USA
4 configs
1x
Nvidia P1000
Compact Pascal card for multi-display setups.
- Arch
- Pascal
- Memory
- 4 GB GDDR5
- Bandwidth
- 82 GB/s
- Released
- Q1 2017
Price history
Weekly median price per GPU per hour
Aggregating historical prices...
At a glance Updated 6 hours ago
- Cheapest in stock
- --
- Median price (current)
- --
- 90-day trend
- --
- Coverage
- 1 provider
- 4 price points
Pricing & availability
How this list works
The two views
By provider shows one card per company, placed where its best offer ranked. By configuration lists every offer.
Order
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:
- Location: datacenter proximity, blended with provider HQ.
- Price: hourly price, per GPU and in total.
- Billing type: reserved ahead of spot, spot ahead of quote-only.
- Specs: more VRAM, vCPUs and RAM.
- Provider diversity: a provider's repeat rows rank slightly lower, so one company can't take all the top spots.
Search
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.
Transparency and funding
- Ads and sponsors: Paid placements sit at the top of the list and are always labeled as sponsored content. Sponsorship never influences the organic ranking itself.
- Affiliates: Affiliate links are marked. We may earn a commission if you click them, but commissions never affect the order.
- Prices: Shown in USD, converted at daily reference rates where a provider publishes in another currency. A month means 720 hours. How we estimate costs.
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.
What can the P1000 run?
One P1000 has 4 GB of VRAM. Even at 4-bit, the weights of most modern AI models exceed the card's usable VRAM, and context adds KV cache on top. Below are some open-weight LLMs, with the estimated memory and GPUs each one needs.
Multi-node
| Model | Memory (INT4 / FP4) | P1000s needed | Cost /hr | Cost /mo |
|---|---|---|---|---|
Qwen3.8-27B
27B
|
19 GB
|
6
|
–
|
–
|
Gemma 4 31B
30.7B
|
24 GB
|
7
|
–
|
–
|
GPT-OSS-120B
117B · 5.1B active
|
68 GB
|
19
|
–
|
–
|
GLM-5.3-Flash
320B · 18B active
|
178 GB
|
50
|
–
|
–
|
MiniMax-M3
428B · 23B active
|
241 GB
|
68
|
–
|
–
|
DeepSeek V4.1 Flash
552B · 16B active
|
306 GB
|
85
|
–
|
–
|
Kimi K3
2.8T · 104B active
|
1,545 GB
|
430
|
–
|
–
|
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.
Technical Specifications
Nvidia P1000 · Per GPU
| Compute · dense | |
|---|---|
| FP32 | 1.8 TFLOPS |
| Precision support | FP16FP32 |
| Memory | |
|---|---|
| Capacity | 4 GB GDDR5 |
| Bandwidth | 82 GB/s |
| Bus width | 128-bit |
| ECC | No |
| Silicon | |
|---|---|
| Architecture | Pascal |
| Process | Samsung 14nm LPP |
| Transistors | 3.3 billion |
| Shader cores | 640 CUDA cores |
| Compute units | 5 SMs |
| Fabric and host | |
|---|---|
| Host interface | PCIe 3.0 x16 |
| Power | |
|---|---|
| Board power | 47 W |
| Cooling | Active |
Source: official Nvidia P1000 datasheet.
Frequently Asked Questions
How much does the P1000 cost per hour?
As of September 14, 2026, we track 4 configs from 1 provider, none of them on demand. Prices are per GPU per hour.
| Billing type | Configs | Cheapest |
|---|---|---|
Reserved | 4 | $0.05 (24 mo) |
No median for reserved: we only show this when at least 3 providers list the GPU on that billing type.
Where can I rent a P1000?
GetDeploying currently tracks P1000 configs from 1 provider. See the full price comparison above for every provider and config.
How many P1000 GPUs do I need?
More than one: even at 4-bit, the weights of most modern AI models exceed one P1000's usable VRAM, and context adds KV cache on top. Larger models run across multiple GPUs: the model table above shows the estimated memory and GPU count for popular open-weight LLMs.
Why choose the P1000?
4GB GDDR5. Compact Pascal professional GPU for basic display and light visualization.
When is the P1000 not a good fit?
Only 4GB VRAM and limited compute. Only useful for multi-display setups or basic visualization.
Alternatives to Nvidia P1000
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