotron 3 Ultra (Nvidia-reported).
Free in OpenCode and via OpenRouter’s free variant; open weights on Hugging Face.
What Nemotron 3.5 Super VL is
Nvidia released it on 15 October 2026 as part of its Nemotron family of open models. “VL” means vision-language: it understands images and documents as well as text. Nvidia says it’s comparable with its largest reasoning model at roughly a fifth of the parameter count.
Nemotron 3.5 Super VL at a glance
Made by
Nvidia
Released
15 October 2026
Size
120B total parameters, 12B active per token (mixture of experts)
Architecture
Hybrid Mamba-2 + Transformer MoE with a C-RADIO vision encoder and multi-token prediction
Context
Up to 1M tokens
Inputs
Text, images, document pages and MP4 video up to 2 minutes (text output)
Reasoning
Off, medium or on; supports tool calling
Licence
OpenMDW-1.1 — open weights, commercial use allowed
Most agents run on text-only models. Hand a text model a screenshot, a chart or a scanned receipt and it’s stuck. A lot of real agent work starts with something visual: a client report, a dashboard screenshot, a PDF. Nemotron 3.5 Super VL puts text and visual understanding in one model, so your agent doesn’t have to pass context between a separate text model and vision model.
On CharXiv — a test of whether an AI really understands charts — it scores 80.82, and it’s strong at reading text inside images (OCR), like the text on a receipt photo.
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120 billion parameters in total, but only 12 billion switch on for each token. Picture a team of 120 where only the 12 best-suited people stand up for each job — that’s why it’s fast.
Up to 5× faster — Nvidia says it’s five times faster than the next-best open agentic model in its class, helped by multi-token prediction, where the model drafts several words ahead and checks them in one go.
63.44% on Hermes Bench, versus 56.33% for Nemotron 3 Ultra.
Free variant, or $0.15/M input and $0.50/M output tokens
Hermes Agent
Choose it via OpenRouter (or your local server) in the model picker
Free or pay-as-you-go
Ollama
ollama run nemotron-3.5-super (80–90GB)
Free, needs big hardware
LM Studio
Download the GGUF (Q4_K_M, about 70GB)
Free, needs 70GB+ RAM
Hugging Face
BF16 and NVFP4 checkpoints for vLLM or SGLang
Free weights, server GPUs
Is Nemotron 3.5 Super VL any good?
Let me be clear: this is not a frontier model. It’s not going to replace Claude Opus 5.5 for your hardest work. What it is: a free, open, fast model that can read screenshots, PDFs and charts and then act on them — which is exactly the job a lot of agent work starts with.
In my test I asked it in OpenCode to build an entertaining to-do list app, and it built a working one quickly. For jobs that start with a picture or a file — reading client reports, receipts, screenshots — it’s a great model to slot into your agent.
What Nvidia released with it
This is one of the most open releases from a big lab. Alongside the model weights, Nvidia published training recipes, reinforcement-learning environments and open datasets covering agentic tool use, long context and vision-language understanding. The model was trained on about 26 trillion tokens and post-trained with roughly 3.8 million samples, according to Nvidia. That means companies can fine-tune it on their own way of working, rather than just using it as-is.
Nvidia also launched two smaller models at the same time: Bolt 74B-A9B, which fits in 24GB of memory, and Bolt E4B, a 4GB model for fast conversational agents.
Where it fits in your agent stack
Think of it as your agent’s eyes. Route any job that starts with a picture or a file — a client report, a receipt, a screenshot, a chart — to Nemotron 3.5 Super VL, keep a fast text model for quick research, and save a frontier model for the hardest reasoning. Because it’s free in OpenCode and on OpenRouter, adding it costs nothing, and it fills a gap most free agent setups have.
My verdict on Nemotron 3.5 Super VL
Nemotron 3.5 Super VL is one of the most useful free models for agents right now: open, fast and able to see. Use it free in OpenCode or Hermes, and keep a frontier model for the hardest tasks.
FAQ: nemotron 3.5 super vl
What is Nemotron 3.5 Super VL?
Nvidia’s open 120B-parameter (12B active) vision-language model for agents, released 15 October 2026, which reads text, images, documents and short videos.
Is Nemotron 3.5 Super VL free?
Yes — it’s free in OpenCode at the time of writing, has a free variant on OpenRouter, and its weights are open on Hugging Face.
Is it better than Nemotron 3 Ultra?
On Nvidia’s agent tests it scored higher — 63.44% vs 56.33% on Hermes Bench — despite being smaller.
Can I run it on my computer?
Only with a lot of memory: the Ollama build is 80–90GB and LM Studio’s smallest is about 70GB.
Is it a frontier model?
No — it’s a fast, free open model, not a replacement for Claude Opus 5.5.
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I’m Julian Goldie — founder of Goldie Agency, best-selling author, and an AI educator with 428K+ YouTube subscribers. I’ve spent 10+ years in SEO and online business and I test every AI agent on my own work before I recommend it. Join the AI Profit Boardroom for the daily builds, or book a free strategy session to talk through yours.
