AMD Instinct MI300 vs NVIDIA GeForce RTX 5050 Mobile Comparison
AMD Instinct MI300
GeForce RTX 5050 Mobile
PERFORMANCE BENCHMARKS
Analysis: AMD Instinct MI300 vs NVIDIA GeForce RTX 5050 Mobile
The AMD Instinct MI300 and NVIDIA GeForce RTX 5050 Mobile occupy opposite ends of the hardware spectrum. The MI300 is a data-center accelerator with a 600 W TDP, while the RTX 5050 Mobile is a 50 W laptop GPU. The database shows no direct head-to-head benchmark scores between them, and the MI300 has no recorded average benchmark score or percentile rank among all GPUs. The RTX 5050 Mobile, however, is well-documented, holding an 83rd percentile position among all GPUs with an average benchmark score of 43,268.
Head-to-Head Benchmarks
Direct comparisons are limited because the database does not list any shared benchmark results for these two parts. The AMD Instinct MI300 has no recorded benchmark scores, leaving its performance to be inferred from its theoretical specifications. The NVIDIA GeForce RTX 5050 Mobile, in contrast, has two recorded scores: 2,365 in 3DMark Steel Nomad DX12 and 84,171 in Geekbench OpenCL. These scores place the RTX 5050 Mobile at the 83rd percentile among all GPUs, with an average benchmark score of 43,268.
The nearest rivals for the RTX 5050 Mobile provide context for its performance. The NVIDIA Quadro M6000 24 GB scores 43,262, a delta of 0.0% compared to the RTX 5050 Mobile. The NVIDIA Quadro M6000 scores 43,301, which is 0.1% higher. The NVIDIA GeForce RTX 4070 SUPER scores 43,223, which is 0.1% lower. The NVIDIA GeForce RTX 4090 Mobile scores 43,667, which is 0.9% higher than the RTX 5050 Mobile. These deltas indicate that the RTX 5050 Mobile performs within a narrow band around these desktop and mobile parts, despite its much lower power envelope.
The MI300 has no such comparative data. Its compute capabilities are defined by its raw specifications: 47.87 TFLOPS of FP32 and FP16 performance. The RTX 5050 Mobile delivers 7.680 TFLOPS in both FP32 and FP16. This means the MI300 has roughly six times the raw floating-point throughput on paper. The MI300 also has a texture rate of 1,496.0 GTexel/s versus 120.0 GTexel/s for the RTX 5050 Mobile, a 12.5x difference. Pixel rates tell a different story: the MI300 has 0 MPixel/s, while the RTX 5050 Mobile has 48.00 GPixel/s, reflecting the MI300’s lack of a traditional raster output pipeline.
Where Each One Wins
The AMD Instinct MI300 wins in raw compute throughput. Its FP32 and FP16 figures of 47.87 TFLOPS are the highest in this comparison, and its texture rate of 1,496.0 GTexel/s is an order of magnitude above the RTX 5050 Mobile. The MI300 is built for data-center workloads that demand large matrix operations, as evidenced by its 14080 shading units, 880 texture mapping units, and 128 GB of HBM3 memory with 5.32 TB/s of bandwidth. The database shows no display outputs for the MI300, confirming it is not intended for rendering to a screen.
The NVIDIA GeForce RTX 5050 Mobile wins in traditional graphics features and portability. It has 20 ray tracing cores and 80 tensor cores, enabling hardware-accelerated ray tracing and AI features, neither of which are present on the MI300. The RTX 5050 Mobile also supports DirectX 12 Ultimate (12_2), OpenGL 4.6, and Vulkan 1.4, whereas the MI300 lists N/A for all three APIs. The RTX 5050 Mobile has a pixel rate of 48.00 GPixel/s, making it a functional rendering device, and it is marked as an integrated graphics processor (IGP) with no power connectors, drawing just 50 W.
The RTX 5050 Mobile also wins on physical footprint. Its dimensions are not listed in the database, but its slot width is marked "IGP," indicating it is designed to be soldered onto a laptop motherboard. The MI300 is a 267 mm long and 111 mm high card, requiring a 1000 W power supply and two 8-pin connectors. The RTX 5050 Mobile has no such requirements.
Architecture Differences
The MI300 uses the CDNA 3.0 architecture on a chip called Aqua Vanjaram, while the RTX 5050 Mobile uses the Blackwell 2.0 architecture on the GB207 chip. Both are manufactured by TSMC on a 5 nm process, but the transistor counts differ dramatically. The MI300 has 153,000 million transistors on a 1017 mm² die, yielding a transistor density of 150.4 million per square millimeter. The RTX 5050 Mobile has 16,900 million transistors on a 149 mm² die, yielding 113.4 million per square millimeter.
The MI300’s die is nearly seven times larger and contains about nine times more transistors. The CDNA 3.0 design is compute-focused, with no RT cores or tensor cores listed and no graphics APIs. The Blackwell 2.0 architecture, by contrast, includes dedicated ray tracing hardware (20 RT cores) and tensor cores (80) to accelerate modern graphics and AI workloads. The MI300’s shading units number 14,080, compared to 2,560 for the RTX 5050 Mobile, and its texture mapping units number 880 versus 80.
Memory architecture is also divergent. The MI300 uses 128 GB of HBM3 across an 8192-bit bus, achieving 5.32 TB/s of bandwidth. The RTX 5050 Mobile uses 8 GB of GDDR7 across a 128-bit bus, achieving 384.0 GB/s. The MI300’s memory clock is 1300 MHz with 5.2 Gbps effective speed, while the RTX 5050 Mobile’s memory clock is 1500 MHz with 24 Gbps effective speed. The MI300’s bandwidth is about 14 times higher, but its memory clock is lower, reflecting the different memory technologies.
Specification Differences
The two GPUs differ in nearly every measured specification. The MI300 has a base clock of 1000 MHz and a boost clock of 1700 MHz. The RTX 5050 Mobile has a base clock of 1020 MHz and a boost clock of 1500 MHz. The RTX 5050 Mobile has a higher base clock by 20 MHz, but the MI300 has a higher boost clock by 200 MHz.
The MI300 has 14,080 shading units, 880 TMUs, and 0 ROPs. The RTX 5050 Mobile has 2,560 shading units, 80 TMUs, and 32 ROPs. The MI300 has no RT cores or tensor cores listed, while the RTX 5050 Mobile has 20 RT cores and 80 tensor cores. The MI300’s pixel rate is 0 MPixel/s, and its texture rate is 1,496.0 GTexel/s. The RTX 5050 Mobile’s pixel rate is 48.00 GPixel/s, and its texture rate is 120.0 GTexel/s.
The TDP difference is substantial: 600 W for the MI300 versus 50 W for the RTX 5050 Mobile. The MI300 requires two 8-pin power connectors and a suggested 1000 W power supply, while the RTX 5050 Mobile has no power connectors and no suggested PSU. The MI300 has a PCIe 5.0 x16 interface and no display outputs. The RTX 5050 Mobile also uses PCIe 5.0 x16 but has portable-device-dependent display outputs.
The MI300 measures 267 mm by 111 mm, while the RTX 5050 Mobile has no recorded dimensions. The MI300 was released on January 3, 2023, and its predecessor is Radeon Instinct. The RTX 5050 Mobile was released on June 23, 2025, and its predecessor is GeForce 40 Mobile. The MI300 has no launch MSRP listed, and neither does the RTX 5050 Mobile.
FAQ
Q: Which GPU has higher raw FP32 compute performance?
A: The AMD Instinct MI300 delivers 47.87 TFLOPS of FP32 performance, which is about 6.2 times higher than the NVIDIA GeForce RTX 5050 Mobile’s 7.680 TFLOPS.
Q: Does the RTX 5050 Mobile support ray tracing?
A: Yes, the RTX 5050 Mobile has 20 ray tracing cores, while the AMD Instinct MI300 has no RT cores listed in the database.
Q: What is the memory bandwidth of each GPU?
A: The MI300 has 5.32 TB/s of bandwidth from 128 GB of HBM3 on an 8192-bit bus. The RTX 5050 Mobile has 384.0 GB/s from 8 GB of GDDR7 on a 128-bit bus.
Q: Which GPU is more power-efficient?
A: The RTX 5050 Mobile has a TDP of 50 W and no power connectors, while the MI300 has a TDP of 600 W and requires two 8-pin connectors and a 1000 W power supply.
Q: How does the RTX 5050 Mobile compare to its nearest rivals?
A: The RTX 5050 Mobile has an average benchmark score of 43,268. It is 0.1% slower than the NVIDIA Quadro M6000, 0.0% different from the Quadro M6000 24 GB, 0.1% faster than the GeForce RTX 4070 SUPER, and 0.9% slower than the GeForce RTX 4090 Mobile.
Q: Can the MI300 output video to a display?
A: No, the MI300 has no display outputs, while the RTX 5050 Mobile’s display outputs are listed as portable-device dependent, meaning they vary by laptop implementation.