Nvidia GB300

Nvidia GB300

Grace CPU + Blackwell Ultra GPU superchip built for rack-scale AI reasoning and inference.

Compare vs other GPUs →
Aggregating historical prices...

Weekly median price per GPU per hour. Nvidia GB300 price history (JSON).

At a glance

Hardware

Architecture
Grace Blackwell Ultra
Memory per GPU
288 GB HBM3e
Memory bandwidth
8,000 GB/s
Release date
Q1 2025

Market Updated 15 minutes ago

Cheapest
$18.00 / GPU / hr
on-demand · not verified in stock
Coverage
6 providers
26 configs · none verified in stock

GB300 Pricing and Availability

6 providers

How this list works

The two views

By provider shows one card per company, placed where its best offer ranked. By configuration lists every offer.

Order

What you can rent comes first: in stock, then waitlist, then not reported, then out of stock. Priced offers rank ahead of quote-only, and on-demand ahead of other billing types.

Within a group, five factors set the order:

  1. Location: datacenter proximity, blended with provider HQ.
  2. Price: hourly price, per GPU and in total.
  3. Billing type: reserved ahead of spot, spot ahead of quote-only.
  4. Specs: more VRAM, vCPUs and RAM.
  5. Provider diversity: a provider's repeat rows rank slightly lower, so one company can't take all the top spots.

Search

We match the provider, its country, GPU model, form factor, billing type, availability and instance name. Matching is partial and case-insensitive. Everyday words work too, so "interruptible" finds spot and "sold out" finds out of stock.

Transparency and funding

  • Ads and sponsors: Paid placements sit at the top of the list and are always labeled as sponsored content. Sponsorship never influences the organic ranking itself.
  • Affiliates: Affiliate links are marked. We may earn a commission if you click them, but commissions never affect the order.
  • Prices: Shown in USD, converted at daily reference rates where a provider publishes in another currency. A month means 720 hours. How we estimate costs.
Oracle Cloud logo

United States of America flag USA 1 config 4x

On-Demand from $18.00
From $18.00 / GPU / hr On-Demand NVL Visit website
Nebius logo

Netherlands flag Netherlands 1 config 1x

Custom on request
Pricing On request Custom NVL Visit website
Amazon Web Services logo

AWS

United States of America flag USA 1 config 72x

Reserved on request
Pricing On request Reservation Visit website
Gcore logo

Luxembourg flag Luxembourg 1 config 72x

Custom on request
Pricing On request Custom NVL Visit website
Together AI logo

United States of America flag USA 1 config 72x

Custom on request
Pricing On request Custom NVL Visit website
Verda logo

Verda

Out of stock

Finland flag Finland 21 configs 1x-4x

On-Demand from $8.62 Reserved from $6.46 Spot from $4.31
From $8.62 / GPU / hr On-Demand SXM Visit website

Heads up: A provider's own page may quote a different figure, for example on tax, region or a promotion. A monthly-only plan shows a derived hourly rate. Verify before provisioning. More on how we price.

What size AI models can the GB300 run?

One GB300 has 288 GB of VRAM. In practice, that's enough memory for roughly 460B parameters at 4-bit or 125B at 16-bit, assuming a 32K context. Below are some open-weight LLMs, with the estimated memory and GPUs each one needs.

Model Parameters 4-bitINT4 / FP4 8-bitFP8 / INT8 16-bitFP16 / BF16
Alibaba Cloud logo Qwen3.8-27B
27B
1 GPU 18 GB VRAM
1 GPU 30 GB VRAM
1 GPU 58 GB VRAM
Google Cloud logo Gemma 4 31B
30.7B
1 GPU 22 GB VRAM
1 GPU 35 GB VRAM
1 GPU 69 GB VRAM
OpenAI logo GPT-OSS-120B
117B 5.1B active
1 GPU 67 GB VRAM
1 GPU 120 GB VRAM
1 GPU 237 GB VRAM
DeepSeek logo DeepSeek V4 Flash
284B 13B active
1 GPU 160 GB VRAM
4 GPUs 287 GB VRAM
4 GPUs 573 GB VRAM
Z.AI logo GLM-5.3-Flash
320B 18B active
1 GPU 178 GB VRAM
4 GPUs 322 GB VRAM
4 GPUs 642 GB VRAM
MiniMax logo MiniMax-M3
428B 23B active
1 GPU 239 GB VRAM
4 GPUs 432 GB VRAM
4 GPUs 862 GB VRAM
Moonshot AI logo Kimi K3
2.8T 104B active
6 GPUs 1,544 GB VRAM
11 GPUs 2,804 GB VRAM
22 GPUs 5,605 GB VRAM

Estimates based on the median on-demand rate. Memory is weights plus FP8 KV cache at 32K context per request (FP16/BF16 in the 16-bit column). GPU counts assume 90% of advertised VRAM is usable. No guarantee of runtime support, usable performance, or that a matching quantized build exists. How we estimate costs.

Technical Specifications

Nvidia GB300 · Per GPU

Compute · dense
FP4 15,000 TFLOPS
FP8 5,000 TFLOPS 10,000 with sparsity
FP16 / BF16 2,500 TFLOPS 5,000 with sparsity
INT8 165 TOPS 330 with sparsity
FP32 80 TFLOPS
FP64 1.3 TFLOPS
Precision support FP4FP6FP8FP16BF16TF32FP32FP64INT8
Memory
Capacity 288 GB HBM3e
Bandwidth 8,000 GB/s
Bus width 8,192-bit
ECC Yes
Silicon
Architecture Blackwell Ultra
Process TSMC 4NP
Transistors 208 billion
Shader cores 20,480 CUDA cores
Matrix cores 640 Tensor cores
Compute units 160 SMs
Fabric and host
GPU interconnect NVLink 1,800 GB/s
Host interface PCIe 6.0 x16
Power
Board power 1,400 W
Cooling Liquid
Platform
Partitioning MIG, up to 7 instances

Source: official Nvidia GB300 datasheet.

Frequently Asked Questions

How much does the GB300 cost per hour?

As of September 1, 2026, we track 26 configs from 6 providers. Prices are per GPU per hour.

Billing type Configs Median / GPU / hr Cheapest in stock
On-demand 4 $18.00
Reserved 16 On request
Spot 3 Sold out
Custom contract 3 On request

No median for on-demand: we only show this when at least 3 providers list the GPU on that billing type. Custom-contract pricing is negotiated per deal and usually not published.

Who has the cheapest GB300?

As of September 1, 2026, the lowest listed on-demand price for the GB300 is $18.00 per GPU per hour from Oracle Cloud, though we haven't verified current stock.

Where can I rent a GB300?

GetDeploying currently tracks GB300 configs from 6 providers. See the full price comparison above for every provider and config.

How many GB300 GPUs do I need?

One GB300 runs models up to roughly 460B parameters at 4-bit quantization or 125B at 16-bit, assuming a 32K context. Larger models run across multiple GPUs: the model table above shows the estimated memory and GPU count for popular open-weight LLMs.

Why choose the GB300?

Pairs Grace CPUs with Blackwell Ultra GPUs carrying 288GB HBM3e each, connected in a 72-GPU NVLink domain. Suited for frontier-scale training and long-context reasoning inference where per-GPU memory and interconnect bandwidth are the bottleneck.

When is the GB300 not a good fit?

Rack-scale form factor with limited cloud availability at the highest cost tier. The GB200 offers a similar architecture with wider availability, and the standalone B200 is sufficient for most Blackwell workloads.

Alternatives to Nvidia GB300

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