AMD Instinct MI350P vs NVIDIA H800 SXM5 Comparison

Head-to-Head Benchmarks

The database contains no recorded benchmark scores for either the AMD Instinct MI350P or the NVIDIA H800 SXM5. Both processors hold a percentile rank of 50 among all GPUs in the database, and their average benchmark scores are recorded as zero. This indicates that neither part has generated measurable performance data yet, likely due to the MI350P being scheduled for release in 2026 and the H800 having a limited deployment profile.

Without head-to-head benchmark results, the comparison must rely on the architectural specifications and theoretical throughput figures recorded in the database. The raw compute numbers show a clear split: NVIDIA H800 SXM5 delivers 59.30 TFLOPS FP32, while AMD Instinct MI350P delivers 36.04 TFLOPS FP32, placing NVIDIA 64.5% ahead in single-precision floating-point work. In FP16, the gap widens dramatically: H800 reaches 237.2 TFLOPS (4:1 ratio), while MI350P achieves 36.04 TFLOPS (1:1 ratio), making NVIDIA 6.58 times faster in half-precision throughput.

The texture rate comparison flips the narrative. AMD Instinct MI350P records 1,126.4 GTexel/s, while NVIDIA H800 SXM5 records 926.6 GTexel/s, giving AMD a 21.6% advantage in texture fill operations. Pixel rate shows a similar inversion: H800 produces 42.12 GPixel/s, while MI350P records 0 MPixel/s, indicating the AMD part lacks ROP functionality entirely, with zero raster operations pipelines in its design.

Memory bandwidth presents the most substantial AMD advantage. The MI350P pairs 144 GB of HBM3e with an 8192-bit bus, producing 8.19 TB/s of bandwidth. The H800 offers 80 GB of HBM3 on a 5120-bit bus, yielding 3.36 TB/s. AMD holds a 143.75% bandwidth lead, which directly impacts memory-bound workloads such as large model inference and data-parallel training loops.

Clock behavior also differs meaningfully. The MI350P has a base clock of 1000 MHz and a boost clock of 2200 MHz, while the H800 operates at 1095 MHz base and 1755 MHz boost. AMD's boost clock runs 25.4% higher, though NVIDIA's base clock sits 9.5% higher. The AMD chip compensates with its 3 nm process node versus NVIDIA's 5 nm node, both fabricated by TSMC.

The Verdict

The recorded data indicates two different design philosophies with no overlapping benchmark results to settle the question empirically. For FP32 compute, NVIDIA H800 SXM5 delivers 59.30 TFLOPS versus AMD's 36.04 TFLOPS, a 64.5% margin that matters for scientific simulation and general HPC workloads. For FP16 throughput, NVIDIA's 237.2 TFLOPS versus AMD's 36.04 TFLOPS represents a 6.58x advantage, which strongly favors the H800 for AI training and inference workloads that rely on half-precision arithmetic.

However, the memory subsystem tells the opposite story. AMD Instinct MI350P provides 144 GB of memory, 80% more capacity than NVIDIA's 80 GB, and 8.19 TB/s of bandwidth, which is 2.44 times NVIDIA's 3.36 TB/s. Any workload constrained by memory capacity or bandwidth, such as training very large transformer models or processing massive embedding tables, would favor the AMD part based on these recorded specifications alone.

The verdict from the data is conditional: NVIDIA H800 SXM5 wins on raw compute density and FP16 throughput, while AMD Instinct MI350P wins on memory capacity, memory bandwidth, and texture rate. The choice depends entirely on whether the workload is compute-bound or memory-bound. The database shows no benchmark evidence to override these specification-derived conclusions.

Architecture Differences

AMD Instinct MI350P uses the CDNA 4.0 architecture with the MI350 128CU chip, while NVIDIA H800 SXM5 uses the Hopper architecture with the GH100 chip. The CDNA 4.0 design targets compute acceleration with 8,192 shading units, 512 texture mapping units, and zero ROPs, reflecting a pure compute-oriented design with no rasterization pipeline. The Hopper architecture similarly omits traditional graphics features but includes 528 tensor cores, which the AMD part does not list in its specification.

The transistor counts differ: NVIDIA GH100 contains 80,000 million transistors on an 814 mm² die, while AMD MI350 128CU contains 73,000 million transistors on a larger 1190 mm² die. This produces transistor densities of 98.3 million per mm² for NVIDIA and 61.3 million per mm² for AMD. The AMD chip is 46.2% larger physically but packs 8.75% fewer transistors, a trade-off enabled by the 3 nm process node that allows larger dies with lower density.

Process technology differs: AMD uses a 3 nm node, while NVIDIA uses a 5 nm node, both from TSMC. The smaller node explains AMD's ability to reach a 2200 MHz boost clock despite the larger die. The MI350P has no tensor cores listed in its specification, whereas the H800 includes 528 tensor cores, suggesting different approaches to matrix math acceleration. The MI350P's FP16 1:1 ratio indicates symmetric FP16 and FP32 throughput, while the H800's 4:1 ratio shows dedicated hardware acceleration for half-precision via tensor cores.

Specification Differences

The two accelerators differ across nearly every recorded specification field. AMD Instinct MI350P uses HBM3e memory totaling 144 GB on an 8192-bit bus, while NVIDIA H800 SXM5 uses HBM3 totaling 80 GB on a 5120-bit bus. Memory clocks also differ: AMD runs at 2000 MHz with 8 Gbps effective, while NVIDIA runs at 1313 MHz with 5.3 Gbps effective.

Power requirements differ: AMD consumes 600 W TDP with a 1000 W suggested PSU and a single 16-pin power connector, while NVIDIA consumes 700 W TDP with a 1100 W suggested PSU and an 8-pin EPS connector. Form factors differ as well: AMD uses a dual-slot design measuring 267 mm in length, 111 mm in height, and 40 mm in width, while NVIDIA uses an SXM module format with no recorded dimensions.

Shading unit counts differ significantly: NVIDIA has 16,896 shading units versus AMD's 8,192, a 106.3% advantage. TMU counts are closer: NVIDIA has 528 versus AMD's 512, a 3.1% difference. ROP counts show the largest structural gap: NVIDIA has 24 ROPs while AMD has zero. Tensor cores exist only on NVIDIA with 528 units. Both parts use PCIe 5.0 x16 interfaces and have no display outputs.

Release dates differ: NVIDIA H800 SXM5 launched in 2023 with active production status, while AMD Instinct MI350P has a 2026 release date and no production status recorded. NVIDIA lists its predecessor as Server Ada and successor as Server Blackwell, while AMD lists its predecessor as Radeon Instinct with no successor. The MI350P belongs to the Instinct (MIx) generation, while the H800 belongs to the Server Hopper (Hxx) generation.

FAQ

Q: Which accelerator has higher FP32 compute throughput?

A: NVIDIA H800 SXM5 records 59.30 TFLOPS FP32, while AMD Instinct MI350P records 36.04 TFLOPS FP32. NVIDIA leads by 64.5% in single-precision performance.

Q: How does memory bandwidth compare between the two?

A: AMD Instinct MI350P provides 8.19 TB/s of bandwidth from 144 GB of HBM3e on an 8192-bit bus. NVIDIA H800 SXM5 provides 3.36 TB/s from 80 GB of HBM3 on a 5120-bit bus. AMD leads by 143.75%.

Q: What is the FP16 performance difference?

A: NVIDIA H800 SXM5 delivers 237.2 TFLOPS FP16 using a 4:1 ratio, while AMD Instinct MI350P delivers 36.04 TFLOPS FP16 using a 1:1 ratio. NVIDIA is 6.58 times faster in half-precision throughput.

Q: Which chip uses a smaller manufacturing process?

A: AMD Instinct MI350P uses a 3 nm TSMC process, while NVIDIA H800 SXM5 uses a 5 nm TSMC process. AMD's node is smaller, though NVIDIA achieves higher transistor density at 98.3M per mm² versus AMD's 61.3M per mm².

Q: Do either of these accelerators support graphics APIs?

A: AMD Instinct MI350P lists DirectX, OpenGL, and Vulkan as N/A, while NVIDIA H800 SXM5 lists null values for all three APIs. Neither part has display outputs, and both are compute-only accelerators.

Q: What are the power consumption figures?

A: AMD Instinct MI350P has a 600 W TDP with a 1000 W suggested PSU, while NVIDIA H800 SXM5 has a 700 W TDP with a 1100 W suggested PSU. NVIDIA consumes 16.7% more power.

Where Each One Wins

AMD Instinct MI350P wins in memory-bound scenarios. The 144 GB capacity exceeds NVIDIA's 80 GB by 80%, and the 8.19 TB/s bandwidth is 2.44 times higher. Workloads that load large model weights, process wide embedding layers, or stream massive datasets benefit from this recorded advantage. The 1,126.4 GTexel/s texture rate also exceeds NVIDIA's 926.6 GTexel/s by 21.6%, which matters for texture-heavy compute pipelines. The higher 2200 MHz boost clock and the 3 nm process node indicate a design optimized for sustained memory access patterns.

NVIDIA H800 SXM5 wins in compute-bound scenarios. The 59.30 TFLOPS FP32 output is 64.5% higher than AMD's 36.04 TFLOPS, and the 237.2 TFLOPS FP16 output is 6.58 times higher. The 528 tensor cores provide dedicated matrix math acceleration that AMD does not list. The 16,896 shading units, 106.3% more than AMD's 8,192, contribute to this compute lead. The 42.12 GPixel/s pixel rate, which AMD cannot match with zero ROPs, indicates NVIDIA retains some rasterization capability. The active production status and 2023 release date mean availability is confirmed, while AMD's 2026 date remains pending.

The data shows a clear split: AMD for memory capacity and bandwidth, NVIDIA for raw compute and tensor throughput. The 600 W versus 700 W TDP difference is small relative to the performance deltas, and both parts target the same PCIe 5.0 x16 server platform. The absence of benchmark scores in the database means these specification-derived conclusions stand as the only quantified comparison available.