Back to all offerings

NVIDIA GB300

288 GB VRAM2,500 FP16 TFLOPS1,400 W TDP1 providers3 offerings0 regions

The NVIDIA GB300 is an enterprise-class GPU built on the Blackwell architecture, featuring 288 GB of memory with 8,000 GB/s of memory bandwidth and a 1,400 W TDP. It delivers 75 TFLOPS of FP32 performance and 2,500 TFLOPS of FP16 tensor performance. Currently available from 1 provider starting at $8.62/GPU/hour, with a market median of $8.62/GPU/hour across 3 configurations.

Cheapest
$8.620/hr
Verda
Median
$8.620/hr
across 3 offerings
Most expensive
$8.620/hr
Verda
90-day trend
0.0%
median rate

Hardware specifications

Same across all providers

Memory
288 GB
HBM3
What LLMs fit? ↓
FP16 performance
2,500 TFLOPS
peak
TDP
1400 W
Memory bandwidth
8,000 GB/s
Architecture
Blackwell
FP32 performance
75 TFLOPS
Brand
NVIDIA
Series
GB300
Market price history

Median price across all providers

Prices updated 4 hours ago

1 offering from 1 providers

Sorted by price ascending. Compare configurations side-by-side.

ProviderCountvCPURAMRegionPer GPU hourTotal/hrAction
Verda logoVerdaCheapest
×132225 GB--
$8.620
From$8.62
Launch

LLMs that fit on the NVIDIA GB300

Estimated VRAM for popular open-weight LLMs at 16-bit (FP16/BF16), 8-bit (FP8/INT8) and 4-bit (INT4/MXFP4) precision, against 288 GB per GPU. Showing the 12 largest that fit.

ModelParameters16-bit8-bit4-bit
DeepSeek V4 Pro
DeepSeek
1.6T
49B active
Not released
Not released
1,038 GB
4× · 114 GB free
Kimi K2.5
Moonshot AI
1T
32B active
Not released
Not released
714 GB
4× · 438 GB free
GLM-5.2
Z.ai
753B
1,808 GB
Too large
994 GB
4× · 158 GB free
579 GB
4× · 573 GB free
or 2× · 19% spare
DeepSeek R1
DeepSeek
671B
37B active
Not released
826 GB
4× · 326 GB free
481 GB
2× · 95 GB free
DeepSeek V4 Flash
DeepSeek
284B
Not released
Not released
192 GB
1× · 96 GB free
Solar Open2 250B
Upstage
250B
15B active
601 GB
4× · 551 GB free
or 2× · 15% spare
330 GB
2× · 246 GB free
or 1× · 4% spare
192 GB
1× · 96 GB free
Qwen3 235B-A22B
Alibaba
235B
22B active
564 GB
2× · 12 GB free
310 GB
2× · 266 GB free
or 1× · 11% spare
181 GB
1× · 107 GB free
Laguna-S 2.1
Poolside
118B
8B active
282 GB
1× · 5.8 GB free
155 GB
1× · 133 GB free
90 GB
1× · 198 GB free
gpt-oss-120b
OpenAI
117B
5.1B active
Not released
Not released
78 GB
1× · 210 GB free
Qwen3.6 35B-A3B
Alibaba
35B
3B active
86 GB
1× · 202 GB free
47 GB
1× · 241 GB free
28 GB
1× · 260 GB free
Qwen3 32B
Alibaba
32.8B
79 GB
1× · 209 GB free
43 GB
1× · 245 GB free
25 GB
1× · 263 GB free
Gemma 4 31B
Google
31.3B
75 GB
1× · 213 GB free
41 GB
1× · 247 GB free
24 GB
1× · 264 GB free

Estimates: model weights plus 20% for KV cache and runtime overhead, at short context lengths. Long contexts and large batches need more. Rows marked “tight” hold the weights but not that full margin. A ×N figure is the total VRAM across N of these GPUs and makes no claim about interconnect throughput. How we estimate this · Start from a model instead

Want more from this page?

See incorrect data?

Frequently asked questions

How much does the GB300 cost per hour?
The GB300 starts at $8.62 per GPU-hour, with a median of $8.62 across 3 available configurations. Actual pricing depends on the provider, region, and whether you rent on-demand, spot or reserved.
Which cloud providers offer the GB300?
1 providers currently list the GB300: Verda. Compare their hourly pricing, regions and machine specs in the table above.
How much VRAM does the GB300 have?
The GB300 comes with 288 GB of VRAM, which determines the largest models and batch sizes it can hold in memory for training and inference.
Which LLMs can I run on the GB300?
With 288 GB of VRAM, a single GB300 can serve models such as DeepSeek V4 Flash, Solar Open2 250B, Qwen3 235B-A22B, Laguna-S 2.1. The table above lists the estimated VRAM for each model at 16-bit, 8-bit and 4-bit precision, including the multi-GPU configurations needed for larger models.
What's the biggest LLM I can run on multiple GB300 GPUs?
The largest models we track that fit across several GB300 cards are DeepSeek V4 Pro on 4 GPUs at 4-bit, Kimi K2.5 on 4 GPUs at 4-bit, GLM-5.2 on 4 GPUs at 8-bit. A multi-GPU configuration means you rent and pay for every card for the whole run, and splitting a model across cards costs throughput as well: the GPUs exchange activations on every token, so performance depends on how fast they are wired together. We do not track interconnect, so check the provider's node specification. The table above gives the smallest configuration for each model at 16-bit, 8-bit and 4-bit precision.
Where is the GB300 cheapest?
The lowest on-demand price we currently track for the GB300 is $8.62 per GPU-hour at Verda. Because providers update pricing and availability frequently, check the live table above before you launch.