Buy the wrong shape of AI hardware, and you'll be re-architecting in six months, not running experiments. Some teams need one model too big for any single GPU. Others need several agents running independently at once. The Exxact Valence with GB300 solves the first case, pooling up to 748GB of coherent memory for 200B+ parameter models. The Exxact Valence 4x Max-Q solves the second, giving each agent its own 96GB NVIDIA RTX PRO 6000 Max-Q GPU, with headroom to double as a rendering or simulation workstation. Full breakdown and decision table in the comments. NVIDIA #GB300 #AgenticAI #LocalAI #HPC
Exxact Corporation
Computer Hardware
Fremont, CA 5,143 followers
Accelerating discovery with GPU Workstations, Servers, & HPC Clusters for Deep Learning, AI, & Scientific Computing.
About us
Exxact Corporation is a leading global provider of advanced computing solutions, empowering organizations to accelerate innovation and accomplish their goals. Specializing in system integration, contract manufacturing, and IT distribution, we deliver cutting-edge platforms tailored for deep learning, artificial intelligence, machine learning, and high performance computing (HPC). Our expertise spans a wide array of industries and applications, including life sciences, molecular dynamics, engineering simulation, computer vision, big data analytics, and natural language processing (NLP). At our ISO 9001:2015-certified facility, Exxact leverages the latest GPU technologies and frameworks to design, engineer, and build turnkey workstations, servers, clusters, and storage solutions optimized for the most demanding workloads. From initial consultation and solution validation to manufacturing, deployment, and ongoing support, our end-to-end services ensure seamless integration and maximum performance. With a customer-centric approach and partnerships with industry leaders like NVIDIA, AMD, and more, Exxact supports over 3,000 clients worldwide and is recognized as NVIDIA Partner Network Solution Integration Partner of the Year for two consecutive years. Exxact also offers standalone comprehensive suite of services—including smart hands support, integration and infrastructure, logistics and supply chain management, and rack integration—that enable clients to deploy, scale, and optimize their IT environments with confidence. Whether you’re advancing breakthroughs in life sciences, deploying large-scale HPC clusters, or harnessing AI for business transformation, Exxact is your trusted partner for next-generation computing solutions.
- Website
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https://www.exxactcorp.com
External link for Exxact Corporation
- Industry
- Computer Hardware
- Company size
- 51-200 employees
- Headquarters
- Fremont, CA
- Type
- Privately Held
- Founded
- 1992
- Specialties
- System Integration, Contract Manufacturing, Deep Learning, IT Distribution, Big Data, Life Sciences, Molecular Dynamics, High Performance Computing, Machine Learning, Artificial Intelligence, Computer Vision, GPU, Data Science, NLP, HPC, TensorFlow, and PyTorch
Employees at Exxact Corporation
View 91 employees at Exxact Corporation
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Locations
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Primary
Get directions
46221 Landing Parkway
Fremont, CA 94538, US
Updates
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New Benchmark Alert! We ran DeepSeek-V4-Flash-0731 on an Exxact Valence built on NVIDIA DGX Station GB300 to test concurrency scalability and reliability. We acheived 10x concurrent AI agents each with 1M tokens context window, ideal for not just for an individual, but an entire team’s extremely large corpus of text and full scale codebase review. Full results and reproduce the steps here. https://lnkd.in/gvXStYwf #DeepSeek #NVIDIA
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BioTuring's spatial multi-omics AI platforms were hitting GPU memory ceilings, forcing batching and capping concurrent samples for researchers worldwide. With the help of Exxact, BioTuring deployed 3 NVIDIA DGX™ B300 systems, relieving their bottlenecks and enabling full-scale pipelines and faster AI fine-tuning. Read the case study to learn more. https://lnkd.in/gKHNuEAy BioTuring NVIDIA
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Need an NVIDIA DGX Spark, RTX PRO Workstation, or DGX Station to run the recently announced NVIDIA Nemotron 3.5 Lightning? Exxact's got you covered. #EnterpriseAI #DigitalTransformation #AIInnovation #AIInfrastructure
Meet NVIDIA Nemotron 3.5 Lightning, built to make always-on AI agents seriously fast.⚡ The new open, customizable 30B MoE model delivers up to 4X faster token generation and 30% faster time to completion compared with open models in its class. Build and customize agents around your organization’s needs while keeping everything local on DGX Spark, RTX PRO Workstations, or DGX Station. Learn more: https://lnkd.in/gmr45sZZ
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Molecular dynamics workloads are growing fast—bigger systems, longer trajectories, more replicas. This post breaks down 3 signs your GPU is now the bottleneck and how to choose an upgrade based on your engine (AMBER, GROMACS, NAMD). https://lnkd.in/gVvCFjbF #GPU #Moleculardynamics
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Agentic AI performs best as a pool of specialized models. Explore how NVIDIA Nemotron 3.5 Lightning, NeMo Switchyard, and Exxact AI infrastructure help enterprises deploy efficient, local AI agent workflows. https://lnkd.in/gcW9yUmA NVIDIA NVIDIA AI Infrastructure
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Planning a 4× NVIDIA DGX Spark cluster for larger local models or multi-node workflows? In this guide, we will cover managed switch selection, QSFP cabling options, power considerations, and key configuration steps. https://lnkd.in/guRTvxkB #NVIDIA #DGXSpark
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Agentic AI changes GPU sizing: context length, KV cache, and concurrency can rival model weights. This guide compares DGX Spark, RTX 6000 workstations, and DGX Station for real deployments. https://lnkd.in/gQRdCvv7 #GPU #AgenticAI
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Teams often trade data privacy for AI-powered productivity. Metricle didn't have to. With two NVIDIA DGX Spark systems running DeepSeek V4 Flash on-prem, their team gets code review and dev support with zero cloud exposure and zero impact on production infrastructure. Full case study: https://lnkd.in/gXvRW33T
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You can run Claude Code locally. No cloud dependency required. By pointing Claude Code to an Anthropic-compatible endpoint (DS4 or Ollama), you can improve uptime, keep code on your hardware, and reduce long-term costs. We also benchmarked Claude Code vs OpenCode vs Qwen Code. https://lnkd.in/gHBX3hwr #Claude
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