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NVIDIA RTX 6000

24 GB VRAM295 W TDP1 providers3 offerings2 regions

The NVIDIA RTX 6000 is an enterprise-class GPU built on the Turing architecture, featuring 24 GB of memory with 624 GB/s of memory bandwidth and a 295 W TDP. It delivers 16.3 TFLOPS of FP32 performance. Currently available from 1 provider starting at $0.13/GPU/hour, with a market median of $0.13/GPU/hour across 3 configurations.

Cheapest
$0.130/hr
Vast.ai
Median
$0.130/hr
across 3 offerings
Most expensive
$0.150/hr
Vast.ai
90-day trend
-77.6%
median rate

Hardware specifications

Same across all providers

TDP
295 W
Memory bandwidth
624 GB/s
Architecture
Turing
FP32 performance
16.3 TFLOPS
Brand
NVIDIA
Series
RTX
Market price history

Median price across all providers

Prices updated 55 minutes ago

3 offerings from 1 providers

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

ProviderCountvCPURAMRegionPer GPU hourTotal/hrAction
Vast.ai logoVast.aiReferral linkTrendingCheapest
×22294 GB
United StatesSouth Korea
From$0.130
0.0% 30d
From$0.26
Launch
×11446 GB--
$0.690
$0.69
Sesterce Cloud logoSesterce CloudReferral link
×11446 GB--
$0.759
$0.76

LLMs that fit on the NVIDIA RTX 6000

Estimated VRAM for popular open-weight LLMs at 16-bit (FP16/BF16), 8-bit (FP8/INT8) and 4-bit (INT4/MXFP4) precision, against 24 GB per GPU. Showing the 12 largest that fit.

ModelParameters16-bit8-bit4-bit
Laguna-S 2.1
Poolside
118B
8B active
282 GB
Too large
155 GB
Too large
90 GB
4× · 5.7 GB free
gpt-oss-120b
OpenAI
117B
5.1B active
Not released
Not released
78 GB
4× · 18 GB free
Qwen3.6 35B-A3B
Alibaba
35B
3B active
86 GB
4× · 9.7 GB free
47 GB
Barely fits on 2×
28 GB
2× · 20 GB free
or 1× · 4% spare
Qwen3 32B
Alibaba
32.8B
79 GB
4× · 17 GB free
43 GB
2× · 4.8 GB free
25 GB
2× · 23 GB free
or 1× · 14% spare
Gemma 4 31B
Google
31.3B
75 GB
4× · 21 GB free
41 GB
2× · 6.7 GB free
24 GB
2× · 24 GB free
or 1× · 19% spare
GLM-4.7 Flash
Z.ai
31.2B
75 GB
4× · 21 GB free
41 GB
2× · 6.8 GB free
24 GB
Barely fits on 1×
Qwen3.6 27B
Alibaba
27.8B
67 GB
4× · 29 GB free
37 GB
2× · 11 GB free
21 GB
1× · 2.7 GB free
Mistral Small 3.2 24B
Mistral AI
24B
58 GB
4× · 38 GB free
32 GB
2× · 16 GB free
18 GB
1× · 5.6 GB free
gpt-oss-20b
OpenAI
21B
3.6B active
Not released
Not released
17 GB
1× · 7.5 GB free
Gemma 3 12B
Google
12.2B
29 GB
2× · 19 GB free
16 GB
1× · 7.9 GB free
9.4 GB
1× · 15 GB free
Granite 4.1 8B
IBM
8.8B
21 GB
1× · 2.9 GB free
12 GB
1× · 12 GB free
6.8 GB
1× · 17 GB free
Qwen3 8B
Alibaba
8.2B
20 GB
1× · 4.3 GB free
11 GB
1× · 13 GB free
6.3 GB
1× · 18 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 6000 cost per hour?
The RTX 6000 starts at $0.13 per GPU-hour, with a median of $0.13 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 RTX 6000?
3 providers currently list the RTX 6000: Sesterce Cloud, Lambda, Vast.ai. Compare their hourly pricing, regions and machine specs in the table above.
How much VRAM does the RTX 6000 have?
The RTX 6000 comes with 24 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 6000?
With 24 GB of VRAM, a single RTX 6000 can serve models such as GLM-4.7 Flash, Qwen3.6 27B, Mistral Small 3.2 24B, gpt-oss-20b. 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 6000 GPUs?
The largest models we track that fit across several RTX 6000 cards are Laguna-S 2.1 on 4 GPUs at 4-bit, gpt-oss-120b on 4 GPUs at 4-bit, Qwen3.6 35B-A3B on 2 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 RTX 6000 cheapest?
The lowest on-demand price we currently track for the RTX 6000 is $0.13 per GPU-hour at Vast.ai. Because providers update pricing and availability frequently, check the live table above before you launch.