NVIDIA Tesla T10 16 GB

NVIDIA Tesla T10 16 GB is a professional server accelerator built on the Turing architecture, fabricated by TSMC on a 12 nm process. The GPU houses 18,600 million transistors on a 754 mm² die, yielding a transistor density of 24.7M per square millimeter. The data positions this card at the 50th percentile among all GPUs, indicating it sits squarely in the mid-range of the performance spectrum, with a balanced profile rather than a top-tier or entry-level standing. The silicon includes 3,584 shading units, 224 texture mapping units, and 64 ROPs, paired with a 256-bit memory interface that delivers 403.2 GB/s of bandwidth from its 16 GB of GDDR6 memory.

Benchmark Performance

The Tesla T10's compute fundamentals are defined by its clock speeds and core configuration. Operating at a base clock of 1065 MHz and a boost clock of 1395 MHz, the card achieves a peak FP32 throughput of 9.999 TFLOPS. This places it in a specific performance class: it is a capable single-precision compute engine, but the data shows no benchmark scores or nearest rivals to contextualize this against other specific models. The absence of benchmark entries means the percentile rank is the sole comparative metric. At the 50th percentile, the Tesla T10 sits exactly at the median of the GPU population, meaning half of all GPUs in the database score higher and half score lower. This is a neutral position, suggesting it is neither a dominant performer nor a weak one, but rather a predictable middle-of-the-road option. The FP32 figure of 9.999 TFLOPS is the key measurable performance indicator; for context, this is just under 10 TFLOPS, which is a strong number for professional compute workloads but not exceptional for modern high-end server accelerators. The texture rate of 312.5 GTexel/s and pixel rate of 89.28 GPixel/s further quantify its rasterization throughput, which is substantial for a single-slot card. The memory clock runs at 1575 MHz, translating to 12.6 Gbps effective, and the 403.2 GB/s bandwidth is adequate for feeding the compute units but not class-leading. Benchmark results indicate that the Tesla T10's performance profile is defined more by its balanced compute and memory characteristics than by any single standout metric.

Ray Tracing and Feature Set

The Tesla T10 integrates 56 ray tracing cores and 448 tensor cores, making it a full implementation of the Turing architecture's dedicated hardware acceleration for ray-traced workloads and AI inference. The ray tracing cores are designed to accelerate bounding volume hierarchy traversal and ray-triangle intersection tests, which are the primary bottlenecks in ray-traced rendering. The 448 tensor cores provide substantial throughput for matrix operations, enabling accelerated deep learning training and inference tasks. The FP16 performance is listed at 20.00 TFLOPS with a 2:1 ratio relative to FP32, meaning the tensor cores and general compute units can process half-precision data at twice the rate of full-precision data. This is a critical feature for AI workloads, where mixed-precision training is standard practice. On the API front, the card supports DirectX 12 Ultimate (feature level 12_2), OpenGL 4.6, and Vulkan 1.4. DirectX 12 Ultimate support indicates the card is compatible with modern gaming and rendering APIs, including ray tracing and variable rate shading features, even though it has no display outputs. Vulkan 1.4 support ensures broad compatibility with cross-platform graphics and compute applications. The absence of display outputs (listed as "No outputs") confirms this is a compute-only accelerator intended for server environments, not a workstation card for driving monitors. The feature set is comprehensive for a Turing-generation product, but it lacks any newer architecture-specific features that would appear in subsequent generations.

Who Should Consider It

Given the 50th percentile ranking and the FP32 throughput of 9.999 TFLOPS, the Tesla T10 is suited for specific professional use cases rather than general-purpose gaming. The card has no display outputs, so it cannot be used for direct rendering to a screen; it is designed for server and datacenter deployments where compute is the sole function. For workloads that rely on FP32 performance, such as certain scientific simulations, financial modeling, or older AI inference frameworks, the Tesla T10 offers a predictable level of throughput. The 16 GB GDDR6 memory with 403.2 GB/s bandwidth is sufficient for models and datasets that fit within that capacity, but larger workloads would exceed it. The 448 tensor cores provide a meaningful acceleration for AI inference tasks, particularly those that can leverage FP16 precision at the 20.00 TFLOPS rate. The 56 ray tracing cores make it a viable option for off-line ray-traced rendering in render farms, where the lack of display outputs is irrelevant. However, the 150 W TDP and single-slot form factor are notable constraints; the card is power-efficient for its compute density, requiring only a single 8-pin power connector and a 450 W suggested power supply. This makes it suitable for dense server configurations where power and space are at a premium. Users with workloads that require higher FP32 performance or larger memory capacities would need to look at other options, as the Tesla T10's 50th percentile standing indicates it is not a top-tier performer.

FAQ

Q: What is the FP32 compute performance of the Tesla T10?

A: The Tesla T10 achieves a peak FP32 throughput of 9.999 TFLOPS, operating at a base clock of 1065 MHz and a boost clock of 1395 MHz.

Q: Does the Tesla T10 support ray tracing?

A: Yes, it includes 56 dedicated ray tracing cores, which are part of the Turing architecture's hardware acceleration for ray-traced workloads.

Q: What is the memory configuration and bandwidth?

A: The card has 16 GB of GDDR6 memory on a 256-bit bus, delivering a bandwidth of 403.2 GB/s, with a memory clock of 1575 MHz (12.6 Gbps effective).

Q: Can this card be used for display output?

A: No, the Tesla T10 has no display outputs and is designed exclusively for compute workloads in server environments.

Q: What is the power requirement?

A: The TDP is 150 W, requiring a single 8-pin power connector; a 450 W power supply is suggested for the system.

Q: What API features does it support?

A: It supports DirectX 12 Ultimate (feature level 12_2), OpenGL 4.6, and Vulkan 1.4, making it compatible with modern rendering and compute APIs.

How It Compares

The nearestRivals field is empty in the available data, meaning there are no directly specified competitor scores or percentage deltas to reference. Consequently, the comparison must rely on the absolute performance metrics and the percentile ranking. The Tesla T10's 50th percentile position indicates it is outperformed by half of all GPUs in the database, which places it in the mid-range rather than the high-end. Its FP32 throughput of 9.999 TFLOPS is a clear benchmark figure, but without rival data, it is impossible to state specific percentage advantages or disadvantages. The 16 GB memory capacity and 403.2 GB/s bandwidth are substantial, but the 256-bit bus width is narrower than what is found on higher-tier accelerators, which typically use 384-bit or wider interfaces. The single-slot design and 150 W TDP are distinguishing characteristics; many comparable compute cards use dual-slot coolers and consume more power. The lack of display outputs is common among server accelerators but unusual for general-purpose GPUs. The Turing architecture, with its 56 RT cores and 448 tensor cores, provides a feature set that is contemporary for its generation, but the 12 nm process node is older compared to more recent 7 nm or smaller nodes. In the absence of direct rival data, the Tesla T10's positioning is best described as a mid-range compute accelerator with balanced specifications, suitable for specific professional tasks but not at the forefront of performance.