workstation
Louer Nvidia RTX A6000.
Ampere
48GB VRAM
300W
From $0.31/hr
Per hour
$0.31
Per day
$7.37
Per week
$51.56
Per month
$221
Provider spread
3 providers ·
up to 72% cheaper at the low end
Cheapest · $0.31/hr on RunPod
Median $0.34/hr
Most expensive · $1.09/hr on Lambda Labs
Price history
Daily median across providers.
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Where to rent it
All providers carrying this GPU.
Buy vs rent
Should you rent or own?
Your usage
Rent on cloud
Per day
—
Per month
—
at $0.31/hr cheapest provider rate
Own on-prem
Electricity per day
—
300W TDP
Rent breakeven on $6,000 MSRP
— days
· — months
Workloads
Suitable workloads.
FAQ
Frequently asked.
How is the Nvidia RTX A6000 price calculated?
We pull live listings from each provider's public API, take the median hourly rate across active offers, and refresh every hour. The rate shown is the median, so a single low-ball spot offer can't distort the headline.
Why does the Nvidia RTX A6000 cost different amounts on different providers?
P2P marketplaces like Vast.ai aggregate offers from individual hosts who set their own rates — bidding pushes prices down. First-party clouds (Lambda, hyperscalers) charge a managed-service premium for support, SLAs, and integrated networking. Decentralized networks (io.net, Akash) settle in tokens, which adds volatility but often the lowest base rate.
Can I really train an LLM on a single Nvidia RTX A6000?
Depends on the model size. With 48GB of VRAM you can fine-tune 13B–34B models with LoRA, or run inference on 70B models at int4 quantization.
Spot vs on-demand on the Nvidia RTX A6000 — which should I rent?
On-demand keeps the same instance until you stop it; spot (or interruptible) is cheaper but the host can reclaim it when a higher-paying job lands. Use on-demand for training runs and anything stateful. Use spot for stateless inference, batch jobs, and experiments where a checkpoint every few minutes is enough to recover.
How is hourly billing measured for the Nvidia RTX A6000?
Most providers bill per-second once the instance is running, with a small minimum (often 60 seconds). A handful of first-party clouds round up to the minute. Either way, headline $/hr is the right comparison unit.
Does the region of the host affect the Nvidia RTX A6000 price?
Yes — US and EU regions usually carry a premium over LATAM, India, and parts of APAC, especially on first-party clouds. P2P marketplaces hide this behind one global price because supply moves wherever bids exist.
AI models
FP16
FP16
FP16
INT8
INT4
FP16
INT8
Models that run on this GPU.
GPU-count + quantization recommendations covering fine-tuning, inference, and run-it-yourself scenarios on the Nvidia RTX A6000.
Gemma 3 27B
by Google DeepMind
Required GPUs
1× Nvidia RTX A6000
Total VRAM
48 GB
Parameters
27B (27B active)
Context
128K tokens
Llama 3.2 11B Vision
by Meta AI
Required GPUs
1× Nvidia RTX A6000
Total VRAM
48 GB
Parameters
11B
Context
128K tokens
Qwen 2.5 Coder 32B
by Alibaba (Qwen Team)
Required GPUs
1× Nvidia RTX A6000
Total VRAM
48 GB
Parameters
33B
Context
128K tokens
Qwen 2.5 72B
by Alibaba (Qwen Team)
Required GPUs
2× Nvidia RTX A6000
Total VRAM
96 GB
Parameters
73B
Context
128K tokens
DeepSeek R1 Distill Llama 70B
by DeepSeek
Required GPUs
1× Nvidia RTX A6000
Total VRAM
48 GB
Parameters
70B
Context
128K tokens
DeepSeek R1 Distill Qwen 32B
by DeepSeek
Required GPUs
1× Nvidia RTX A6000
Total VRAM
48 GB
Parameters
33B
Context
128K tokens
Llama 3.3 70B
by Meta AI
Required GPUs
2× Nvidia RTX A6000
Total VRAM
96 GB
Parameters
70B
Context
128K tokens
Renting for inference?
Pair these models with the cheapest provider on the rental table.
See rental rates on the Overview tab →
FAQ
AI models on this GPU.
How is the Nvidia RTX A6000 price calculated?
We pull live listings from each provider's public API, take the median hourly rate across active offers, and refresh every hour. The rate shown is the median, so a single low-ball spot offer can't distort the headline.
Why does the Nvidia RTX A6000 cost different amounts on different providers?
P2P marketplaces like Vast.ai aggregate offers from individual hosts who set their own rates — bidding pushes prices down. First-party clouds (Lambda, hyperscalers) charge a managed-service premium for support, SLAs, and integrated networking. Decentralized networks (io.net, Akash) settle in tokens, which adds volatility but often the lowest base rate.
Can I really train an LLM on a single Nvidia RTX A6000?
Depends on the model size. With 48GB of VRAM you can fine-tune 13B–34B models with LoRA, or run inference on 70B models at int4 quantization.
Spot vs on-demand on the Nvidia RTX A6000 — which should I rent?
On-demand keeps the same instance until you stop it; spot (or interruptible) is cheaper but the host can reclaim it when a higher-paying job lands. Use on-demand for training runs and anything stateful. Use spot for stateless inference, batch jobs, and experiments where a checkpoint every few minutes is enough to recover.
How is hourly billing measured for the Nvidia RTX A6000?
Most providers bill per-second once the instance is running, with a small minimum (often 60 seconds). A handful of first-party clouds round up to the minute. Either way, headline $/hr is the right comparison unit.
Does the region of the host affect the Nvidia RTX A6000 price?
Yes — US and EU regions usually carry a premium over LATAM, India, and parts of APAC, especially on first-party clouds. P2P marketplaces hide this behind one global price because supply moves wherever bids exist.