Nemotron 3.5 Bolt Description

NVIDIA Nemotron 3.5 Bolt is a series of efficient AI models developed by NVIDIA for running autonomous agents and conversational applications directly on local hardware. The family consists of Bolt 74B-A9B 24GB and Bolt E4B 4GB, which address different performance and memory requirements. Bolt 74B-A9B uses a mixture-of-experts architecture with 74 billion total parameters and approximately 9 billion active parameters to balance reasoning capabilities with computational efficiency. Native 2-bit quantization enables the model to operate within a 24GB memory footprint on supported NVIDIA systems. Its agentic capabilities include web research, code generation, software debugging, information retrieval, and multistep task execution. The model can be integrated with local AI agent frameworks and development tools to complete assignments without sending application workloads to external inference services. Bolt E4B is optimized for fast conversational responses, multistep interactions, and embedded AI experiences such as virtual assistants and interactive game characters. NVIDIA supports local deployment of the Bolt family across compatible GeForce RTX, RTX PRO, DGX Spark, and Jetson hardware, depending on the model variant. Bolt 74B-A9B is available with open weights through Hugging Face and supports inference tools including llama.cpp, Ollama, LM Studio, Unsloth, and vLLM.

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Pricing

Pricing Starts At:
Free
Free Version:
Yes

Integrations

API:
Yes, Nemotron 3.5 Bolt has an API
View Integrations

Company Details

Company:
NVIDIA
Year Founded:
1993
Headquarters:
United States
Website:
nvidia.com

Media

Nemotron 3.5 Bolt Screenshot 1
Nemotron 3.5 Bolt Screenshot 1
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Product Details

Platforms
Web-Based
Linux
On-Premises
Types of Training
Training Docs

Nemotron 3.5 Bolt Features and Options

Nemotron 3.5 Bolt User Reviews

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  • Name: Anonymous (Verified)
    Job Title: CTO
    Length of product use: Less than 6 months
    Used How Often?: Daily
    Role: User, Administrator
    Organization Size: 26 - 99
    Features
    Pricing
    Likelihood to Recommend to Others
    1 2 3 4 5 6 7 8 9 10

    Really good/fast model for agents

    Date: Oct 15 2026

    Summary: Overall, Nemotron 3.5 Bolt is one of the most practical local agent models I have seen. It gives me strong reasoning and agent capability with much more privacy, control, and deployment flexibility than a cloud-only model.

    Positive: What I like most is that I can run a genuinely capable agent model locally without needing datacenter hardware. The 74B-A9B version fits in 24GB of memory, which makes it realistic for high-end RTX systems and DGX Spark. It is also surprisingly useful for real agent work. I can use it for research, coding, debugging, writing, and multi-step tasks while keeping everything on my own machine instead of pushing code or sensitive data to a cloud API. The performance-to-memory tradeoff is probably the biggest win. NVIDIA says Bolt 74B-A9B is the #1 open model in its class on PinchBench and #2 on BrowseComp, so it is not just small enough to run locally — it is actually competitive at agentic tasks.

    Negative: The main downside is that 24GB is still a meaningful hardware requirement, and local inference will not always match the raw capability of the biggest cloud frontier models.

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