
We're pleased to announce that Vast.ai has successfully completed the SOC 2 Type I audit, a significant milestone as we continue to deliver secure and scalable GPU compute to a global user base.

Security remains central to everything we do here at Vast.ai. We've spent the past 6+ years delivering reliable service worldwide while meeting the [highest standards](https://vast.ai/article/security-and-compliance-at-vast-ai) of regulatory compliance. 

### Vast.ai’s Secure Cloud Offering

Our [Trust Center](https://trust.vast.ai/) includes additional information about our controls, compliance stance, FAQs and Subprocessors.

For customers with heightened security and compliance requirements, our [**Secure Cloud**](https://cloud.vast.ai/?secure_cloud=true) offering provides access to GPUs hosted exclusively by our certified datacenter partners. This environment already delivers an added layer of assurance – now further backed by an independent SOC 2 audit on our platform infrastructure.

Achieving **SOC 2 Type I certification** is a clear validation of the controls we've built to protect customer data and ensure the integrity of our infrastructure.

Here's a brief overview of SOC 2 Type I and what it entails.

### What Is SOC 2 Type I?

Put simply, SOC 2 (System and Organization Controls 2\) compliance assesses an organization's security measures. The audit determines whether internal controls are appropriately designed to meet [trust services criteria](https://www.aicpa-cima.com/topic/audit-assurance/audit-and-assurance-greater-than-soc-2) – covering areas like security, confidentiality, privacy, and processing integrity – in order to safeguard customer data.

Developed by the American Institute of Certified Public Accountants (AICPA), the SOC 2 Type I report is essentially a detailed snapshot evaluating the design and implementation of these controls at a specific point in time. Its goal is to ensure that security measures meet rigorous industry standards.

### Why This Matters

Our SOC 2 Type I certification affirms to our customers and partners that we've put strong, well-designed controls in place to protect their data and maintain operational reliability. We take data security seriously and follow industry-recognized best practices.

The Type I audit is only the first step in a broader compliance roadmap. We are currently preparing for the SOC 2 Type II audit, which evaluates how effectively internal controls perform over an extended period. That assessment will validate that we maintain our security practices consistently, both in design and in day-to-day execution.

We're also advancing our compliance efforts across other standards, to help us better serve organizations with strict regulatory requirements.

### Our Ongoing Commitment

Earning this SOC 2 Type I certification reflects our commitment to protecting the privacy and integrity of the data entrusted to us by developers, researchers, and organizations worldwide. As a distributed peer-to-peer platform powering global compute, we take our responsibility seriously. This certification is one step in our ongoing effort to provide users with infrastructure they can trust. 

For more about security and compliance at Vast.ai as well as our datacenter partners, please see our previous post [here](https://vast.ai/article/security-and-compliance-at-vast-ai). To request a copy of our SOC 2 report, feel free to contact us anytime at [compliance@vast.ai](mailto:compliance@vast.ai).

A huge thank-you to our team at Vast.ai and the audit partners who helped us reach this milestone\! 

We'll keep raising the bar – and keep you updated as we do.



Vast.ai has achieved SOC 2 Type I certification, reinforcing its commitment to data security and trusted infrastructure. Learn what this means for users and what’s next on their compliance roadmap.

Vast.ai Achieves SOC 2 Type I Certification


Google has recently released Gemma 3, their latest open-source language model family. The model, designed to run efficiently on a single GPU, brings state-of-the-art capabilities including advanced multimodal understanding, multilingual support, and an impressive 128K token context window. In this post, we'll explore the key features of Gemma 3 and demonstrate how to deploy it on Vast.ai to leverage one of its new features, comparing images.

## What makes Gemma 3 Special

Gemma 3 is available in four model sizes: 1B, 4B, 12B, and 27B parameters. Each size comes in both instruction-tuned (IT) and pre-trained (PT) variants, allowing developers to choose the optimal model for their specific applications.

What makes Gemma 3 particularly accessible is its efficient architecture - all models are optimized to run on a single GPU, with the smaller variants capable of running on consumer-grade GPUs through Vast.ai's platform.

Gemma 3 offers multiple state-of-the-art capabilities:

### 1. Enhanced Context Window

-   Supports up to 128K tokens context window
-   Improved long-range understanding and coherence
-   Better handling of complex, multi-turn conversations

### 2. Multi-Modal Capabilities

-   Native image understanding and analysis (available in 4B, 12B, and 27B models only)
-   Support for both text and image inputs in the same prompt
-   Advanced ability to analyze images, text, and short videos

### 3. Improved Performance

-   State-of-the-art performance for its size
-   Enhanced reasoning capabilities
-   Better code generation and understanding

### 4. Multilingual Support

-   Out-of-the-box support for over 35 languages
-   Pretrained support for over 140 languages

### 5. Additional Features

-   Function calling support for automated workflows
-   Official quantized versions for faster performance
-   Optimized for various hardware platforms (NVIDIA GPUs, Google Cloud TPUs, AMD GPUs)

## Using Gemma 3 For Image Comparison On Vast

Gemma 3 supports multimodal inputs, including an impressive image comparison capability. In this guide, we'll demonstrate this feature using images from the Open Image Preferences dataset, available [here](https://huggingface.co/datasets/data-is-better-together/open-image-preferences-v1-binarized).

### Image Selection

For this post, we've selected two contrasting astronaut images from the Open Image Preferences dataset:

<div style={{ display: "flex", gap: "20px", marginBottom: "2rem" }}>
    <div style={{ flex: 1 }}>
        <img
            src="/uploads/image-1.jpg"
            alt="Astronaut 1"
            style={{ width: "100%" }}
        />
        <p style={{ textAlign: "center", fontWeight: "bold" }}>Astronaut 1</p>
    </div>
    <div style={{ flex: 1 }}>
        <img
            src="/uploads/image-2.jpg"
            alt="Astronaut 2"
            style={{ width: "100%" }}
        />
        <p style={{ textAlign: "center", fontWeight: "bold" }}>Astronaut 2</p>
    </div>
</div>

### Launch an Instance

First, let's set up a Vast.ai instance with the necessary configurations to run Gemma 3:

```bash
vastai create instance $INSTANCE_ID \
    --image vllm/vllm-openai:latest \
    --disk 40 \
    --env '-p 8000:8000 -e HUGGING_FACE_HUB_TOKEN=hf-token' \
    --args --model google/gemma-3-4b-it --gpu-memory-utilization 0.9 --max-model-len 4096 --limit-mm-per-prompt "image=2"
```

### Call Gemma 3 Using the OpenAI SDK

Next, we'll write a script to call Gemma 3 on our instance. vLLM exposes an OpenAI-compatible API endpoint, allowing us to interact with Gemma 3 using the OpenAI SDK:

```python
from openai import OpenAI
import base64

# Your Vast.ai instance details
VAST_IP_ADDRESS = ""
VAST_PORT = ""

# Initialize the client
client = OpenAI(
    api_key="EMPTY",
    base_url=f"http://{VAST_IP_ADDRESS}:{VAST_PORT}/v1"
)

# Load and convert local images to base64
def image_to_base64(image_path):
    with open(image_path, "rb") as image_file:
        return base64.b64encode(image_file.read()).decode('utf-8')

# Convert images to base64
image1_base64 = image_to_base64("/path/to/image-1.jpg")
image2_base64 = image_to_base64("/path/to/image-2.jpg")

response = client.chat.completions.create(
    model="google/gemma-3-4b-it",
    messages=[
        {
            "role": "user",
            "content": [
                {
                    "type": "text",
                    "text": "Compare these two images"
                },
                {
                    "type": "image_url",
                    "image_url": {
                        "url": f"data:image/jpeg;base64,{image1_base64}"
                    }
                },
                {
                    "type": "image_url",
                    "image_url": {
                        "url": f"data:image/jpeg;base64,{image2_base64}"
                    }
                }
            ]
        }
    ]
)

print(response.choices[0].message.content)
```

Here is our output from Gemma 3:

```
Okay, let's compare these two images of astronauts. Here's a breakdown of the key differences and similarities:

**Similarities:**

* **Subject:** Both images feature a spacesuit and the astronaut's helmet.
* **Style:**  Both are highly stylized and appear to be digitally rendered images, likely created with a focus on aesthetic appeal and a sense of wonder. They evoke a futuristic and somewhat surreal feeling.
* **Helmet:** The overall shape and design of the helmet are fairly consistent between the two – a classic, bulbous, and slightly vintage-looking design.



**Differences:**

1. **Background:** This is the most significant difference.
   * **Image 1:** Features a vibrant, complex, and detailed space scene with a blue and gold starry sky, nebulas, and a visible horizon line suggesting a planet or moon. The background is rich in color and texture.
   * **Image 2:** Shows a much simpler and muted background. It’s a dusky blue sky with scattered stars and a faint suggestion of a horizon with mountains. There's no nebula or dramatic planetary features.

2. **Suit Detail & Appearance:**
    * **Image 1:** The spacesuit is more elaborate and brightly colored. It has intricate gold detailing on the arms and chest and a much more modern and polished look. It also appears to be a little more reflective.
    * **Image 2:** The suit is weathered and looks older. There's a visible rust and decay on the metal parts, suggesting it's been used and exposed to the elements. It’s a more rugged and worn appearance.

3. **Pose and Composition:**
   * **Image 1:** The astronaut is standing and facing slightly towards the camera, but the composition is broader, showing more of the suit and the expansive space.
   * **Image 2:** The astronaut is positioned at a three-quarter angle, focusing primarily on the helmet and upper body. The composition is more intimate and tightly framed.

4. **Lighting & Tone:**
   * **Image 1:**  The lighting is dramatic and highlights the spacesuit with warm, glowing lights. It's a brighter and more vibrant image overall.
   * **Image 2:** The lighting is softer and cooler, creating a more subdued and melancholic atmosphere.

**In essence:**

* **Image 1** is a grand, visually stunning depiction of an astronaut experiencing the majesty of space.
* **Image 2** is a more intimate and evocative portrayal, suggesting a sense of isolation, exploration, and the passage of time.



Would you like me to elaborate on any specific aspect of the comparison, such as the artistic style or the possible symbolism of the images?
```

### Image Comparison Analysis

The model provides detailed, structured analysis of the images, demonstrating its sophisticated visual understanding capabilities. The analysis includes:

1. **Comprehensive Comparison**: The model systematically breaks down both similarities and differences between the images
2. **Structured Output**: Results are organized into clear categories (Similarities, Differences, In essence)
3. **Detailed Observations**: The model captures both obvious and subtle details, from overall composition to specific visual elements
4. **Contextual Understanding**: The analysis includes interpretation of artistic style, mood, and potential symbolism
5. **Interactive Engagement**: The model offers to elaborate on specific aspects of the comparison

This level of analysis showcases Gemma 3's advanced multimodal capabilities, particularly its ability to:

-   Process and compare multiple images simultaneously
-   Provide nuanced visual analysis
-   Generate structured, coherent responses
-   Maintain context throughout the analysis

## Next Steps

The image comparison capabilities we've demonstrated can be applied to several real-world use cases:

-   **Visual Quality Control**: Compare product images for manufacturing defects
-   **Design Evolution**: Analyze changes between design iterations
-   **Medical Imaging**: Compare diagnostic images for changes or anomalies

### Beyond Image Analysis: Additional Capabilities

While image comparison showcases Gemma 3's visual understanding, the model's versatility extends far beyond visual tasks. Here are several other powerful applications you can build:

-   **Multilingual Chatbots**: Create AI assistants that can communicate in 140+ languages
-   **Document Analysis**: Leverage the 128K token context window for processing extensive documents
-   **Educational Tools**: Build interactive learning systems with multilingual support
-   **Visual Search**: Combine text and image understanding for sophisticated search applications

These applications can be deployed using the same Vast.ai infrastructure we've explored, allowing for efficient development and scaling.

## Conclusion

Gemma 3 represents a significant advancement in open-source AI models, offering state-of-the-art performance while being designed to run efficiently on a single GPU. Vast.ai's infrastructure provides an ideal platform for deploying Gemma 3 in production environments, making it accessible for both development and scaling applications.


Google’s open-source Gemma 3 model brings multimodal reasoning, 128K context, and multilingual support—all runnable on a single GPU. Deploy it on Vast.ai to compare images or build advanced AI apps.

Running Google's Gemma 3 on Vast.ai


A new NVIDIA Blackwell GPU with 96GB of VRAM? If rumors are to be believed, that could be exactly what's coming. 

A recent shipping manifest [revealed](https://wccftech.com/nvidia-rtx-pro-6000-x-blackwell-leak-96-gb-gddr7-600w/) an entry for the "**RTX PRO 6000 X Blackwell**," evidently being sent to India "for testing purposes." At least two different shippers have sent the GPUs for testing.

This isn't your typical consumer-grade gaming card, however. The as-yet-unannounced Blackwell-based GPU appears to be aimed at AI and data-intensive workloads. Here's what we know so far about this new entry in NVIDIA's professional lineup.

### NVIDIA RTX Pro 6000 X: What We Know So Far

With the impressive [RTX 5090](https://vast.ai/article/nvidia-geforce-rtx-5090-specs-everything-you-need-to-know) expected to remain at the top of the GeForce 50-series lineup, the professional segment is where we'll likely see ultra-high-end specs that push the limits on VRAM – and this latest shipping log discovery suggests that will be the case. 

According to reports, as mentioned, the RTX Pro 6000 X features a staggering **96GB of GDDR7 memory** on a 512-bit memory bus. That's significantly higher than even the most powerful gaming cards. For example, the RTX 5090 has 32GB of GDDR7 memory – which is more than enough for most purposes – but higher VRAM is obviously beneficial for workloads that require handling massive datasets, such as foundation AI model training and large-scale simulations.

The RTX Pro 6000 X also features a **GB202 die** and **600 watts** of total board power (TBP). This aligns with previous high-end Blackwell architecture designs, like the RTX 5090, which also has the GB202 die and comes in at 575 watts of TBP.

Interestingly, the discovery of the RTX Pro 6000 X on the shipping manifest follows an [earlier sighting](https://wccftech.com/nvidia-rtx-4090-with-96gb-vram-reportedly-exists/) of a 96GB RTX 4090 GPU – perhaps an engineering sample. While NVIDIA hasn't made any announcements, these repeated sightings nonetheless suggest a broader push for high-VRAM GPUs.

### Comparison to Existing RTX Workstation GPUs

We've seen professional-grade GPUs with massive VRAM configurations before, such as the RTX 6000 Ada with 48GB of memory, as well as the A100/A800 series. However, the RTX Pro 6000 X's 96GB of GDDR7 memory would make it one of the highest-capacity workstation GPUs to date. 

Assuming we see the RTX Pro 6000 X emerge, it would set a new benchmark for professional GPUs, doubling the memory of the RTX 6000 Ada while offering the faster speeds and efficiency of GDDR7 memory.

Plus, unlike the A100 and A800 series, which are designed primarily for data centers and enterprise AI workloads, the RTX Pro 6000 X could serve as a more flexible solution. Its ultra-high VRAM would allow professionals to work with larger datasets without necessarily relying on multi-GPU setups. 

### Looking Ahead

NVIDIA hasn't officially announced the RTX Pro 6000 X, so all information should be taken with a grain of salt, but the repeated mentions of this new GPU in shipping logs suggest that an announcement may be imminent. 

For Vast.ai users, this could mean more powerful GPU rental options in the near future. Stay tuned for more developments\! In the meantime, check out our current selection of high-performance GPUs available on Vast.ai for flexible and cost-effective access to cutting-edge hardware today.  

NVIDIA’s rumored RTX Pro 6000 X packs 96GB of GDDR7 VRAM, a GB202 die, and 600W TBP—ideal for AI, data science, and high-end workstation workloads.

NVIDIA RTX Pro 6000 X Rumors: Blackwell GPU with 96GB VRAM Spotted in Shipping Log

Pyannote Audio and NVIDIA’s Sortformer enhance Whisper’s speech recognition by adding speaker diarization. We’ll run them on VAST.ai to create speaker-attributed transcripts.

Implementing Speech-to-Text with Speaker Diarization: Comparing Pyannote and Sortformer on VAST.ai


The long-awaited NVIDIA GeForce RTX 5090 is here – but good luck getting your hands on one. From shipping delays to hardware defects, this GPU launch has been far from smooth.

Controversy aside, it's exciting to finally have confirmed performance details for this high-end graphics card. You can [try it now](https://cloud.vast.ai/?gpu_option=RTX%205090) for yourself on Vast.ai. Here's everything you need to know about the RTX 5090...

### RTX 5090: The Performance King?

As NVIDIA's new flagship GPU, the [RTX 5090](https://vast.ai/pricing/gpu/RTX-5090) is undoubtedly an impressive machine. Is it worth the $1999 price tag, though? That depends on more than just raw power – let's take a look.

#### Official Specs

For starters, here are some of the official specs for the RTX 5090:

-   **Architecture:** Powered by NVIDIA's cutting-edge Blackwell architecture.
-   **Gaming Chip:** Featuring the next-gen GB202 gaming chip.
-   **Memory:** 32GB of GDDR7 memory with a blazing-fast 1,792GB/sec bandwidth, supported by a super-wide 512-bit memory interface for even faster data transfer.
-   **CUDA Cores:** 21,760 cores, ideal for high-performance graphics and AI workloads.
-   **L2 Cache:** Expanded to 98MB, up from 73MB on the RTX 4090, improving memory efficiency and reducing latency.
-   **Display Support:** PCIe Gen 5 with DisplayPort 2.1b connectors supporting up to 8K at 165Hz.
-   **Power Requirements:** 575W total graphics power (TGP), with a 1000W power supply recommended for optimal performance.

Another bonus? The RTX 5090 has a redesigned **Founders Edition** with a two-slot design and a dual flow-through fan configuration – so it's compact enough for small form factor PCs, a remarkable shift from its predecessors.

For reference, here's a quick overview of the RTX 5090 specs:

| Spec                           | RTX 5090                       |
| :----------------------------- | :----------------------------- |
| **CUDA Cores**                 | 21,760                         |
| **Ray Tracing Cores**          | 170 (4th-gen)                  |
| **Tensor Cores**               | 680 (5th-gen)                  |
| **Base Clock**                 | 2,017 MHz                      |
| **Boost Clock**                | 2,407 MHz                      |
| **L2 Cache**                   | 98,304KB                       |
| **ROPs**                       | 176                            |
| **VRAM**                       | 32GB 28Gbps GDDR7              |
| **VRAM Interface**             | 512-bit                        |
| **Memory Bandwidth**           | 1,792 GB/s                     |
| **Interface**                  | 16x PCIe 5.0                   |
| **Power Connectors**           | 1 x 16-pin / 4 x 8-pin adapter |
| **Total Graphics Power (TGP)** | 575W                           |

(For more specifications – and to see how the RTX 5090 stacks up against its younger siblings in the RTX 50-series lineup as well as the RTX 4090 – check out the chart at the bottom of this page.)

#### AI and Professional Workloads

Beyond gaming, the RTX 5090 is well suited for high-performance AI and professional workloads. Its **680 Tensor cores** and **32GB of GDDR7** memory efficiently accelerate deep learning, 3D rendering, and other compute-intensive tasks. With **98MB of L2 cache** and a **512-bit memory interface**, the RTX 5090 delivers faster data access and reduced latency – crucial for AI training, scientific computing, and content creation.

The **5th-gen Tensor cores** boost AI inference efficiency in frameworks like TensorFlow and PyTorch, while **4th-gen RT cores** enhance real-time ray tracing for animation, visual effects, CAD work, and more.

For demanding AI and video workloads, the RTX 5090 more than meets the challenge. In Procyon's AI XL (FP16) test, the RTX 5090 was **40% faster** than the RTX 4090, and in PugetBench's DaVinci Resolve video processing test, it was **12% faster**.

However, cutting-edge performance doesn't necessarily mean a flawless launch\! Early adopters are already encountering serious issues in some cases.

#### Next-Gen Gaming Features

The biggest leap in technology for this GPU comes from DLSS 4's new **Multi Frame Generation**, an AI-driven frame interpolation technique exclusive to the RTX 50 series. It uses AI to generate up to three additional frames between traditionally rendered ones, significantly boosting frame rates with minimal visual artifacts.

Further, the RTX 5090 introduces a range of AI-driven enhancements in what's called **neural rendering**, designed to push in-game realism to new levels. **RTX Neural Shaders** improve texture compression and deliver film-quality lighting and shading in real time, while **RTX Neural Faces** uses generative AI to create lifelike skin, hair, and facial details.

Building on the power of DLSS 4, these neural rendering techniques integrate directly into the graphics pipeline, leveraging NVIDIA’s Tensor cores to enhance visual fidelity. Though game support is still in development, early demos – such as _Half-Life 2 RTX_ – [showcase](https://www.pcgamesn.com/nvidia/geforce-rtx-5090-review) the potential for deeper shadows, realistic translucency in materials, and an overall richer environment.

Another breakthrough is **Mega Geometry**, a feature that uses RT cores to significantly boost the number of triangles in ray-traced scenes. This allows game engines to maintain full geometric detail without sacrificing performance, resulting in more realistic object depth, shadows, and fine details.

The above features position the RTX 5090 as a powerhouse for next-generation gaming visuals... but there's a catch.

##### Caveat: Performance Claims vs. Real-World Results

The way that NVIDIA presents its performance numbers can be misleading. The company leans heavily on Multi Frame Generation-boosted FPS (frames per second) to compare these new GPUs against older ones.

Frame Generation and Multi Frame Generation (MFG) are powerful tools, but they aren't universal fixes. Their impact varies by game – some titles see massive FPS gains with little visual trade-off, while others may introduce artifacts or latency.

In addition, **not all games will support these features**, as DLSS adoption depends on individual developers. A GPU's raw performance still matters. MFG-inflated benchmarks can make performance gains seem more significant, but Frame Generation still needs a strong base frame rate to be effective. In CPU-limited games, or titles that don't support DLSS 4, the real-world performance gap may be far smaller.

Ultimately, while the RTX 5090 excels at AI-driven rendering, **real-world results will depend on game support and how well these features are implemented.**

### Early Defects and Controversies

#### Melting Power Connectors

Reports of **melted power connectors** on the RTX 5090 Founders Edition have [surfaced](https://www.theverge.com/news/609207/nvidia-rtx-5090-power-connector-melting-burning-issues). A number of users have experienced burnt plastic at both the GPU and PSU ends – with user error and third-party cables evidently not to blame.

NVIDIA introduced the updated 12V-2x6 power connector for the RTX 50 series following melting and overheating issues with the RTX 40-series GPUs. The new connector features shorter sensing pins and longer conductor terminals to improve connection reliability. Users can still use existing 12VHPWR cables with the RTX 50 series; however, the RTX 5090 can draw up to 575 watts of power – which is dangerously close to the cable's 600-watt rating.

PSU manufacturers have taken precautions, such as adding visual indicators to ensure a secure connection, but it remains unclear whether this fully resolves the risk of overheating. So far, NVIDIA has declined to comment on the reports.

#### Chip-Level Fault

One of the more unexpected issues plaguing the RTX 5090 launch is what's now being called the **"missing ROPs" defect.** NVIDIA has officially [confirmed](https://www.techradar.com/computing/gpu/some-lucky-rtx-5080-buyers-may-not-be-so-lucky-after-all-as-nvidia-confirms-rare-chip-fault-also-applies-to-this-gpu-as-well-as-the-rtx-5090-and-5070-ti) that a small number of RTX 5090, RTX 5090D, and RTX 5070 Ti cards were shipped with fewer ROPs (Render Output Units) than they should have. These ROPs are basically rendering pipelines for 3D graphics. Having fewer of them slows down PC gaming performance.

While this defect reportedly only impacts an estimated 0.5% of units (or around 1 in 200), affected cards have an average 4% drop in graphical performance. Since it's a hardware issue, it can't be fixed via BIOS or driver updates. However, it has no impact on AI and compute tasks, and NVIDIA has corrected the production anomaly while offering free replacements for affected cards.

Tools like GPU-Z can help verify whether your card has the correct number of ROPs; if fewer than 176, it should probably be replaced.

### Shipping Delays and Stock Shortages

Due to a combination of these production issues as well as high demand and supply chain challenges, the RTX 5090 is currently experiencing **significant shipping delays.** Availability is low and wait times are high. UK retailer Overclockers has been particularly transparent about lead times, [revealing](https://www.pcgamesn.com/nvidia/overclockers-stock-announcement) that it could take anywhere from 3-16 weeks for its customers to receive an RTX 5090 that they've already pre-ordered.

Most other retailers are facing similar challenges, with limited stock and long waitlists becoming prevalent. Speculation about imminent price hikes is already growing.

### Price Increase Rumors

It's no surprise that high demand and limited supply often lead to rising prices. With the RTX 5090, though, there may be another factor at play. DeepSeek's rapid rise in popularity has sparked a huge [surge](https://www.theinformation.com/articles/deepseek-spurs-black-market-demand-for-nvidia-gaming-chips-in-china) in demand for NVIDIA's gaming GPUs in China, as these cards can be repurposed to run DeepSeek's AI models – and provide a workaround for U.S. export restrictions on advanced GPUs.

(For more info on DeepSeek and how to run their LLM on our GPU cloud, see our previous post [here](https://vast.ai/article/deepseek-r1-open-source-disruptor-or-overhyped-upstart).)

With both gamers and AI developers vying for the same hardware, the strain on supply could push prices even higher in the near future. Some forecasts predict RTX 5090 prices could skyrocket to $5,000 or more.

### Final Thoughts: The Power of the RTX 5090 – Without the Hassle

Despite its hurdles, the RTX 5090 represents a major step forward in AI-driven graphics and cutting-edge performance, cementing its place as the most powerful consumer-grade GPU available today.

At the same time, it may only be worth purchasing if you really want the best of the best and you're willing to shell out for it. With a $1,999 price tag and relatively modest raw performance gains over the RTX 4090, the RTX 5090's true potential hinges on the wider adoption of Multi Frame Generation and neural rendering – features that, if fully embraced, could eventually make this flagship GPU a must-have for those willing to invest.

In the meantime, why wait? Skip the delays and high costs – [rent an RTX 5090](https://cloud.vast.ai/?gpu_option=RTX%205090) on Vast.ai for instant access to top-tier performance\! Given its limited availability on store shelves and its 575-watt power draw, our affordable rental options are the most practical way to access the RTX 5090's full potential without the upfront investment.

[Try it out](https://cloud.vast.ai/?gpu_option=RTX%205090) for yourself today\!

\*\*\*\*\*\*\*\*\*\*

#### Additional Specifications:

| Spec                                |   RTX 5090    |   RTX 5080    |  RTX 5070 Ti  |   RTX 5070   |    RTX 4090    |
| :---------------------------------- | :-----------: | :-----------: | :-----------: | :----------: | :------------: |
| **Architecture**                    |     GB202     |     GB203     |     GB203     |    GB205     |     AD102      |
| **VRAM**                            |  32GB GDDR7   |  16GB GDDR7   |  16GB GDDR7   |  12GB GDDR7  |  24GB GDDR6X   |
| **VRAM Speed**                      |    28Gbps     |    30Gbps     |    28Gbps     |    28Gbps    |     21Gbps     |
| **VRAM Bus Width**                  |      512      |      256      |      256      |     192      |      384       |
| **Bandwidth**                       |   1792GB/s    |    960GB/s    |    896GB/s    |   672GB/s    |    1.01TB/s    |
| **Streaming Multiprocessors (SMs)** |      170      |      84       |      70       |      48      |                |
| **Tensor Cores**                    |      680      |      336      |      280      |     192      |      512       |
| **Ray Tracing Cores**               |      170      |      84       |      70       |      48      |      128       |
| **Boost Clock**                     |   2407 MHz    |   2617 MHz    |   2452 MHz    |   2512 MHz   |    2520 MHz    |
| **Total Graphics Power (TGP)**      |     575W      |     360W      |     300W      |     250W     |      450W      |
| **Recommended Power Supply**        |     1000W     |     850W      |     750W      |     650W     |      850W      |
| **Launch Date**                     | Jan. 30, 2025 | Jan. 30, 2025 | Feb. 20, 2025 | Mar. 5, 2025 | Sept. 20, 2022 |
| **Launch Price**                    |    $1,999     |     $999      |     $749      |     $549     |     $1,599     |


NVIDIA’s RTX 5090 delivers cutting-edge AI and gaming performance, but launch issues, high costs, and stock shortages make it hard to get. Try it now on Vast.ai!

Vast.ai

Vast.ai Achieves SOC 2 Type I Certification

Running Google's Gemma 3 on Vast.ai

NVIDIA RTX Pro 6000 X Rumors: Blackwell GPU with 96GB VRAM Spotted in Shipping Log

Implementing Speech-to-Text with Speaker Diarization: Comparing Pyannote and Sortformer on VAST.ai

NVIDIA GeForce RTX 5090 Specs: Everything You Need to Know