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NVIDIA B200 CC

180 GB VRAM2,250 FP16 TFLOPS1,000 W TDP1 providers3 offerings0 regions

The NVIDIA B200 CC is an enterprise-class GPU built on the Blackwell architecture, featuring 180 GB of memory with 8,000 GB/s of memory bandwidth and a 1,000 W TDP. It delivers 75 TFLOPS of FP32 performance and 2,250 TFLOPS of FP16 tensor performance. Currently available from 1 provider starting at $6.88/GPU/hour, with a market median of $6.89/GPU/hour across 3 configurations.

Cheapest
$6.884/hr
Verda
Median
$6.885/hr
across 3 offerings
Most expensive
$6.885/hr
Verda
90-day trend
+10.5%
median rate

Hardware specifications

Same across all providers

Memory
180 GB
HBM3
What LLMs fit? ↓
FP16 performance
2,250 TFLOPS
peak
TDP
1000 W
Memory bandwidth
8,000 GB/s
Architecture
Blackwell
FP32 performance
75 TFLOPS
Brand
NVIDIA
Series
B200
Market price history

Median price across all providers

Prices updated 3 hours ago

1 offering from 1 providers

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

ProviderCountvCPURAMRegionPer GPU hourTotal/hrAction
Verda logoVerdaCheapest
×82401.33 TB--
From$6.884
+10.5% 30d
From$55.07
Launch

LLMs that fit on the NVIDIA B200 CC

Estimated VRAM for popular open-weight LLMs at 16-bit (FP16/BF16), 8-bit (FP8/INT8) and 4-bit (INT4/MXFP4) precision, against 180 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
8× · 402 GB free
Kimi K2.5
Moonshot AI
1T
32B active
—
Not released
—
Not released
714 GB
4× · 5.8 GB free
GLM-5.2
Z.ai
753B
1,808 GB
Too large
994 GB
8× · 446 GB free
579 GB
4× · 141 GB free
DeepSeek R1
DeepSeek
671B
37B active
—
Not released
826 GB
8× · 614 GB free
or 4× · 4% spare
481 GB
4× · 239 GB free
DeepSeek V4 Flash
DeepSeek
284B
—
Not released
—
Not released
192 GB
2× · 168 GB free
or 1× · 12% spare
Solar Open2 250B
Upstage
250B
15B active
601 GB
4× · 119 GB free
330 GB
2× · 30 GB free
192 GB
2× · 168 GB free
or 1× · 12% spare
Qwen3 235B-A22B
Alibaba
235B
22B active
564 GB
4× · 156 GB free
310 GB
2× · 50 GB free
181 GB
2× · 179 GB free
or 1× · 19% spare
Laguna-S 2.1
Poolside
118B
8B active
282 GB
2× · 78 GB free
155 GB
1× · 25 GB free
90 GB
1× · 90 GB free
gpt-oss-120b
OpenAI
117B
5.1B active
—
Not released
—
Not released
78 GB
1× · 102 GB free
Qwen3.6 35B-A3B
Alibaba
35B
3B active
86 GB
1× · 94 GB free
47 GB
1× · 133 GB free
28 GB
1× · 152 GB free
Qwen3 32B
Alibaba
32.8B
79 GB
1× · 101 GB free
43 GB
1× · 137 GB free
25 GB
1× · 155 GB free
Gemma 4 31B
Google
31.3B
75 GB
1× · 105 GB free
41 GB
1× · 139 GB free
24 GB
1× · 156 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

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Frequently asked questions

How much does the B200 CC cost per hour?
The B200 CC starts at $6.88 per GPU-hour, with a median of $6.89 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 B200 CC?
1 providers currently list the B200 CC: Verda. Compare their hourly pricing, regions and machine specs in the table above.
How much VRAM does the B200 CC have?
The B200 CC comes with 180 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 B200 CC?
With 180 GB of VRAM, a single B200 CC can serve models such as Laguna-S 2.1, gpt-oss-120b, Qwen3.6 35B-A3B, Qwen3 32B. 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 B200 CC GPUs?
The largest models we track that fit across several B200 CC cards are DeepSeek V4 Pro on 8 GPUs at 4-bit, Kimi K2.5 on 4 GPUs at 4-bit, GLM-5.2 on 4 GPUs at 4-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 B200 CC cheapest?
The lowest on-demand price we currently track for the B200 CC is $6.88 per GPU-hour at Verda. Because providers update pricing and availability frequently, check the live table above before you launch.