Low-profile workstation GPU for basic visualization and light compute.
Weekly median price per GPU per hour
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.
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 A2000 has 12 GB of VRAM. In practice, that's enough memory for roughly 1B parameters at 4-bit or 0.4B 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 A2000s needed | Cost /hr | Cost /mo |
|---|---|---|---|---|
Qwen3.8-27B
27B
|
19 GB
|
2
|
–
|
–
|
Gemma 4 31B
30.7B
|
24 GB
|
3
|
–
|
–
|
GPT-OSS-120B
117B · 5.1B active
|
68 GB
|
7
|
–
|
–
|
GLM-5.3-Flash
320B · 18B active
|
178 GB
|
17
|
–
|
–
|
MiniMax-M3
428B · 23B active
|
241 GB
|
23
|
–
|
–
|
DeepSeek V4.1 Flash
552B · 16B active
|
306 GB
|
29
|
–
|
–
|
Kimi K3
2.8T · 104B active
|
1,545 GB
|
144
|
–
|
–
|
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. How we estimate costs.
Nvidia RTX A2000 · Per GPU
| Compute · dense | |
|---|---|
| FP16 / BF16 | 31.9 TFLOPS 63.9 with sparsity |
| FP32 | 8 TFLOPS |
| Precision support | FP16BF16TF32FP32INT4INT8 |
| Memory | |
|---|---|
| Capacity | 12 GB GDDR6 |
| Bandwidth | 288 GB/s |
| Bus width | 192-bit |
| ECC | Yes |
| Silicon | |
|---|---|
| Architecture | Ampere |
| Shader cores | 3,328 CUDA cores |
| Matrix cores | 104 Tensor cores |
| Compute units | 26 SMs |
| Fabric and host | |
|---|---|
| Host interface | PCIe 4.0 x16 |
| Power | |
|---|---|
| Board power | 70 W |
| Cooling | Active |
Source: official Nvidia RTX A2000 datasheet.
As of September 13, 2026, we track 7 configs from 2 providers. Prices are per GPU per hour.
| Billing type | Configs | Cheapest |
|---|---|---|
On-demand | 5 | $0.05 (in stock, Vast.ai) |
Spot | 2 | $0.03 (in stock, Vast.ai) |
No median for on-demand and spot: we only show this when at least 3 providers list the GPU on that billing type.
The cheapest verified in-stock estimate is $36 per month on-demand, $22 spot.
GetDeploying currently tracks RTX A2000 configs from 2 providers. Vast.ai has verified in-stock on-demand configs. See the full price comparison above for every provider and config.
One RTX A2000 runs models up to roughly 1B parameters at 4-bit quantization or 0.4B 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.
12GB or 6GB GDDR6, compact low-profile professional GPU. Low power draw. Entry-level option for basic GPU tasks and light AI experimentation.
Very limited compute and VRAM for AI workloads. Best kept to basic visualization, light prototyping, and display tasks.
Last updated
