Nemotron 3.5 Bolt Reviews

Nemotron 3.5 Bolt

5.0 out of 5 stars

Average Ratings 1 Rating

Total 5 out of 5 stars
features 5 out of 5 stars

Average Ratings 0 Ratings

Total 0 out of 5 stars
ease 0 out of 5 stars
features 0 out of 5 stars
design 0 out of 5 stars
support 0 out of 5 stars

No User Reviews. Be the first to provide a review:

Write a Review

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.

Description

Qwen3.5-35B-A3B is a member of the Qwen3.5 "Medium" model series, meticulously crafted as an effective multimodal foundation model that strikes a balance between robust reasoning capabilities and practical application needs. Utilizing a Mixture-of-Experts (MoE) architecture, it boasts a total of 35 billion parameters, yet activates only around 3 billion for each token, enabling it to achieve performance levels similar to much larger models while significantly cutting down on computational expenses. The model employs a hybrid attention mechanism that merges linear attention with traditional attention layers, which enhances its ability to handle extensive context and boosts scalability for intricate tasks. As an inherently vision-language model, it processes both textual and visual data, catering to a variety of applications, including multimodal reasoning, programming, and automated workflows. Furthermore, it is engineered to operate as a versatile "AI agent," proficient in planning, utilizing tools, and systematically solving problems, extending its functionality beyond mere conversational interactions. This capability positions it as a valuable asset across diverse domains, where advanced AI-driven solutions are increasingly required.

API Access

Has API Yes 

API Access

Has API Yes 

Screenshots View All

Screenshots View All

Integrations

Baseten Yes 
Cheaper Inference No 
Hugging Face No 
Hugging Face Transformers Yes 
ModelScope No 
NVIDIA NIM Yes 
Ollama No 
OpenClaw No 
OpenRouter Yes 
Qwen No 
Qwen Studio No 
vLLM Yes 

Integrations

Baseten No 
Cheaper Inference Yes 
Hugging Face Yes 
Hugging Face Transformers No 
ModelScope Yes 
NVIDIA NIM No 
Ollama Yes 
OpenClaw Yes 
OpenRouter No 
Qwen Yes 
Qwen Studio Yes 
vLLM No 

Pricing Details

Free
Free Trial No 
Free Version Yes 

Pricing Details

Free
Open source
Free Trial No 
Free Version Yes 

Deployment

Web-Based Yes 
On-Premises Yes 
iPhone App No 
iPad App No 
Android App No 
Windows No 
Mac No 
Linux Yes 
Chromebook No 

Deployment

Web-Based Yes 
On-Premises Yes 
iPhone App Yes 
iPad App Yes 
Android App Yes 
Windows Yes 
Mac Yes 
Linux Yes 
Chromebook Yes 

Customer Support

Business Hours No 
Live Rep (24/7) No 
Online Support No 

Customer Support

Business Hours No 
Live Rep (24/7) No 
Online Support No 

Types of Training

Training Docs Yes 
Webinars No 
Live Training (Online) No 
In Person No 

Types of Training

Training Docs Yes 
Webinars No 
Live Training (Online) No 
In Person No 

Vendor Details

Company Name

NVIDIA

Founded

1993

Country

United States

Website

nvidia.com

Vendor Details

Company Name

Alibaba

Founded

1999

Country

China

Website

qwen.ai/blog

Alternatives

GPT-6.1 Terra Reviews

GPT-6.1 Terra

OpenAI
5.0 out of 5 stars

Alternatives

Bonsai 27B Reviews

Bonsai 27B

PrismML
GPT-5.5 Reviews

GPT-5.5

OpenAI
5.0 out of 5 stars
Nemotron 3.5 Super VL Reviews

Nemotron 3.5 Super VL

NVIDIA
5.0 out of 5 stars
Qwen3.5 Reviews

Qwen3.5

Alibaba
GPT-6.1 Sol Reviews

GPT-6.1 Sol

OpenAI
5.0 out of 5 stars
DeepSeek-V4-Flash Reviews

DeepSeek-V4-Flash

DeepSeek
5.0 out of 5 stars