Budget Ada Lovelace GPU for local AI work and gaming.
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 4070 Ti has 12 GB of VRAM. In practice, that's enough memory for roughly 9B 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 4070 Tis needed | Cost /hr | Cost /mo |
|---|---|---|---|---|
Qwen3.8-27B
27B
|
18 GB
|
2
|
–
|
–
|
Gemma 4 31B
30.7B
|
22 GB
|
2
|
–
|
–
|
GPT-OSS-120B
117B · 5.1B active
|
67 GB
|
7
|
–
|
–
|
GLM-5.3-Flash
320B · 18B active
|
178 GB
|
17
|
–
|
–
|
MiniMax-M3
428B · 23B active
|
239 GB
|
23
|
–
|
–
|
DeepSeek V4.1 Flash
552B · 16B active
|
306 GB
|
29
|
–
|
–
|
Kimi K3
2.8T · 104B active
|
1,544 GB
|
143
|
–
|
–
|
Estimates based on the median on-demand rate. Memory is weights plus FP8 KV cache at 32K context per request (FP16/BF16 in the 16-bit column). 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 4070 Ti · Per GPU
| Compute · dense | |
|---|---|
| FP8 | 160.4 TFLOPS 320.7 with sparsity |
| FP16 / BF16 | 80.2 TFLOPS 160.4 with sparsity |
| INT8 | 320.7 TOPS 641.4 with sparsity |
| FP32 | 40.1 TFLOPS |
| Precision support | FP8FP16BF16TF32FP32INT4INT8 |
| Memory | |
|---|---|
| Capacity | 12 GB GDDR6X |
| Bandwidth | 504 GB/s |
| Bus width | 192-bit |
| ECC | No |
| Silicon | |
|---|---|
| Architecture | Ada Lovelace |
| Process | TSMC 4N |
| Transistors | 35.8 billion |
| Shader cores | 7,680 CUDA cores |
| Matrix cores | 240 Tensor cores |
| Compute units | 60 SMs |
| Fabric and host | |
|---|---|
| Host interface | PCIe 4.0 |
| Power | |
|---|---|
| Board power | 285 W |
| Cooling | Active |
As of October 3, 2026, we track 5 configs from 3 providers. Prices are per GPU per hour.
| Billing type | Configs | Cheapest |
|---|---|---|
On-demand | 4 | $0.14 (in stock, Vast.ai) |
Spot | 1 | $0.08 |
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 on-demand RTX 4070 Ti tracked by GetDeploying is $0.14 per GPU per hour from Vast.ai.
The cheapest verified in-stock estimate is $101 per month on-demand.
GetDeploying currently tracks RTX 4070 Ti configs from 3 providers. Vast.ai and Salad have verified in-stock on-demand configs. See the full price comparison above for every provider and config.
One RTX 4070 Ti runs models up to roughly 9B 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 GDDR6X with Ada Lovelace FP8 Tensor Cores. Budget Ada option for local AI work and gaming.
Only 12GB VRAM. Subject to Nvidia's consumer EULA, which may restrict data center use.
Nvidia RTX 5070 Ti
16 GB GDDR7 · 78% more bandwidth than the RTX 4070 Ti
Nvidia RTX 4070
12 GB GDDR6X · released Q2 2023
Last updated