NVIDIA TITAN X Pascal

The NVIDIA TITAN X Pascal is a GeForce 10-generation flagship built on the Pascal architecture, fabricated on TSMC's 16 nm process with 11,800 million transistors on a 471 mm² die. It launched in August 2016 at a launch MSRP of 1,199 USD, and is now end-of-life. With 3584 shading units, 224 texture mapping units, and 96 ROPs, it delivers 10.97 TFLOPS of FP32 compute and 480.4 GB/s of memory bandwidth via a 384-bit GDDR5X interface. The database places it at the 50th percentile among all GPUs tracked, though no benchmark scores or nearest-rival data are available in the record.

How It Compares

The TITAN X Pascal sits at the 50th percentile in the database's GPU ranking. This indicates a median position relative to every other GPU ever tracked, but without a specific percentile breakdown or nearest-rival entries, the exact competitive landscape cannot be quantified. The record lists no nearest rivals, meaning no direct score comparisons or delta percentages are provided. Consequently, any positional analysis must rely on the card's intrinsic specifications rather than head-to-head benchmark data.

Its generation placement is clear: it belongs to the GeForce 10 series, succeeding the GeForce 900 family and preceding the GeForce 20 series. The Pascal architecture is a full iteration over its predecessor, but the absence of successor details in the pack prevents a quantitative generational leap. The card's 12 GB GDDR5X memory and 384-bit bus are substantial for its era, and its 10.97 TFLOPS FP32 throughput places it firmly in the high-end segment of its generation—though this is an inference from its raw numbers, not a comparison to named competitors.

The 50th percentile rank is a neutral data point. It does not imply mediocrity or excellence; it simply states that half of the GPUs in the database score higher and half score lower. Because no benchmark scores are attached to this entry, the percentile may reflect a lack of submitted results rather than actual performance. The card's end-of-life status and 2016 release date mean it has been superseded by multiple generations, which likely contributes to its mid-pack rank in a database that includes modern GPUs.

Ray Tracing and Feature Set

The TITAN X Pascal does not include dedicated ray tracing cores or tensor cores; both fields are null in the specification. This means the hardware lacks the specialized units found in later GeForce 20-series cards for accelerated ray tracing and AI-based tensor operations. The card's feature set is therefore defined by its rasterization capabilities and API support.

It supports DirectX 12 with feature level 12_1, OpenGL 4.6, and Vulkan 1.4. These APIs cover the major graphics standards of its generation, including asynchronous compute and explicit multi-GPU support where applicable. The absence of RT cores does not preclude software-based ray tracing, but performance would rely on the general-purpose FP32 pipeline, which is not optimized for that workload.

The display output configuration includes one DVI port, one HDMI 2.0 port, and three DisplayPort 1.4a ports. This allows for multi-monitor setups and high refresh rates on compatible displays. The memory subsystem features 12 GB of GDDR5X across a 384-bit interface, yielding 480.4 GB/s of bandwidth. The memory clock is listed at 1251 MHz with an effective data rate of 10 Gbps. The FP16 compute rate is 171.5 GFLOPS, which is 1/64th of the FP32 rate—a deliberate design choice that prioritizes single-precision throughput over half-precision.

Power and Cooling

The TITAN X Pascal has a thermal design power (TDP) of 250 W. The manufacturer recommends a 600 W power supply, and the card requires one 6-pin and one 8-pin PCIe power connector. This is a dual-slot card, occupying two expansion slots in a chassis. Its physical dimensions are 267 mm in length, 112 mm in height, and 40 mm in width, making it a sizable card that may require careful case clearance.

The cooling solution is not specified in the pack, but the dual-slot form factor and 250 W TDP suggest a robust air-cooling design. The power connector arrangement is typical for high-end GPUs of its era, and the 600 W PSU recommendation provides headroom for the rest of the system. The card's 16 nm process node from TSMC contributes to a transistor density of 25.1 million transistors per square millimeter, which is a key factor in managing power efficiency relative to older architectures.

The memory operates at 1251 MHz (10 Gbps effective), and the core clocks are 1417 MHz base and 1531 MHz boost. These clock speeds, combined with the 3584 shading units, result in the 10.97 TFLOPS FP32 figure. The pixel fill rate is 147.0 GPixel/s, and the texture fill rate is 342.9 GTexel/s, both derived from the ROP and TMU counts multiplied by the boost clock.

FAQ

Q: What is the memory configuration of the TITAN X Pascal?

A: It has 12 GB of GDDR5X memory on a 384-bit bus, with a bandwidth of 480.4 GB/s. The memory clock is 1251 MHz, effective 10 Gbps.

Q: Does the card support hardware ray tracing?

A: No. The specification lists no RT cores or tensor cores, so ray tracing would have to be performed through general-purpose compute, which is not hardware-accelerated.

Q: What power supply is recommended?

A: A 600 W power supply is suggested. The card itself has a TDP of 250 W and requires one 6-pin and one 8-pin PCIe power connector.

Q: What display outputs are available?

A: The card offers one DVI port, one HDMI 2.0 port, and three DisplayPort 1.4a ports, allowing for multi-monitor configurations.

Q: When was it released and is it still in production?

A: It was released on August 1, 2016, and is now end-of-life. It succeeded the GeForce 900 series and was succeeded by the GeForce 20 series.

Q: What is the FP16 compute performance?

A: FP16 performance is 171.5 GFLOPS, which is 1/64th of the FP32 throughput of 10.97 TFLOPS.

Benchmark Performance

The benchmark section of the database contains no entries for this GPU—no average score, no individual benchmarks, and no nearest-rival deltas. The only quantitative performance indicators are the theoretical specifications. The FP32 compute rate of 10.97 TFLOPS is the headline number, derived from 3584 shading units at a boost clock of 1531 MHz. This places the card in a strong position for compute-heavy workloads of its generation, though without comparative data, its standing relative to specific competitors cannot be quantified.

The pixel fill rate of 147.0 GPixel/s and texture fill rate of 342.9 GTexel/s are consistent with the 96 ROPs and 224 TMUs. These rates indicate the card's ability to handle high-resolution rendering and texture-heavy scenes. The memory bandwidth of 480.4 GB/s is a critical factor for maintaining frame rates at high resolutions and with high-quality textures, and the 12 GB capacity allows for large datasets and modern game assets.

The FP16 figure of 171.5 GFLOPS is notably low, reflecting a 1:64 ratio to FP32. This means the card is not optimized for half-precision workloads, which are common in AI inference and some compute tasks. In contrast, the FP32 throughput is substantial, suggesting the card was designed for traditional graphics and single-precision scientific computing.

Given the lack of benchmark scores, the percentile rank of 50 is the only comparative metric available. This rank is likely influenced by the card's age and the absence of submitted results. In a database that includes modern GPUs with higher compute densities and newer architectures, a 2016 flagship may naturally fall to the median. However, the raw specifications still demonstrate a capable high-end part for its time, with a memory subsystem and fill rates that were competitive at launch.

The card's 16 nm process and 11,800 million transistors contribute to its 471 mm² die, with a density of 25.1M transistors per mm². These physical characteristics, along with the 250 W TDP, define its power envelope. The 10.97 TFLOPS FP32 figure, when combined with the 480.4 GB/s bandwidth, suggests a balanced design for rasterization and compute, but without benchmark data, real-world performance cannot be validated. The absence of ray tracing and tensor cores further narrows its applicability to modern workloads that rely on those features.