Vast.ai
Our sponsor- On-Demand
- from $0.39
- Reserved
- from $0.26
- Spot
- from $0.13
Professional workstation GPU for AI development and CAD.
Weekly median price per GPU per hour · Get the data
By provider shows one card per company, placed where its best offer ranked. By configuration lists every offer.
What you can rent comes first: in stock, then waitlist, then not reported, then out of stock. Priced offers rank ahead of quote-only, and on-demand ahead of other billing types.
Within a group, five factors set the order:
We match the provider, its country, GPU model, form factor, billing type, availability and instance name. Matching is partial and case-insensitive. Everyday words work too, so "interruptible" finds spot and "sold out" finds out of stock.
No providers match .
Heads up: A provider's own page may quote a different figure, for example on tax, region or a promotion. A monthly-only plan shows a derived hourly rate. Verify before provisioning. More on how we price.
One RTX A6000 has 48 GB of VRAM. In practice, that's enough memory for roughly 60B parameters at 4-bit or 17B at 16-bit, assuming a 32K context. Below are some open-weight LLMs, with the estimated memory and GPUs each one needs.
| Model | Memory (INT4 / FP4) | RTX A6000s needed | Cost /hr | Cost /mo |
|---|---|---|---|---|
|
|
19 GB
|
1
|
$0.56
|
$403
|
|
|
24 GB
|
1
|
$0.56
|
$403
|
|
|
68 GB
|
2
|
$1.12
|
$806
|
|
|
178 GB
|
8
|
$4.48
|
$3,226
|
|
|
241 GB
|
8
|
$4.48
|
$3,226
|
|
|
306 GB
|
8
|
$4.48
|
$3,226
|
|
|
1,545 GB
|
36
|
–
|
–
|
Estimates based on the median on-demand rate. Memory is weights plus FP16/BF16 KV cache at 32K context per request. GPU counts assume 90% of advertised VRAM is usable. No guarantee of runtime support, usable performance, or that a matching quantized build exists. Pricing methodology.
Nvidia RTX A6000 · Per GPU
| Compute · dense | |
|---|---|
| FP16 / BF16 | 154.8 TFLOPS 309.6 with sparsity |
| INT8 | 309.7 TOPS 619.4 with sparsity |
| FP32 | 38.7 TFLOPS |
| Precision support | FP16BF16TF32FP32INT4INT8 |
| Memory | |
|---|---|
| Capacity | 48 GB GDDR6 |
| Bandwidth | 768 GB/s |
| Bus width | 384-bit |
| ECC | Yes |
| Silicon | |
|---|---|
| Architecture | Ampere |
| Process | Samsung 8N |
| Transistors | 28.3 billion |
| Shader cores | 10,752 CUDA cores |
| Matrix cores | 336 Tensor cores |
| Compute units | 84 SMs |
| Fabric and host | |
|---|---|
| GPU interconnect | NVLink 112 GB/s |
| Host interface | PCIe 4.0 x16 |
| Power | |
|---|---|
| Board power | 300 W |
| Cooling | Active |
Source: official Nvidia RTX A6000 datasheet.
As of October 2, 2026, the median on-demand price is $0.56 per GPU per hour across 16 providers with a priced on-demand config.
| Billing type | Configs | Median /GPU/hr | Cheapest |
|---|---|---|---|
On-demand | 91 | $0.56 | $0.35 (in stock, Thunder Compute) |
Reserved | 86 | $0.48 | $0.26 (6 mo, in stock, Vast.ai) |
Spot | 26 | $0.13 (in stock, Vast.ai) |
No median for spot: we only show this when at least 3 providers list the GPU on that billing type.
The cheapest verified in-stock on-demand RTX A6000 tracked by GetDeploying is $0.35 per GPU per hour from Thunder Compute. Cheapest verified in stock on other billing types: reserved $0.26 (6 mo) and spot $0.13, both from Vast.ai.
At 720 hours per month, one RTX A6000 costs an estimated $403 at the median on-demand price. Cheapest verified in stock: $252 per month on-demand, $187 reserved (6 mo), $94 spot.
GetDeploying currently tracks RTX A6000 configs from 21 providers. The cheapest verified in-stock on-demand configs come from Thunder Compute, Vast.ai, GPU.ai and Spheron. See the full price comparison above for every provider and config.
As of October 2, 2026, the median on-demand price has been flat over the past 90 days, at about $0.56 per GPU per hour.
One RTX A6000 runs models up to roughly 60B parameters at 4-bit quantization or 17B at 16-bit, assuming a 32K context. Larger models run across multiple GPUs: the model table above shows the estimated memory and GPU count for popular open-weight LLMs.
48GB GDDR6 with NVLink (112 GB/s). Professional-grade with ECC memory and ISV certifications. Strong for both AI development and CAD/visualization workloads.
Priced as a professional workstation GPU. For pure AI inference, the L40S offers similar VRAM with better FP8 performance at lower cost.
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