AMD Instinct MI300X
AMD graphics card specifications and benchmark scores
MCM DesignAt a Glance
AMDAMD Instinct MI300X Specifications
Instinct MI300X GPU Core
Shader units and compute resources
The AMD Instinct MI300X 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.
Instinct MI300X Clock Speeds
GPU and memory frequencies
Clock speeds directly impact the Instinct MI300X'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 Instinct MI300X by AMD dynamically adjusts frequencies based on workload, temperature, and power limits to maximize performance while maintaining stability.
AMD's Instinct MI300X Memory
VRAM capacity and bandwidth
VRAM (Video RAM) is dedicated memory for storing textures, frame buffers, and shader data. The Instinct MI300X'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.
Instinct MI300X by AMD Cache
On-chip cache hierarchy
On-chip cache provides ultra-fast data access for the Instinct MI300X, 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.
Instinct MI300X Theoretical Performance
Compute and fill rates
Theoretical performance metrics provide a baseline for comparing the AMD Instinct MI300X 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.
CDNA 3.0 Architecture & Process
Manufacturing and design details
The AMD Instinct MI300X is built on AMD's CDNA 3.0 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 Instinct MI300X will perform in GPU benchmarks compared to previous generations.
AMD's Instinct MI300X Power & Thermal
TDP and power requirements
Power specifications for the AMD Instinct MI300X 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 Instinct MI300X to maintain boost clocks without throttling.
Instinct MI300X by AMD Physical & Connectivity
Dimensions and outputs
Physical dimensions of the AMD Instinct MI300X 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.
AMD API Support
Graphics and compute APIs
API support determines which games and applications can fully utilize the AMD Instinct MI300X. 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.
Instinct MI300X Product Information
Release and pricing details
The AMD Instinct MI300X is manufactured by AMD 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 Instinct MI300X by AMD represents good value at current market prices. Predecessor and successor information aids in tracking generational improvements and planning future upgrades.
Instinct MI300X Benchmark Scores
geekbench_openclSource
Geekbench OpenCL tests GPU compute performance using the cross-platform OpenCL API. This shows how AMD Instinct MI300X handles parallel computing tasks like video encoding and scientific simulations. OpenCL is widely supported across different GPU vendors and platforms.
Top 5 Performers
Top 5 PerformersNearby Performers
Nearby PerformersAbout AMD Instinct MI300X
The AMD Instinct MI300X is a data-center accelerator built on the CDNA 3.0 architecture, designed for high-performance computing and AI workloads. Its benchmark results place it in the top tier of available accelerators, with a Geekbench OpenCL score of 317,994, which places it in the 100th percentile of all GPUs. This analysis examines the MI300X’s position against its closest competitors, its architectural strengths, and the specific workloads it is best suited for.
How It Compares
NVIDIA H200 NVL: The MI300X scores 5% lower than the NVIDIA H200 NVL, which achieves an average score of 334,891. This positions the MI300X as a direct competitor to NVIDIA’s high-memory-capacity offering, with the H200 NVL holding a modest edge in raw compute throughput. In practice, this means the H200 NVL may complete certain compute-bound tasks slightly faster, but the MI300X remains within a close performance band.
NVIDIA L40S: Against the NVIDIA L40S, which scores 295,763, the MI300X is 7.5% faster. This is a significant margin in the accelerator market, indicating that the MI300X delivers meaningfully higher compute performance for workloads like inference and training. The L40S is a capable card, but the data shows the MI300X has a clear advantage in OpenCL-based benchmarks.
NVIDIA B200: The MI300X trails the NVIDIA B200 by 8%, with the B200 scoring 345,482. This is the largest performance gap among the listed rivals, suggesting that the B200 holds a distinct performance lead. However, the MI300X’s advantage lies in its memory configuration, which is discussed later, potentially offsetting the raw compute deficit in memory-bound scenarios.
NVIDIA RTX 6000 Ada Generation: The MI300X outperforms the NVIDIA RTX 6000 Ada Generation by 10.7%, with the RTX 6000 scoring 287,237. This is the largest positive delta for the MI300X among its rivals, demonstrating a substantial performance advantage over a workstation-class card. The data indicates that the MI300X is not just an enterprise part but also significantly faster than high-end professional GPUs.
Ray Tracing and Feature Set
The MI300X does not include dedicated ray tracing cores or tensor cores, as indicated by the null values in its specification sheet. This is a deliberate design choice for a compute-optimized accelerator, where the focus is on raw FP32/FP16 throughput rather than graphics rendering features. Consequently, the API support for DirectX, OpenGL, and Vulkan is listed as "N/A", confirming that this is not a graphics card but a pure compute device.
The absence of a pixel rate (0 MPixel/s) and the lack of display outputs further reinforce this positioning. The MI300X is designed for headless operation in data centers, where it accelerates matrix operations and scientific simulations. Its shading units (19,456) and texture mapping units (1,216) are configured for parallel compute, with a texture rate of 2,553.6 GTexel/s, which is a measure of its raw arithmetic capability. The FP32 and FP16 performance are both rated at 81.72 TFLOPS, with a 1:1 ratio, meaning the card does not rely on reduced precision to boost throughput, it delivers consistent compute power across both formats.
Benchmark Performance
The Geekbench OpenCL score of 317,994 is the sole benchmark data point for the MI300X, and it serves as a reliable indicator of its compute performance. This score places it in the 100th percentile of all GPUs, which is the highest possible percentile ranking, indicating that it outperforms virtually all other graphics cards in this test. The average benchmark score is identical to the single test score, confirming that the MI300X has a consistent performance profile.
Relative to its nearest rivals, the deltas are as follows: the MI300X is 5% slower than the H200 NVL, 7.5% faster than the L40S, 8% slower than the B200, and 10.7% faster than the RTX 6000 Ada Generation. The pattern is clear, the MI300X sits in the upper-middle tier of this competitive set, trading blows with NVIDIA’s flagship accelerators. The 10.7% lead over the RTX 6000 Ada is notable, as it shows the MI300X can outperform a high-end professional GPU by a double-digit margin.
The data suggests that the MI300X is most competitive against the L40S, where it holds a solid advantage, and the RTX 6000 Ada, where it is decisively faster. The performance gap to the B200 and H200 NVL is smaller but consistent, indicating that NVIDIA retains a slight edge in raw compute. For workloads that are not memory-limited, this could translate to longer training times or slower inference for the MI300X, but the margin is narrow enough that other factors, such as software optimization, could tip the balance.
FAQ
Q: What is the Geekbench OpenCL score of the AMD Instinct MI300X?
A: The MI300X achieves a Geekbench OpenCL score of 317,994, which places it in the 100th percentile of all GPUs.
Q: How does the MI300X compare to the NVIDIA H200 NVL?
A: The MI300X scores 5% lower than the H200 NVL, which has an average score of 334,891. This makes the H200 NVL slightly faster in compute-bound tasks.
Q: Does the MI300X support ray tracing?
A: No, the MI300X does not have ray tracing cores, and its DirectX, OpenGL, and Vulkan APIs are listed as "N/A". It is a compute-only accelerator.
Q: What is the memory bandwidth of the MI300X?
A: The MI300X has a memory bandwidth of 5.32 TB/s, which is exceptionally high and suited for large data sets.
Q: What power supply is recommended for the MI300X?
A: The suggested PSU for the MI300X is 1150 W, and it has a TDP of 750 W. It does not require external power connectors, as it uses an OAM Module slot.
Q: Is the MI300X faster than the NVIDIA RTX 6000 Ada Generation?
A: Yes, the MI300X is 10.7% faster than the RTX 6000 Ada Generation, which scores 287,237. This is the largest performance advantage among its listed rivals.
Memory Subsystem
The MI300X is equipped with an enormous 192 GB of HBM3 memory, which is a defining feature of this accelerator. The memory bus width is 8192 bits, which is exceptionally wide, allowing for a memory bandwidth of 5.32 TB/s. This combination of capacity and bandwidth is critical for workloads that require holding large models or datasets in memory, such as training large language models or processing massive scientific simulations.
The effective memory clock is 1300 MHz, with a data rate of 5.2 Gbps, and the HBM3 interface is designed to maximize data throughput. For high-resolution or large-batch workloads, this memory subsystem is a major advantage. The 192 GB capacity means that many models can be loaded entirely into memory without needing to be split across multiple devices, reducing communication overhead and simplifying software development. The 5.32 TB/s bandwidth ensures that the compute units are fed with data quickly, minimizing idle time.
Compared to rivals, the MI300X’s memory capacity is a key differentiator. While the exact memory configurations of competitors are not listed in the data, the MI300X’s 192 GB is a large pool, likely exceeding what many other accelerators offer. For workloads that are memory-bound, the MI300X could outperform rivals with higher raw compute scores, such as the B200, because it can process larger batches or higher-resolution data without hitting memory bottlenecks.
Power and Cooling
The MI300X has a thermal design power (TDP) of 750 W, which is a substantial power draw, reflecting its high compute density. The suggested power supply is 1150 W, which provides a reasonable headroom above the TDP to account for system components and transient power spikes. Notably, the MI300X has no power connectors, as it is designed as an OAM (Open Accelerator Module) form factor, which receives power through the module slot itself rather than traditional PCIe power cables.
This form factor means that the MI300X is not intended for consumer desktops or standard server chassis but rather for specialized OAM-based systems. The lack of display outputs further confirms its data-center orientation. Cooling for the MI300X would require a capable air or liquid cooling solution designed for OAM modules, as the 750 W TDP generates significant heat. The data does not specify a cooler, but the power requirements suggest that robust thermal management is essential for sustained performance. The bus interface is PCIe 5.0 x16, which provides high-bandwidth connectivity to the host system, ensuring that data transfer does not become a bottleneck.
Who Should Consider It
The MI300X is suited for organizations and workloads that require massive memory capacity combined with high compute throughput. The 100th percentile benchmark score indicates that it is among the fastest accelerators available, and the 192 GB memory capacity makes it ideal for applications that need to process large models or datasets in a single device. For example, training large language models with billions of parameters, running complex simulations, or performing high-resolution scientific computing would all benefit from the MI300X’s capabilities.
At high resolutions or with large batch sizes, the memory bandwidth of 5.32 TB/s is a significant asset. The MI300X’s performance relative to rivals varies: it is 7.5% faster than the L40S and 10.7% faster than the RTX 6000 Ada, making it a strong choice if these are the primary alternatives. However, it trails the H200 NVL by 5% and the B200 by 8%, so for workloads that are purely compute-bound and fit within the memory capacity of those rivals, NVIDIA’s parts may offer slightly better performance.
The 1:1 FP16/FP32 ratio is particularly relevant for AI workloads that use mixed precision, as the MI300X does not sacrifice FP32 performance when running FP16 operations. This makes it a versatile choice for both training and inference. The lack of display outputs and graphics APIs means it is not suitable for rendering or visualization tasks, but for headless server deployment, it is a powerful compute engine. The OAM form factor requires a compatible chassis, so it is best considered by data centers with existing OAM infrastructure or plans to adopt it.
Architecture and Design
The MI300X is built on the CDNA 3.0 architecture, which is AMD’s dedicated compute architecture, distinct from its graphics-oriented RDNA line. The chip is named "Aqua Vanjaram" and is manufactured by TSMC on a 5 nm process node. This cutting-edge process enables a massive transistor count of 153,000 million (153 billion) on a die size of 1017 mm², resulting in a transistor density of 150.4 million transistors per square millimeter. This density is a testament to the advanced manufacturing process and the complexity of the design.
The core configuration includes 19,456 shading units, 1,216 texture mapping units, and no raster operation units (ROPs), consistent with its compute-focused role. The clock speeds are a base of 1000 MHz and a boost of 2100 MHz, which provide a wide dynamic range for power management. The FP32 compute is rated at 81.72 TFLOPS, with FP16 also at 81.72 TFLOPS, indicating a balanced design that does not rely on reduced precision for higher throughput.
The MI300X is part of the Instinct (MIx) generation and was released on December 5, 2023, as a successor to the Radeon Instinct line. It uses a PCIe 5.0 x16 bus interface, which is the latest standard for high-speed data transfer. The absence of RT cores and tensor cores, along with the "N/A" API support, reinforces that this is a pure compute accelerator. The architecture is optimized for throughput and memory bandwidth, with the 8192-bit memory bus and HBM3 memory working in tandem to deliver 5.32 TB/s. This design philosophy prioritizes data movement and parallel computation, making the MI300X a formidable tool for data-center-scale workloads.
The NVIDIA Equivalent of Instinct MI300X
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