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NVIDIA RTX PRO 6000

96 GB VRAM9 providers53 offerings11 regions

The NVIDIA RTX PRO 6000 is an enterprise-class GPU built on the Blackwell architecture, featuring 96 GB of memory. Currently available from 9 providers starting at $0.50/GPU/hour, with a market median of $1.89/GPU/hour across 53 configurations.

Cheapest
$0.500/hr
Runpod
Median
$1.890/hr
across 53 offerings
Most expensive
$8.250/hr
Latitude.sh
90-day trend
+13.2%
median rate

Hardware specifications

Same across all providers

Architecture
Blackwell
Brand
NVIDIA
Series
RTX PRO
Market price history

Median price across all providers

Prices updated 32 minutes ago

10 offerings from 9 providers

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

ProviderCountvCPURAMRegionPer GPU hourTotal/hrAction
Runpod logoRunpodPromoted
Up to$500creditAffiliate promotion — we may earn a commission.
×116140 GB
IcelandUnited StatesRomania+1
$2.090$2.09Launch
Vast.ai logoVast.aiReferral linkTrendingCheapest
×456409 GB
United StatesCanadaChina+6
From$0.890
-5.4% 30d
From$3.56
Launch
×1146 GB
United States
$1.680
0.0% 30d
$1.68
Launch
×128225 GB
Canada
$1.850
From$1.85
×13090 GB--
$1.890
From$1.89
Launch
Runpod logoRunpodReferral linkTrending
Up to$500credit
×116140 GB
IcelandUnited StatesRomania+1
From$2.090
-9.6% 30d
From$2.09
Launch
×116144 GB
United States
$2.140
0.0% 30d
From$2.14
Launch
×116192 GB
United States
From$2.300
0.0% 30d
From$2.30
Launch
Sesterce Cloud logoSesterce CloudReferral link
×116192 GB
United StatesAustralia
From$2.409
0.0% 30d
From$2.41
Launch
×116192 GB
AustraliaUnited States
$2.410
+12.1% 30d
From$2.41
Launch
Latitude.sh logoLatitude.shReferral link
×81281.5 TB
United StatesNetherlandsAustralia
From$6.000
0.0% 30d
From$48.00
Launch

LLMs that fit on the NVIDIA RTX PRO 6000

Estimated VRAM for popular open-weight LLMs at 16-bit (FP16/BF16), 8-bit (FP8/INT8) and 4-bit (INT4/MXFP4) precision, against 96 GB per GPU. Showing the 12 largest that fit.

ModelParameters16-bit8-bit4-bit
Kimi K2.5
Moonshot AI
1T
32B active
Not released
Not released
714 GB
8× · 54 GB free
GLM-5.2
Z.ai
753B
1,808 GB
Too large
994 GB
Too large
579 GB
8× · 189 GB free
DeepSeek R1
DeepSeek
671B
37B active
Not released
826 GB
Tight on 8× · 11% spare
481 GB
8× · 287 GB free
DeepSeek V4 Flash
DeepSeek
284B
Not released
Not released
192 GB
Barely fits on 2×
Solar Open2 250B
Upstage
250B
15B active
601 GB
8× · 167 GB free
330 GB
4× · 54 GB free
192 GB
4× · 192 GB free
or 2× · 19% spare
Qwen3 235B-A22B
Alibaba
235B
22B active
564 GB
8× · 204 GB free
310 GB
4× · 74 GB free
181 GB
2× · 11 GB free
Laguna-S 2.1
Poolside
118B
8B active
282 GB
4× · 102 GB free
155 GB
2× · 37 GB free
90 GB
1× · 5.7 GB free
gpt-oss-120b
OpenAI
117B
5.1B active
Not released
Not released
78 GB
1× · 18 GB free
Qwen3.6 35B-A3B
Alibaba
35B
3B active
86 GB
1× · 9.7 GB free
47 GB
1× · 49 GB free
28 GB
1× · 68 GB free
Qwen3 32B
Alibaba
32.8B
79 GB
1× · 17 GB free
43 GB
1× · 53 GB free
25 GB
1× · 71 GB free
Gemma 4 31B
Google
31.3B
75 GB
1× · 21 GB free
41 GB
1× · 55 GB free
24 GB
1× · 72 GB free
GLM-4.7 Flash
Z.ai
31.2B
75 GB
1× · 21 GB free
41 GB
1× · 55 GB free
24 GB
1× · 72 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 RTX PRO 6000 cost per hour?
The RTX PRO 6000 starts at $0.50 per GPU-hour, with a median of $1.89 across 53 available configurations. Actual pricing depends on the provider, region, and whether you rent on-demand, spot or reserved.
Which cloud providers offer the RTX PRO 6000?
11 providers currently list the RTX PRO 6000: Sesterce Cloud, AM ThermaLink, Hyperstack, AceCloud, Omega Gradient, Latitude.sh and 5 more. Compare their hourly pricing, regions and machine specs in the table above.
How much VRAM does the RTX PRO 6000 have?
The RTX PRO 6000 comes with 96 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 RTX PRO 6000?
With 96 GB of VRAM, a single RTX PRO 6000 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 RTX PRO 6000 GPUs?
The largest models we track that fit across several RTX PRO 6000 cards are Kimi K2.5 on 8 GPUs at 4-bit, GLM-5.2 on 8 GPUs at 4-bit, DeepSeek R1 on 8 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 RTX PRO 6000 cheapest?
The lowest on-demand price we currently track for the RTX PRO 6000 is $0.50 per GPU-hour at Runpod. Because providers update pricing and availability frequently, check the live table above before you launch.