AMD Instinct MI300 vs AMD Radeon Instinct MI308X Comparison

# Where Each One Wins

The AMD Instinct MI300 and the AMD Radeon Instinct MI308X share the same physical die, the Aqua Vanjaram chip, built on the same CDNA 3.0 architecture. But the recorded data separates them clearly into distinct roles. The MI300 delivers a balanced compute profile with a 1000 MHz base clock and a 1700 MHz boost clock, while the MI308X pushes the same silicon much harder with a 2100 MHz boost clock. That clock difference alone shifts the entire performance envelope.

The MI308X wins on raw throughput in every measured category where the two can be compared. Its shading units total 19,456 versus 14,080 on the MI300, a 38% increase in compute resources. Texture mapping units follow the same pattern: 1,216 on the MI308X versus 880 on the MI300, a 38% rise. The texture rate scales accordingly, with the MI308X reaching 2,553.6 GTexel/s versus 1,496.0 GTexel/s on the MI300. That is a 70.7% advantage in texture throughput.

The MI300 holds its ground in one specific area: memory capacity per compute unit. With 128 GB of HBM3 across an 8192-bit bus, the MI300 dedicates more memory per shading unit than the MI308X. The MI308X carries 192 GB across the same 8192-bit bus, which is 50% more total memory but only 31.6% more capacity per shading unit. For workloads that need large models resident in VRAM, the MI308X wins outright. For workloads that need balanced memory access patterns across a smaller compute footprint, the MI300's ratio is tighter.

The MI300 also wins on power efficiency per terabyte of bandwidth. It draws 600 W for 5.32 TB/s, while the MI308X draws 750 W for 10.3 TB/s. Normalized, the MI300 delivers 8.87 GB/s per watt, and the MI308X delivers 13.73 GB/s per watt. The MI308X is more efficient per byte moved, but the MI300's lower absolute power draw allows deployment in systems with a 1000 W suggested PSU versus 1150 W for the MI308X.

# Architecture Differences

Both cards use the same Aqua Vanjaram chip, fabricated on TSMC's 5 nm process with 153,000 million transistors on a 1017 mm² die. Transistor density sits at 150.4 million per square millimeter for both. The architecture is CDNA 3.0 in both cases, with no tensor core or ray tracing core counts listed. The critical architectural split appears in how each card configures the silicon.

The MI300 runs its memory at 1300 MHz, achieving 5.2 Gbps effective data rate. The MI308X runs memory at 2525 MHz, achieving 10.1 Gbps effective, nearly doubling the memory clock. Both use HBM3 and the same 8192-bit bus, but the MI308X's faster memory clock directly produces its 10.3 TB/s bandwidth, versus 5.32 TB/s on the MI300. That is a 93.6% bandwidth increase.

FP16 compute tells a different architectural story. The MI300 lists FP16 at 47.87 TFLOPS with a 1:1 ratio to FP32, meaning it executes FP16 at the same rate as FP32. The MI308X lists FP16 at 653.7 TFLOPS with an 8:1 ratio, indicating it uses a different execution path that processes eight FP16 operations per FP32-equivalent clock. This 13.6x FP16 advantage on the MI308X suggests the card is tuned for matrix-heavy ML workloads, while the MI300's 1:1 ratio suits general compute where precision consistency matters.

The MI308X also expands shading units from 14,080 to 19,456, a 38.2% increase, and TMUs from 880 to 1,216, a 38.2% increase. Both retain 0 ROPs and 0 pixel rate, confirming neither card is designed for rasterization output. The MI300 lists no slot width, while the MI308X specifies an OAM Module form factor, indicating a different physical mounting approach. The MI300 uses 2x 8-pin power connectors, but the MI308X lists no connectors, relying on the OAM baseboard for power delivery.

# Head-to-Head Benchmarks

The recorded benchmark data contains no direct head-to-head results, but the specification differences produce clear numerical deltas that function as performance projections. The biggest single win for the MI308X is FP16 throughput. At 653.7 TFLOPS versus 47.87 TFLOPS, the MI308X delivers 13.65x the FP16 compute. That gap is so large it changes the class of workloads feasible on the card. Any neural network training or inference task that uses FP16 precision will complete dramatically faster on the MI308X.

FP32 compute also favors the MI308X, but by a smaller margin. The MI308X produces 81.72 TFLOPS versus 47.87 TFLOPS on the MI300, a 70.7% advantage. This aligns with the shading unit increase, as FP32 scales directly with the 38% more shading units and the 23.5% higher boost clock (2100 MHz versus 1700 MHz).

Memory bandwidth is the second-largest delta. The MI308X's 10.3 TB/s versus 5.32 TB/s on the MI300 represents a 93.6% improvement. For memory-bound kernels, such as large matrix multiplications with poor data reuse or graph traversal workloads, this bandwidth advantage will dominate execution time. The MI300's 128 GB capacity versus 192 GB on the MI308X means the MI308X can hold larger datasets in VRAM, reducing host-device transfers. The MI300's 128 GB is still substantial, but the MI308X's 50% capacity increase allows models that exceed 128 GB to run without spilling to system memory.

Texture rate shows a 70.7% advantage for the MI308X (2,553.6 GTexel/s versus 1,496.0 GTexel/s), which matters for convolutional operations that rely on texture unit throughput. The MI300's 1:1 FP16 to FP32 ratio means it processes FP16 at the same speed as FP32, which could be beneficial for workloads where FP32 precision is required but FP16 data is supplied, as the card does not need to convert or split paths. The MI308X's 8:1 ratio suggests it prioritizes FP16 density over FP32 compatibility.

# The Verdict

The data points to a clear split. The AMD Instinct MI300 is the conservative, balanced choice for mixed-precision compute where FP32 and FP16 are used roughly equally. Its 1:1 FP16 ratio means no penalty for FP16 operations, and its 600 W power draw with a 1000 W suggested PSU fits into standard server chassis with less power infrastructure. The 128 GB HBM3 at 5.32 TB/s is sufficient for many large-model inference tasks, and the 47.87 TFLOPS FP32 rate handles general scientific computing.

The AMD Radeon Instinct MI308X is the specialist for FP16-heavy workloads. Its 653.7 TFLOPS FP16 output, 10.3 TB/s bandwidth, and 192 GB capacity make it the stronger choice for large-scale AI training, particularly with models that exceed 128 GB. The 750 W TDP and 1150 W suggested PSU demand more robust power delivery, and the OAM Module slot width indicates a different server integration path. The MI308X's 81.72 TFLOPS FP32 also outperforms the MI300 by 70.7%, so it wins on every compute metric. The only reason to choose the MI300 is a system constraint on power, physical slot type, or the need for a 1:1 FP16/FP32 execution ratio.

# FAQ

Q: Which card has more memory bandwidth?

A: The MI308X has 10.3 TB/s bandwidth versus 5.32 TB/s on the MI300, a 93.6% difference.

Q: Are these cards the same physical chip?

A: Yes, both use the Aqua Vanjaram chip with 153,000 million transistors on a 1017 mm² die at TSMC 5 nm.

Q: What is the FP16 performance difference?

A: The MI308X delivers 653.7 TFLOPS FP16 with an 8:1 ratio, while the MI300 delivers 47.87 TFLOPS FP16 with a 1:1 ratio.

Q: Which card has more memory capacity?

A: The MI308X has 192 GB of HBM3, while the MI300 has 128 GB.

Q: Do either cards support DirectX or Vulkan?

A: The MI300 lists N/A for DirectX, OpenGL, and Vulkan. The MI308X lists null for those APIs, and both have no display outputs.

Q: What power connectors does each card use?

A: The MI300 uses 2x 8-pin connectors, while the MI308X lists no connectors, using its OAM Module form factor for power delivery.

# Specification Differences

| Specification | AMD Instinct MI300 | AMD Radeon Instinct MI308X |

|----------------|---------------------|-----------------------------|

| Boost clock | 1700 MHz | 2100 MHz |

| Memory clock | 1300 MHz, 5.2 Gbps effective | 2525 MHz, 10.1 Gbps effective |

| Memory size | 128 GB HBM3 | 192 GB HBM3 |

| Memory bandwidth | 5.32 TB/s | 10.3 TB/s |

| Shading units | 14,080 | 19,456 |

| Texture mapping units | 880 | 1,216 |

| Texture rate | 1,496.0 GTexel/s | 2,553.6 GTexel/s |

| FP32 compute | 47.87 TFLOPS | 81.72 TFLOPS |

| FP16 compute | 47.87 TFLOPS (1:1) | 653.7 TFLOPS (8:1) |

| TDP | 600 W | 750 W |

| Suggested PSU | 1000 W | 1150 W |

| Power connectors | 2x 8-pin | None |

| Slot width | Not listed | OAM Module |

| Release date | 2023-01-03 | 2023-12-05 |

| Generation | Instinct (MIx) | Radeon Instinct (MIx) |

| Predecessor | Radeon Instinct | FirePro Data Center |