here is the comparison of two GPU’s, your advice? ×GeForce RTX 3080 Ti ×GeForce RTX 4070 Ti SUPER + ADD
Price $1368.96 BUY NOW! $799.99 BUY NOW!
Bus Interface PCIe 4.0 x16 NA2
GPU Class Desktop NA2
Core Clock 1370 MHz NA2
Memory Clock NA2 NA2
Maximum Memory Supported 12288 MB NA2
DirectX 12.0 NA2
OpenGL 4.6 NA2
Max TDP 350W NA2
First Seen on Chart Q2 2021 Q1 2024
# of Samples 8447 148
Average Results (% diff. to max in group)
DirectX 9 272 FPS (-22.2%) 349 FPS
DirectX 10 192 FPS 184 FPS (-4.5%)
DirectX 11 226 FPS (-19.8%) 282 FPS
DirectX 12 111 FPS (-7.4%) 120 FPS
GPU Compute 16233 Ops/Sec (-15.8%) 19269 Ops/Sec
G2D Rating 1095 (-6.1%) 1165
G3D Rating 27280
(-14.8%) 32018
Based on the provided information, here is a concise comparison of the GeForce RTX 3080 Ti and the GeForce RTX 4070 Ti SUPER:
1. **Price:**
– GeForce RTX 3080 Ti: $1368.96
– GeForce RTX 4070 Ti SUPER: $799.99
*Advice:* The GeForce RTX 4070 Ti SUPER is significantly more affordable.
2. **Bus Interface:**
– GeForce RTX 3080 Ti: PCIe 4.0 x16
– GeForce RTX 4070 Ti SUPER: Not specified (NA2)
*Advice:* The GeForce RTX 3080 Ti has a defined PCIe interface, while the RTX 4070 Ti SUPER information is not provided.
3. **GPU Class:**
– GeForce RTX 3080 Ti: Desktop
– GeForce RTX 4070 Ti SUPER: Not specified (NA2)
*Advice:* The GeForce RTX 3080 Ti is designed for desktop use, but information is lacking for the RTX 4070 Ti SUPER.
4. **Core Clock:**
– GeForce RTX 3080 Ti: 1370 MHz
– GeForce RTX 4070 Ti SUPER: Not specified (NA2)
*Advice:* The core clock information for the RTX 4070 Ti SUPER is missing.
5. **Memory:**
– GeForce RTX 3080 Ti: Maximum Memory Supported 12288 MB
– GeForce RTX 4070 Ti SUPER: Not specified (NA2)
*Advice:* The RTX 3080 Ti has a defined maximum memory capacity, while the RTX 4070 Ti SUPER information is not provided.
6. **Performance:**
– GeForce RTX 3080 Ti has better average results in various DirectX versions and GPU compute tasks.
– GeForce RTX 4070 Ti SUPER has higher G2D and G3D ratings.
*Advice:* Consider the specific tasks you’ll be using the GPU for; the RTX 3080 Ti seems to have better DirectX and compute performance, while the RTX 4070 Ti SUPER excels in G2D and G3D ratings.
7. **Power Consumption (Max TDP):**
– GeForce RTX 3080 Ti: 350W
– GeForce RTX 4070 Ti SUPER: Not specified (NA2)
*Advice:* The RTX 3080 Ti has a higher TDP, which might impact power consumption and cooling requirements.
8. **Availability:**
– GeForce RTX 3080 Ti: First Seen on Chart Q2 2021
– GeForce RTX 4070 Ti SUPER: First Seen on Chart Q1 2024
*Advice:* The RTX 3080 Ti has been available since Q2 2021, while the RTX 4070 Ti SUPER is a newer release.
In summary, the choice between the two GPUs depends on your budget, specific use case, and the availability of detailed specifications for the RTX 4070 Ti SUPER. If the missing information is critical for your decision, you may need to wait for more details to be released.
The MSI GeForce RTX 4070 Ti VENTUS 3X OC 12G graphics card has a 2640 MHz gaming boost clock, a 2655 MHz extreme performance clock, 12 GB of GDDR6X memory, and a 192-bit memory interface. It also has a 21 Gb/s memory speed, 1 x HDMI 2.1, and 3 x DisplayPort 1.4a. It supports OpenGL 4.6 and DirectX 1
Thank you for providing additional information about the MSI GeForce RTX 4070 Ti VENTUS 3X OC 12G graphics card. Here’s a concise summary of its key specifications:
1. **Core Clocks:**
– Gaming Boost Clock: 2640 MHz
– Extreme Performance Clock: 2655 MHz
2. **Memory:**
– 12 GB GDDR6X
– 192-bit memory interface
– Memory Speed: 21 Gb/s
3. **Video Outputs:**
– 1 x HDMI 2.1
– 3 x DisplayPort 1.4a
4. **API Support:**
– OpenGL 4.6
– DirectX 12
This card seems to offer high clock speeds for gaming and extreme performance, along with a decent amount of GDDR6X memory and a modern set of video outputs. It supports the latest versions of OpenGL and DirectX, ensuring compatibility with modern games and applications.
Please note that the choice of a graphics card also depends on factors like pricing, availability, and your specific use case. If this card meets your requirements and fits your budget, it could be a good choice for gaming and other graphics-intensive tasks. Keep in mind to check for reviews and benchmarks to ensure it aligns with your performance expectations.
now compare to the 3080ti
Certainly, let’s compare the MSI GeForce RTX 4070 Ti VENTUS 3X OC 12G to the GeForce RTX 3080 Ti:
**MSI GeForce RTX 4070 Ti VENTUS 3X OC 12G:**
– Gaming Boost Clock: 2640 MHz
– Extreme Performance Clock: 2655 MHz
– Memory: 12 GB GDDR6X, 192-bit memory interface, 21 Gb/s memory speed
– Video Outputs: 1 x HDMI 2.1, 3 x DisplayPort 1.4a
– API Support: OpenGL 4.6, DirectX 12
**GeForce RTX 3080 Ti (Generic):**
– Core Clock: 1370 MHz (typical base clock)
– Memory: 12 GB GDDR6X, 384-bit memory interface, 19 Gb/s memory speed
– Video Outputs: Typically 1 x HDMI 2.1, 3 x DisplayPort 1.4a
– API Support: DirectX 12, OpenGL 4.6
**Comparison:**
1. **Clock Speeds:**
– The RTX 4070 Ti has higher gaming boost and extreme performance clocks compared to the typical base clock of the RTX 3080 Ti.
2. **Memory Interface and Speed:**
– The RTX 4070 Ti has a 192-bit memory interface with a faster 21 Gb/s memory speed, whereas the RTX 3080 Ti has a wider 384-bit memory interface but a slightly slower 19 Gb/s memory speed.
3. **Video Outputs:**
– Both cards have similar video output configurations, with HDMI 2.1 and DisplayPort 1.4a support.
4. **API Support:**
– Both cards support DirectX 12 and OpenGL 4.6.
5. **Other Factors:**
– Detailed TDP (Power Consumption) information for the RTX 4070 Ti is not provided in the current information, whereas the RTX 3080 Ti has a TDP of 350W.
**Considerations:**
– The RTX 4070 Ti has higher clock speeds and a more compact memory interface but lacks information on power consumption.
– The RTX 3080 Ti has a wider memory interface, but with slightly lower memory speed, and is known to have a TDP of 350W.
**Conclusion:**
– Depending on the specific use case, preferences, and pricing, either card could be a viable option. The RTX 4070 Ti may offer a performance advantage in certain scenarios with its higher clock speeds, while the RTX 3080 Ti provides a balance with its wider memory interface. Consider your specific needs, such as gaming, content creation, or professional applications, when making a decision. Additionally, check for real-world benchmarks and reviews for a more accurate performance assessment.
I am interested only in inference
For inference-focused tasks, such as machine learning inference or running pre-trained models for AI applications, the key factors to consider are generally the GPU’s compute capabilities, memory capacity, and memory bandwidth. Let’s evaluate the inference-related aspects of the MSI GeForce RTX 4070 Ti VENTUS 3X OC 12G and the generic GeForce RTX 3080 Ti:
**MSI GeForce RTX 4070 Ti VENTUS 3X OC 12G:**
– GPU Compute: Information not provided
– Memory: 12 GB GDDR6X, 192-bit memory interface, 21 Gb/s memory speed
**GeForce RTX 3080 Ti (Generic):**
– GPU Compute: Information not provided (Note: Check specific compute benchmarks for accurate information)
– Memory: 12 GB GDDR6X, 384-bit memory interface, 19 Gb/s memory speed
**Considerations:**
1. **Memory Interface and Speed:**
– The RTX 4070 Ti has a narrower 192-bit memory interface but a faster 21 Gb/s memory speed.
– The RTX 3080 Ti has a wider 384-bit memory interface but a slightly slower 19 Gb/s memory speed.
2. **GPU Compute:**
– Unfortunately, specific GPU compute benchmarks or information are not provided for either card. This data is crucial for understanding the cards’ capabilities in inference tasks.
**Advice:**
– In the absence of specific GPU compute information, it’s recommended to look for benchmark results or reviews that focus on inference performance for each card.
– Consider the memory bandwidth and capacity, as these aspects are essential for handling large datasets in inference tasks.
**Conclusion:**
– Both GPUs can handle inference tasks, but specific benchmarks and reviews focused on inference workloads would provide a clearer understanding of their performance. Look for reliable sources that provide insights into the cards’ performance in the specific inference tasks you are interested in.
GeForce RTX 4070 Ti[182] January 5, 2023 AD104-400 7680:240:80:240:60
(60)(5) 2310 2610 208.8 626.4 35.5
40.1 0.554
0.627 35.5
40.1 142 (284)
160 (321) 92.7
The information provided appears to be technical specifications for the GeForce RTX 4070 Ti GPU. Let’s break down the key details:
1. **GPU Details:**
– **Code Name:** AD104-400
– **Release Date:** January 5, 2023
2. **Architecture:**
– **CUDA Cores:** 7680
– **Tensor Cores:** 240
– **Texture Units:** 480
– **ROP Units:** 60
– **Ray Tracing Cores:** 240
3. **Clock Speeds:**
– **Base Clock:** 2310 MHz
– **Boost Clock:** 2610 MHz
4. **Performance:**
– **FP32 Performance (in TFLOPS):** 208.8
– **RT Core Performance (in GRays/s):** 626.4
– **Tensor Core Performance (in TFLOPS):** 35.5
– **Memory Bandwidth (in GB/s):** 40.1
5. **Memory:**
– **Memory Type:** Not specified
– **Memory Size:** Not specified
– **Memory Speed:** Not specified
6. **Power Consumption (TDP):**
– **TDP:** 35.5 Watts (Typical), 40.1 Watts (Peak)
7. **Efficiency:**
– **Performance per Watt (FP32):** 0.554 TFLOPS/W
– **Performance per Watt (Tensor Core):** 0.627 TFLOPS/W
– **Power Efficiency (Performance/Watt):** 35.5
8. **Other Metrics:**
– **Die Size:** Not specified
– **Transistor Count:** 142 billion (284 billion for peak)
9. **Temperature:**
– **Typical Operating Temperature:** 92.7°C
Please note that some critical information, such as the memory type, memory size, and die size, is not specified in the provided data. Additionally, specific use cases like gaming or machine learning inference may require additional information for a comprehensive assessment. If there are specific aspects you would like more details on or if you have any further questions, feel free to ask.
eForce RTX 3080 Ti[168] June 3, 2021 GA102-225-A1 10240:320:112:320:80
(80) (7) 1365 1665 153.5
186.5 438.5
532.8 28.57
34.1 0.438
0.533 28.06
34.10 228.6
272.8 68.2
Here are the technical specifications for the GeForce RTX 3080 Ti GPU based on the provided information:
1. **GPU Details:**
– **Code Name:** GA102-225-A1
– **Release Date:** June 3, 2021
2. **Architecture:**
– **CUDA Cores:** 10240
– **Tensor Cores:** 320
– **Texture Units:** 320
– **ROP Units:** 112
– **Ray Tracing Cores:** 80
3. **Clock Speeds:**
– **Base Clock:** 1365 MHz
– **Boost Clock:** 1665 MHz
4. **Performance:**
– **FP32 Performance (in TFLOPS):** 153.5
– **RT Core Performance (in GRays/s):** 186.5
– **Tensor Core Performance (in TFLOPS):** 438.5
– **Memory Bandwidth (in GB/s):** 532.8
5. **Memory:**
– **Memory Type:** Not specified
– **Memory Size:** Not specified
– **Memory Speed:** Not specified
6. **Power Consumption (TDP):**
– **TDP:** 28.57 Watts (Typical), 34.1 Watts (Peak)
7. **Efficiency:**
– **Performance per Watt (FP32):** 0.438 TFLOPS/W
– **Performance per Watt (Tensor Core):** 0.533 TFLOPS/W
– **Power Efficiency (Performance/Watt):** 28.06
8. **Other Metrics:**
– **Die Size:** Not specified
– **Transistor Count:** 228.6 billion
9. **Temperature:**
– **Typical Operating Temperature:** 68.2°C
As with the previous specification set, some important details such as memory type, memory size, and die size are not provided. If you have specific requirements or use cases you would like to assess these GPUs for, feel free to ask for more details or clarification.
With all of the data I sent we should be able to table a results?
Certainly! Let’s create a table to compare the key specifications of the GeForce RTX 4070 Ti and the GeForce RTX 3080 Ti based on the information you provided:
| Specification | RTX 4070 Ti | RTX 3080 Ti |
|——————————————-|————————————————|————————————————|
| **Architecture** | AD104-400 | GA102-225-A1 |
| **CUDA Cores** | 7680 | 10240 |
| **Tensor Cores** | 240 | 320 |
| **Texture Units** | 480 | 320 |
| **ROP Units** | 60 | 112 |
| **Ray Tracing Cores** | 240 | 80 |
| **Base Clock** | 2310 MHz | 1365 MHz |
| **Boost Clock** | 2610 MHz | 1665 MHz |
| **Memory Interface** | 192-bit | Not specified |
| **Memory Speed** | 21 Gb/s | Not specified |
| **FP32 Performance (TFLOPS)** | 208.8 | 153.5 |
| **RT Core Performance (GRays/s)** | 626.4 | 186.5 |
| **Tensor Core Performance (TFLOPS)** | 35.5 | 438.5 |
| **Memory Bandwidth (GB/s)** | 40.1 | 532.8 |
| **TDP (Watts)** | 35.5 (Typical), 40.1 (Peak) | 28.57 (Typical), 34.1 (Peak) |
| **Performance/Watt (FP32)** | 0.554 TFLOPS/W | 0.438 TFLOPS/W |
| **Performance/Watt (Tensor Core)** | 0.627 TFLOPS/W | 0.533 TFLOPS/W |
| **Power Efficiency (Performance/Watt)** | 35.5 | 28.06 |
| **Transistor Count (Billion)** | 142 (284 Peak) | 228.6 |
| **Typical Operating Temperature (°C)** | 92.7 | 68.2 |
Please note that some information, such as memory type, memory size, and die size, is still not provided. If you have any specific criteria or questions, feel free to ask for more details or clarification.
With the more tensor and cuda cores and a 384bit interface it seems that the 3080ti would be better for inference or am I missing something?
Based on the provided information, the GeForce RTX 3080 Ti indeed appears to have a higher number of CUDA cores and Tensor cores, as well as a wider memory interface (384-bit) compared to the GeForce RTX 4070 Ti. These specifications are essential for inference tasks, especially those involving deep learning and AI, as they contribute to the overall parallel processing power and memory bandwidth.
Here are some key points to consider:
1. **CUDA Cores and Tensor Cores:**
– The higher number of CUDA cores and Tensor cores in the RTX 3080 Ti generally implies greater parallel processing capabilities, which are beneficial for inference workloads.
2. **Memory Interface:**
– The wider 384-bit memory interface in the RTX 3080 Ti allows for higher memory bandwidth, which can be advantageous in handling large datasets during inference tasks.
3. **Memory Speed:**
– The memory speed is not specified for either GPU, so it’s essential to consider this factor as well. Faster memory speed can further enhance performance in memory-intensive tasks.
4. **Performance per Watt (Tensor Core):**
– The performance per watt for Tensor cores is higher in the RTX 3080 Ti, indicating potentially better power efficiency in tensor-based calculations.
While these specifications suggest that the RTX 3080 Ti could be better suited for inference tasks, it’s crucial to consider real-world benchmarks and performance metrics for the specific applications or frameworks you plan to use. Actual performance can vary based on software optimizations, driver support, and other factors.
If possible, refer to benchmark results or reviews that focus on inference performance for both GPUs in the context of your intended use case. Additionally, consider factors such as pricing, availability, and power consumption in your decision-making process.
SO Tensor (fp16)(sparese 2:1) when the values are : 172 (344)
195 (390 means what?
In the context of tensor operations using half-precision floating-point (FP16) format and with sparse data where the density is 2:1 (meaning there are 2 non-zero values for every 1 zero value), the provided values “172 (344)” and “195 (390)” likely represent the compressed and uncompressed sizes of the tensors.
Let’s break down the interpretation:
1. **172 (344):**
– The first number (172) is likely the size of the compressed tensor.
– The second number (344) is likely the size of the uncompressed tensor.
2. **195 (390):**
– Similarly, the first number (195) is likely the size of another compressed tensor.
– The second number (390) is likely the size of the uncompressed version of the same tensor.
The compression ratio can be calculated as the ratio of the compressed size to the uncompressed size. In these cases:
– For the first tensor: Compression ratio = 172 / 344 = 0.5 (or 2:1 when considering the reciprocal).
– For the second tensor: Compression ratio = 195 / 390 = 0.5 (or 2:1).
These ratios indicate that, with the given sparse representation, the compressed tensors are half the size of their uncompressed counterparts, achieving a 2:1 compression ratio.
Keep in mind that these interpretations are based on common conventions in representing compressed and uncompressed tensor sizes, but the exact meaning may vary depending on the specific context or notation used in the source material.
and when the same number are reperesented only: 228.6
272.8
In the context of sparse tensor operations with half-precision floating-point (FP16) format and a 2:1 sparse density, the values “228.6” and “272.8” might represent the compressed and uncompressed sizes of a tensor, similar to the previous examples.
Interpreting these values:
1. **228.6:**
– This is likely the size of the compressed tensor.
2. **272.8:**
– This is likely the size of the uncompressed tensor.
The compression ratio in this case can be calculated as:
[ text{Compression Ratio} = frac{text{Compressed Size}}{text{Uncompressed Size}} = frac{228.6}{272.8} approx 0.838 ]
So, in this instance, the compression ratio is approximately 0.838, or conversely, the uncompressed tensor is about 1.194 times larger than the compressed tensor. This indicates that, with the given sparse representation, the compressed tensor is achieving some level of compression but not as high as in the previous 2:1 density cases.
As always, the exact interpretation may depend on the specific conventions or notations used in the source material, so it’s essential to consider the context in which these values are presented.