NVIDIA Tesla K10
NVIDIA graphics card specifications and benchmark scores
At a Glance
NVIDIANVIDIA Tesla K10 Specifications
GPU Core
Shader units and compute resources
The NVIDIA Tesla K10 GPU core specifications define its raw processing power for graphics and compute workloads. Shading units (also called CUDA cores, stream processors, or execution units depending on manufacturer) handle the parallel calculations required for rendering. TMUs (Texture Mapping Units) process texture data, while ROPs (Render Output Units) handle final pixel output. Higher shader counts generally translate to better GPU benchmark performance, especially in demanding games and 3D applications.
Tesla K10 Clock Speeds
GPU and memory frequencies
Clock speeds directly impact the Tesla K10's performance in GPU benchmarks and real-world gaming. The base clock represents the minimum guaranteed frequency, while the boost clock indicates peak performance under optimal thermal conditions. Memory clock speed affects texture loading and frame buffer operations. The Tesla K10 by NVIDIA dynamically adjusts frequencies based on workload, temperature, and power limits to maximize performance while maintaining stability.
NVIDIA's Tesla K10 Memory
VRAM capacity and bandwidth
VRAM (Video RAM) is dedicated memory for storing textures, frame buffers, and shader data. The Tesla K10's memory capacity determines how well it handles high-resolution textures and multiple displays. Memory bandwidth, measured in GB/s, affects how quickly data moves between the GPU and VRAM. Higher bandwidth improves performance in memory-intensive scenarios like 4K gaming. The memory bus width and type (GDDR6, GDDR6X, HBM) significantly influence overall GPU benchmark scores.
Tesla K10 by NVIDIA Cache
On-chip cache hierarchy
On-chip cache provides ultra-fast data access for the Tesla K10, reducing the need to fetch data from slower VRAM. L1 and L2 caches store frequently accessed data close to the compute units. AMD's Infinity Cache (L3) dramatically increases effective bandwidth, improving GPU benchmark performance without requiring wider memory buses. Larger cache sizes help maintain high frame rates in memory-bound scenarios and reduce power consumption by minimizing VRAM accesses.
Tesla K10 Theoretical Performance
Compute and fill rates
Theoretical performance metrics provide a baseline for comparing the NVIDIA Tesla K10 against other graphics cards. FP32 (single-precision) performance, measured in TFLOPS, indicates compute capability for gaming and general GPU workloads. FP64 (double-precision) matters for scientific computing. Pixel and texture fill rates determine how quickly the GPU can render complex scenes. While real-world GPU benchmark results depend on many factors, these specifications help predict relative performance levels.
Kepler Architecture & Process
Manufacturing and design details
The NVIDIA Tesla K10 is built on NVIDIA's Kepler architecture, which defines how the GPU processes graphics and compute workloads. The manufacturing process node affects power efficiency, thermal characteristics, and maximum clock speeds. Smaller process nodes pack more transistors into the same die area, enabling higher performance per watt. Understanding the architecture helps predict how the Tesla K10 will perform in GPU benchmarks compared to previous generations.
Power & Thermal
TDP and power requirements
Power specifications for the NVIDIA Tesla K10 determine PSU requirements and thermal management needs. TDP (Thermal Design Power) indicates the heat output under typical loads, guiding cooler selection. Power connector requirements ensure adequate power delivery for stable operation during demanding GPU benchmarks. The suggested PSU wattage accounts for the entire system, not just the graphics card. Efficient power delivery enables the Tesla K10 to maintain boost clocks without throttling.
Tesla K10 by NVIDIA Physical & Connectivity
Dimensions and outputs
Physical dimensions of the NVIDIA Tesla K10 are critical for case compatibility. Card length, height, and slot width determine whether it fits in your chassis. The PCIe interface version affects bandwidth for communication with the CPU. Display outputs define monitor connectivity options, with modern cards supporting multiple high-resolution displays simultaneously. Verify these specifications against your case and motherboard before purchasing to ensure a proper fit.
NVIDIA API Support
Graphics and compute APIs
API support determines which games and applications can fully utilize the NVIDIA Tesla K10. DirectX 12 Ultimate enables advanced features like ray tracing and variable rate shading. Vulkan provides cross-platform graphics capabilities with low-level hardware access. OpenGL remains important for professional applications and older games. CUDA (NVIDIA) and OpenCL enable GPU compute for video editing, 3D rendering, and scientific applications. Higher API versions unlock newer graphical features in GPU benchmarks and games.
Tesla K10 Product Information
Release and pricing details
The NVIDIA Tesla K10 is manufactured by NVIDIA as part of their graphics card lineup. Release date and launch pricing provide context for comparing GPU benchmark results with competing products from the same era. Understanding the product lifecycle helps evaluate whether the Tesla K10 by NVIDIA represents good value at current market prices. Predecessor and successor information aids in tracking generational improvements and planning future upgrades.
About NVIDIA Tesla K10
The NVIDIA Tesla K10 is a dual-slot, end-of-life compute accelerator built on the 28 nm Kepler architecture, featuring the GK104 chip with 1,536 shading units, 128 TMUs, and 32 ROPs. It ships with 4 GB of GDDR5 memory on a 256-bit bus, delivering 160.0 GB/s of bandwidth, and its benchmark results place it in the 55th percentile of all GPUs, with an average score of 14,029 in Geekbench OpenCL. This card is a legacy compute part, not a gaming or consumer graphics product, and its data reflects a design focused on raw throughput rather than modern feature support.
How It Compares
The Tesla K10’s nearest rival is the NVIDIA GeForce GTX 1660 Ti, which posts an average score of 13,925. The K10 leads by a narrow 0.7% margin, meaning the two are effectively neck-and-neck in raw compute throughput. In practice, the GTX 1660 Ti is a much newer architecture with modern driver support, so the K10’s slight edge in this specific OpenCL test does not translate to broader superiority.
Against the AMD Radeon RX 570X, the K10 scores 1.1% higher (14,029 vs. 13,871). This is a small but consistent lead, suggesting the K10 holds its own against a mid-range AMD part from a later generation. The delta is within run-to-run variance for many workloads, so the practical difference is minimal, but the data shows the K10 is not embarrassingly outclassed.
The NVIDIA RTX A2000 Mobile is 1.5% behind the K10, with a score of 13,821. This is notable because the A2000 Mobile is a laptop-oriented professional GPU with modern features like ray tracing and tensor cores, while the K10 lacks those entirely. The K10’s lead here is purely a function of raw FP32 compute, not efficiency or feature set, and it underscores how far the architecture has aged.
The closest competitor is the NVIDIA GeForce GTX 680, which scores 13,812, putting the K10 1.6% ahead. This makes sense, as both are built on the same GK104 chip, but the K10 is configured with more shading units (1,536 vs. the GTX 680’s lower count) and higher memory clocks. The delta is small, reflecting that the K10 is essentially a compute-oriented sibling of that gaming card.
Ray Tracing and Feature Set
The Tesla K10 has no dedicated ray tracing cores and no tensor cores, as those features were introduced in later NVIDIA architectures. This is a pure Kepler compute card, so any workload requiring hardware-accelerated ray tracing or AI tensor operations is out of scope. The card’s API support includes DirectX 12 (11_0), OpenGL 4.6, and Vulkan 1.2.175, which means it can run modern graphics APIs in a compute context, but it lacks the specialized hardware found in RTX-class products.
The absence of display outputs confirms this is not a graphics card for connecting monitors; it is intended for server or workstation compute tasks. The API list is relevant for compute kernels that leverage these interfaces, but the lack of RT/tensor hardware limits its use in contemporary machine learning or real-time ray tracing pipelines. For pure rasterization or general-purpose compute, the Kepler architecture remains functional, but it does not benefit from any of the acceleration features that define modern NVIDIA parts.
Benchmark Performance
The K10’s single benchmark result is a Geekbench OpenCL score of 14,029, which places it in the 55th percentile of all GPUs. This is a mid-pack position, indicating that while the card is not a top performer, it is far from the bottom. The score represents the card’s FP32 compute throughput of 2.289 TFLOPS, which is the primary metric for this type of workload.
Relative to its nearest rivals, the K10 is 0.7% ahead of the GTX 1660 Ti, 1.1% ahead of the RX 570X, 1.5% ahead of the RTX A2000 Mobile, and 1.6% ahead of the GTX 680. These deltas are all under 2%, meaning the K10 sits in a tight cluster of similarly-performing GPUs. The practical takeaway is that the K10’s compute performance is comparable to a modern mid-range card, but it achieves this with significantly older hardware and higher power consumption.
The pixel rate of 23.84 GPixel/s and texture rate of 95.36 GTexel/s are consistent with the card’s 32 ROPs and 128 TMUs at the given clocks. These figures are respectable for the era but are not competitive with modern parts that have much higher fill rates. The memory bandwidth of 160.0 GB/s is the clear bottleneck, as many contemporary GPUs exceed 300 GB/s, and this limits the K10 in memory-bound workloads despite its healthy compute score.
FAQ
Q: Does the Tesla K10 support ray tracing?
A: No, the K10 has no ray tracing cores. It is based on the Kepler architecture, which predates hardware ray tracing support, so any ray tracing workload would run on the shader units inefficiently.
Q: What is the K10’s memory configuration?
A: The card has 4 GB of GDDR5 memory on a 256-bit bus, providing 160.0 GB/s of bandwidth. The memory clock is 1250 MHz, or 5 Gbps effective.
Q: Can I use the Tesla K10 for gaming?
A: The K10 has no display outputs, so it cannot connect to a monitor. While it can render frames via compute APIs, it is not designed for interactive graphics and lacks the modern feature set of gaming cards.
Q: How does the K10 compare to the GTX 680?
A: The K10 scores 14,029, which is 1.6% higher than the GTX 680’s 13,812. Both use the GK104 chip, but the K10 has more shading units and a higher memory clock.
Q: What is the K10’s production status?
A: The K10 is end-of-life, meaning NVIDIA no longer produces it. Its predecessor is Tesla Fermi, and its successor is Tesla Maxwell.
Q: What APIs does the K10 support?
A: The card supports DirectX 12 (11_0), OpenGL 4.6, and Vulkan 1.2.175. This allows it to run modern compute workloads, but without RT or tensor cores.
Who Should Consider It
The Tesla K10 is a card for legacy compute workloads where raw FP32 throughput is the primary need and modern features are irrelevant. The benchmark score of 14,029 places it in the 55th percentile, meaning it outperforms a majority of GPUs in OpenCL compute, but it is not a top-tier part. Users running older scientific or rendering applications that rely on CUDA or OpenCL and do not require ray tracing or tensor operations could still find it functional, provided they have compatible drivers.
At 1080p or 1440p resolution for compute tasks, the K10 can handle moderate workloads, but its 160.0 GB/s memory bandwidth will cap performance in data-intensive applications. For settings-heavy workloads that require high fill rates, the 23.84 GPixel/s pixel rate and 95.36 GTexel/s texture rate are below modern standards, so it is not suitable for high-detail rendering. The data suggests this card is best suited for users who already own it or need a specific Kepler compute feature, not for new builds.
Power and Cooling
The Tesla K10 has a TDP of 225 W, which is the maximum power draw under load. NVIDIA recommends a 550 W power supply, and the card requires one 6-pin and one 8-pin power connector. This is a dual-slot card, measuring 272 mm (10.7 inches) in length, so it will fit in most full-tower cases but may be tight in smaller chassis.
The 28 nm process node and 3,540 million transistors on a 294 mm² die mean the card runs hot by modern standards, but the dual-slot cooler is designed to handle the 225 W TDP. There are no display outputs, so the card does not need to drive any monitors, which simplifies cooling in a server environment. Users should ensure their power supply has the necessary connectors and wattage headroom, as the 550 W suggestion is the minimum for a system with this card.
Detailed benchmark scores and charts for the NVIDIA Tesla K10 are below.
Benchmark Scores
geekbench_openclSource
Geekbench OpenCL tests GPU compute performance using the cross-platform OpenCL API. This shows how NVIDIA Tesla K10 handles parallel computing tasks like video encoding and scientific simulations.
Top 5 Performers
Top 5 PerformersNearby Performers
Nearby PerformersPopular NVIDIA Tesla K10 Comparisons
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