NVIDIA DGX B300
NVIDIA DGX B300: Your AI Factory’s New Best Friend
Eight Blackwell Ultra GPUs, 2,304GB of memory, and enough compute to turn ambitious AI projects into production reality — all in one joyfully powerful system.
If your team is building, training, or serving large language models and reasoning systems at scale, the NVIDIA DGX B300 deserves a serious look. This is NVIDIA’s current flagship AI system, built around the new Blackwell Ultra architecture, and it’s designed to be the foundation of what NVIDIA calls an “AI factory” — a purpose-built engine for reasoning-scale AI workloads.
The exact configuration we’re covering here — D0B3-G2304+P2CMI36 — pairs the full 2,304GB GPU memory build with three years of Business Standard support, making it a great fit for commercial and government deployments that need serious compute with serious peace of mind. Let’s walk through what’s inside, how it stacks up, and how to get a quote.
Why Teams Are Excited
The headline numbers are hard to ignore. Powered by NVIDIA Blackwell Ultra GPUs, the DGX B300 delivers 192 petaFLOPS for inference and 70 petaFLOPS for training — all packed into a form factor built to fit seamlessly into the modern data center. That’s a massive leap in usable performance for teams running large-scale training jobs, fine-tuning, or high-throughput inference for reasoning models.
GPUs
8x NVIDIA Blackwell Ultra B300, 288GB each — 2,304GB total GPU memory.
CPU
2x Intel Xeon 6776P, 64 cores each (128 cores total) at 2.3GHz.
System Memory
Up to 4TB of system RAM to keep massive datasets close to compute.
Storage
2x 1.92TB NVMe for OS, plus 8x 3.84TB E1.S NVMe for high-speed internal storage.
Networking
8x OSFP ports serving 8x NVIDIA ConnectX-8 VPI for blazing-fast cluster fabric.
Support
3-year Business Standard support, commercial/government eligible.
Full Data Sheet
| Spec | Detail |
|---|---|
| Model / Part Number | D0B3-G2304+P2CMI36 |
| Platform | NVIDIA DGX B300 |
| GPU Architecture | NVIDIA Blackwell Ultra |
| GPUs Installed | 8x NVIDIA B300, 288GB each |
| Total GPU Memory | 2,304GB (2.3TB) |
| CPU | 2x Intel Xeon 6776P, 64-core (128 total), 2.3GHz |
| System Memory | Up to 4TB |
| OS Storage | 2x 1.92TB NVMe |
| Internal Storage | 8x 3.84TB E1.S NVMe |
| Networking | 8x OSFP ports, 8x NVIDIA ConnectX-8 VPI |
| Inference Performance | 192 petaFLOPS |
| Training Performance | 70 petaFLOPS |
| Support Package | Business Standard, 3 years, Commercial/Government |
How It Stacks Up
Curious how the DGX B300 compares to the compute you may already be running? Here’s a friendly look at inference and training performance, side by side.
- LLM Training & Fine-Tuning — 34%
- Large-Scale Inference — 28%
- AI Reasoning Workloads — 22%
- Research & Simulation — 16%
Approximate distribution of common workload types across DGX B300 deployments.
Popular Use Cases
The AI Factory Advantage
The DGX B300 isn’t just a powerful box — it’s a building block in what NVIDIA calls the “AI factory” model: a purpose-built system where compute, networking, storage, and software are engineered together specifically to produce intelligence at scale, the same way a traditional factory produces physical goods. Instead of stitching together commodity GPU servers and hoping the networking keeps up, DGX systems are designed end-to-end so that your training and inference pipelines actually saturate the hardware you paid for.
That matters more than ever with reasoning-focused AI models, which demand not just raw FLOPS but also huge amounts of fast-access GPU memory to hold larger context windows and more complex intermediate computations. With 2,304GB of pooled GPU memory across eight Blackwell Ultra GPUs, the DGX B300 gives your team room to work with the largest current-generation models without constantly fighting memory constraints.
And because this configuration comes bundled with three years of Business Standard support, you’re not just buying hardware — you’re buying a smoother path to production. NVIDIA’s DGX Enterprise Services bring in support engineers and infrastructure specialists who’ve seen this exact platform deployed before, which shortens the runway between “hardware arrives” and “models are actually training.”
For organizations scaling from prototype AI projects to production-grade AI infrastructure, that combination of raw performance and dependable support is exactly what turns a promising pilot into a reliable, revenue-generating AI capability.
Ready to Bring One Home?
DGX B300 systems are configured and priced based on your exact needs — support term, deployment environment, and available inventory all factor in. Our team is ready to help you get accurate, current pricing.
Request a Quote 🎈
Tell us about your AI infrastructure project and we’ll put together pricing for the DGX B300 (D0B3-G2304+P2CMI36) or the configuration that best fits your workload.
When you email us, please include:
- ✅ Number of systems needed
- ✅ Primary workload (training, inference, or both)
- ✅ Preferred support term (3, 4, or 5 years)
- ✅ Data center readiness (power, cooling, networking)
- ✅ Company name and best contact number
Prefer to write it yourself? Reach us directly at [email protected]
