Nvidia Nemotron 3.5: The Fastest Open AI Model Claim, Explained
Nvidia has launched its own new AI model, and the headline claim is speed. I have researched what Nvidia actually released on 15 October 2026, and I have found that the important detail is not just "fast" — it is fast for a specific kind of work, in a specific class of models, and with the weights open for anyone to download. After comparing Nvidia's announcement with independent coverage of the release, this article explains what Nemotron 3.5 Super VL is, what the smaller Bolt models mean for laptops, and what the NVDA share price looked like around the launch. It is price and product information only, not a recommendation to buy or sell anything.
What Nvidia launched on 15 October 2026
Nvidia released Nemotron 3.5 Super VL, an open 120-billion-parameter model built for specialised, always-on agents — the kind of AI that works through multi-step business tasks, uses tools, and understands images and text together, rather than answering one question and stopping. Alongside it came two smaller models in the same family, Nemotron 3.5 Bolt, designed to run locally on Nvidia systems instead of in a cloud data centre.
In my analysis, this is a deliberate shift in strategy. Nvidia is best known for the chips that other companies use to run AI. With Nemotron, Nvidia is also supplying the model itself, in open form, so that more AI work runs well on Nvidia hardware. The model is the invitation; the hardware is where the value is captured.
Nemotron 3.5 Super VL in plain terms
| Feature | What Nvidia says |
|---|---|
| Size | 120 billion parameters, mixture-of-experts design, about 12 billion active at a time |
| Context window | 1 million tokens |
| Speed claim | Fastest task completion in its class for specialised always-on agents, 5x faster than the next best open model in its class |
| Accuracy claim | Frontier-level accuracy for its class on agentic tasks such as instruction following, tool use, multi-step workflows and visual understanding, at roughly one-fifth the size of Nvidia's largest reasoning model |
| Availability | Open weights, with a commercial-friendly licence, distributed through Hugging Face, OpenRouter and ModelScope |
The key phrase is "in its class". Super VL is not claimed to be faster than every AI model in the world. It is claimed to be the fastest open agentic model in its class — that is, among open-weight models built for agent work. That distinction matters, because closed frontier models are a different class, and they are not part of this comparison.
What "5x faster" really means — and what it does not prove yet
When Nvidia says 5x faster, it means task completion speed for high-volume agent workflows, not simply how quickly a model can type out a reply. For an agent that runs for days or weeks, completing each task faster changes the cost of the whole job, because every inefficiency is multiplied over time.
I have found one honest caveat that must stay with the claim: at the time of release, the speed figure was vendor-reported. Independent trackers had not yet scored it, so the claim should be treated as Nvidia's measurement until outside benchmarks confirm it. A reader who repeats "fastest ever" without that caveat is repeating a press claim, not a verified result.
Nemotron 3.5 Bolt: AI that runs on your laptop
Bolt is the part of the launch that most ordinary users will feel first. Bolt 74B-A9B is a 74-billion-parameter model fitted into 24 GB of memory, the kind available on high-end RTX laptops, and Bolt E4B is a smaller 4 GB model for fast conversational agents. The point of a local model is simple: lower delay, no data leaving the machine, and no cloud subscription standing between the user and the model.
After comparing the two approaches, the trade-off is clear. Cloud models can be larger and more powerful, but they depend on a connection and a service. Local models are smaller, but they are private, fast to respond, and available offline. Bolt is Nvidia's bet that serious agent work will increasingly happen on the desk, not only in the data centre.
NVDA price around the launch
Prices are indicative and may vary by exchange. The figures below are the regular-session close on Friday 23 October 2026, because the US market was closed on Sunday 25 October 2026, when this article was written. They are not a live price.
- NVDA close, 23 October 2026: $210.96, down $1.25 (-0.59%) on the day
- Previous close: $212.21; day's range: $210.18 – $213.85
- 52-week range: $164.27 – $243.37
- Market capitalisation: about $5.1 trillion
- On the launch day itself, 15 October 2026, NVDA closed at $217.20, down 0.17% on the day
In other words, the launch did not coincide with a sharp one-day jump in the share price in the figures above. A product launch and a share price move on the same week are two separate facts, and one does not prove the other. This article gives the price for context only. It does not predict where the price will go, and it does not advise buying, selling or holding NVDA. For live prices in USD, EUR, GBP and CHF, see the price calculator on the Sulivex home page.
Why this launch matters for the AI market
For the past year, the open-weight leaderboard has been led largely by Chinese labs, with models such as GLM, Kimi, DeepSeek and Qwen trading top spots. Super VL is Nvidia's clearest attempt to put a US open-weight model back at the top on the metric that increasingly decides agent deployments: not raw intelligence alone, but completed tasks per dollar per second.
For enterprises, the practical question is not whether a model is impressive in a demo, but whether it can run a high-volume agent workflow reliably and affordably for weeks. If Super VL's speed claim holds up in independent testing, it would make that workflow cheaper on Nvidia infrastructure. If it does not, the launch is still significant as an open model with a commercial licence, because open weights lower the barrier for companies to start building.
What to watch next
- Independent benchmarks for Super VL, to test the 5x speed claim outside Nvidia
- Availability and real-world use of Bolt E4B, which was due on 23 October 2026
- RTX Spark laptops reaching users in October 2026, and whether local agent models become a normal laptop feature
- Enterprise adoption — whether companies named as early users actually deploy Super VL in production agent workflows
Common questions
Is Nemotron 3.5 free to use? The weights are open under a commercial-friendly licence, so developers and companies can download and build on them. Running a 120-billion-parameter model still needs serious hardware, so "open" does not mean "free to run on any computer".
Is this the fastest AI ever? No, not in absolute terms. It is claimed to be the fastest open agentic model in its class. Closed frontier models, and models built for different tasks, are not part of that claim.
Does this replace ChatGPT or other chatbots? No. Super VL is built for specialised agent work, and Bolt is built for local agents. General chatbots serve a different use, and most users will not run a 120-billion-parameter model themselves.
Should I buy NVDA because of this launch? This article does not answer that question. It gives product and price information only. Investment decisions need your own research, and ideally advice from a qualified financial adviser who knows your situation.
References
- Nvidia announcement via HPCWire, 15 October 2026: Nvidia expands Nemotron family with Super VL and Bolt models — hpcwire.com
- Independent coverage of the open-weights release, 20 October 2026 — ai-blogs.org
- NVDA price, regular-session close 23 October 2026 — stockanalysis.com and finnhub.io
Sulivex provides price comparison only. Not financial advice. Prices are approximate — verify before making decisions.
Frequently asked questions
What is Nemotron 3.5 Super VL? An open 120-billion-parameter model built for specialised, always-on agents, the kind of AI that works through multi-step business tasks, uses tools, and understands images and text together, rather than answering one question and stopping. It uses a mixture-of-experts design with about 12 billion parameters active at a time, and a context window of 1 million tokens.
What does the 5x faster claim actually mean? It means task completion speed for high-volume agent workflows in its class, not simply how quickly a model can type out a reply, and it is claimed to be the fastest open agentic model in its class. The article keeps one caveat: at the time of release the speed figure was vendor-reported and independent trackers had not yet scored it, so it should be treated as Nvidia's measurement until outside benchmarks confirm it.
What are Nemotron 3.5 Bolt models for? Bolt models are designed to run locally on Nvidia systems instead of in a cloud data centre. Bolt 74B-A9B is a 74-billion-parameter model fitted into 24 GB of memory, the kind available on high-end RTX laptops, and Bolt E4B is a smaller 4 GB model for fast conversational agents. The point of a local model is lower delay, no data leaving the machine, and no cloud subscription standing between the user and the model.
Not financial advice. This article is for general information and research purposes only. The "fastest" speed claim is Nvidia's vendor-reported claim, in its class, not an independently verified absolute result. NVDA prices are indicative, from the regular-session close on Friday 23 October 2026, and are not live prices. It is not a recommendation to buy, sell, or hold any security. Sulivex provides price comparison only. Prices are approximate — verify current figures before making decisions. Do your own research and consider speaking with a qualified financial professional if you need personalized advice.
