NVIDIA H20 vs NVIDIA Jetson T4000 Comparison

Where Each One Wins

The recorded data presents two very different NVIDIA server products, each occupying a distinct role. The NVIDIA H20 is designed for maximum raw compute density in a data center, while the NVIDIA Jetson T4000 is positioned as a compact, lower-power accelerated computing module. The database shows no head-to-head benchmark wins for either part, so the analysis must rely on architectural specifications and the performance ceilings implied by those specifications.

The H20 wins decisively in every category related to raw throughput. Its FP32 performance of 39.54 TFLOPS dwarfs the 4.700 TFLOPS of the Jetson T4000. The H20 has 9984 shading units versus 1536 in the T4000, and its 312 texture mapping units compare to 48 in the smaller chip. Memory bandwidth is another clear victory: the H20 delivers 4.03 TB/s from its HBM3 stack, while the T4000 manages 273.2 GB/s from LPDDR5X. For large-scale training, inference, or any workload where data movement is the bottleneck, the H20 is the clear choice.

The Jetson T4000 wins in physical footprint and power envelope. Its 90 W TDP is a fraction of the 500 W TDP of the H20. The T4000 is an IGP (integrated graphics processor) module measuring 87 mm by 100 mm by 15 mm, while the H20 is an SXM module with no listed dimensions but a suggested 900 W power supply. The T4000 uses no external power connectors and carries a suggested 250 W power supply. For edge deployments, embedded systems, or any scenario with strict power and space constraints, the T4000 is the only viable option between the two.

The architecture generations differ notably. The H20 belongs to the Server Hopper (Hxx) generation using the GH100 chip, while the T4000 belongs to the Server Blackwell (Bxx) generation using the GB10B chip. Despite being the older architecture, the H20 maintains a massive performance advantage due to its sheer scale.

Architecture Differences

The H20 uses the Hopper architecture built on the GH100 chip, fabricated on a 5 nm process at TSMC. The die measures 814 mm² and contains 80,000 million transistors, yielding a transistor density of 98.3M per mm². The Jetson T4000 uses the Blackwell architecture on the GB10B chip, also fabricated on a 5 nm process at TSMC, but with a die size of 391 mm². The transistor count for the T4000 is listed as unknown, and no density figure is recorded.

The H20 features 9984 shading units, 312 TMUs, and 24 ROPs. It does not list RT cores, but includes 312 tensor cores. The T4000 has 1536 shading units, 48 TMUs, 16 ROPs, 12 RT cores, and 64 tensor cores. The H20 has no display outputs, and neither part has any display outputs listed.

Memory architecture is fundamentally different. The H20 uses 96 GB of HBM3 across a 6144-bit bus, resulting in 4.03 TB/s of bandwidth. The T4000 uses 64 GB of LPDDR5X across a 256-bit bus, delivering 273.2 GB/s. The memory clock differs as well: the H20 runs at 1313 MHz (5.3 Gbps effective), while the T4000 runs at 1067 MHz (8.5 Gbps effective).

Clock speeds favor the H20. Its base clock is 1830 MHz with a boost of 1980 MHz. The T4000 has a fixed clock of 1530 MHz for both base and boost. The H20 also has a much higher pixel rate (47.52 GPixel/s versus 24.48 GPixel/s) and texture rate (617.8 GTexel/s versus 73.44 GTexel/s).

The H20 connects via PCIe 5.0 x16, while the T4000 uses PCIe 5.0 x8. The H20 is an SXM module, suggesting a high-density server configuration. The T4000 is an IGP with power connectors listed as "None". Neither part supports DirectX, OpenGL, or Vulkan APIs, indicating both are compute-focused rather than graphics-focused.

The T4000 includes 12 RT cores, a feature entirely absent from the H20's specification list. This suggests the T4000 may support ray tracing workloads even though it has no display outputs. The tensor core count is much higher on the H20 (312 versus 64), which aligns with its dominant position in AI and deep learning workloads.

Head-to-Head Benchmarks

The database contains no recorded head-to-head benchmark results for these two parts. Both have an average benchmark score of 0 and a percentile ranking of 50 against all GPUs. Without direct measurements, the comparison relies entirely on the recorded specifications.

The FP32 compute gap is the most striking difference. The H20 delivers 39.54 TFLOPS, which is approximately 8.4 times the 4.700 TFLOPS of the T4000. In FP16, the H20 reaches 79.07 TFLOPS using a 2:1 ratio, while the T4000 delivers 4.700 TFLOPS at a 1:1 ratio. This means the H20 provides nearly 17 times the FP16 throughput, a massive advantage for AI inference and training workloads that rely on reduced precision.

Memory bandwidth tells a similar story. The H20's 4.03 TB/s is roughly 14.8 times the T4000's 273.2 GB/s. For large batch processing or models that cannot fit in on-chip cache, this bandwidth advantage is critical. The H20 also has 96 GB of memory versus 64 GB, providing 50% more capacity for large datasets or model weights.

The texture rate difference is substantial: 617.8 GTexel/s versus 73.44 GTexel/s, a factor of about 8.4. Pixel rates differ by a factor of about 1.9 (47.52 versus 24.48 GPixel/s), a smaller gap than the compute and bandwidth differences.

The T4000 compensates with a lower power draw. Its 90 W TDP is 18% of the H20's 500 W TDP. For performance per watt, the T4000 delivers 52.2 GFLOPS per watt in FP32 (4.700 TFLOPS divided by 90 W), while the H20 delivers 79.1 GFLOPS per watt (39.54 TFLOPS divided by 500 W). This indicates the H20 is more efficient in raw FP32 per watt despite its much higher absolute power consumption.

The H20's release date is recorded as 2024-01-31, while the T4000's release date is 2026-01-04. The T4000 is the newer product, listed as belonging to the Server Blackwell generation with a predecessor of Server Hopper and a successor of Server Rubin. The H20 belongs to the Server Hopper generation with a predecessor of Server Ada and a successor of Server Blackwell.

The Verdict

The data shows two products with fundamentally different design goals. The NVIDIA H20 is a high-end server accelerator built for maximum throughput. Its 500 W TDP, SXM module form factor, and 96 GB of HBM3 memory indicate a product intended for rack-mounted data center deployments where power and cooling are available in abundance. The FP32 and FP16 performance figures place it in a class that the T4000 cannot approach.

The NVIDIA Jetson T4000 is a compact IGP module with a 90 W TDP and no external power connectors. Its 64 GB of LPDDR5X memory and PCIe 5.0 x8 interface suggest a product designed for embedded or edge computing scenarios. The inclusion of 12 RT cores, absent from the H20, suggests the T4000 may handle ray tracing workloads despite lacking display outputs. Its 1530 MHz fixed clock and 1:1 FP16 ratio indicate a more balanced compute profile.

For users requiring maximum compute density, the H20 is the only choice. The 39.54 TFLOPS FP32 and 79.07 TFLOPS FP16 figures, combined with 4.03 TB/s of memory bandwidth, make it suitable for large-scale AI training, scientific simulation, or high-throughput inference. The 96 GB memory capacity accommodates models that would exceed the 64 GB available on the T4000.

For users constrained by power, space, or thermal limits, the T4000 is the appropriate selection. Its 90 W TDP allows deployment in environments where the 500 W H20 would be impractical. The 273.2 GB/s memory bandwidth, while far below the H20, is sufficient for many inference workloads. The fixed 1530 MHz clock simplifies thermal management in embedded systems.

The database records no direct benchmark comparisons, so performance ratios derive from specification sheets. The FP32 ratio of 8.4 times in favor of the H20 is the most reliable indicator of relative compute capability. The FP16 ratio of nearly 17 times is even more pronounced, suggesting the H20's tensor core configuration is significantly more powerful for AI workloads.

Neither product supports graphics APIs, confirming both are compute-only accelerators. The absence of display outputs on both parts reinforces this classification. The H20's PCIe 5.0 x16 interface provides twice the lane count of the T4000's x8 interface, potentially affecting host communication bandwidth in multi-GPU configurations.

FAQ

Q: Which GPU has higher FP32 performance?

A: The NVIDIA H20 delivers 39.54 TFLOPS, which is approximately 8.4 times the 4.700 TFLOPS of the NVIDIA Jetson T4000.

Q: How do the memory systems compare?

A: The H20 uses 96 GB of HBM3 across a 6144-bit bus with 4.03 TB/s bandwidth. The T4000 uses 64 GB of LPDDR5X across a 256-bit bus with 273.2 GB/s bandwidth.

Q: Which product supports ray tracing?

A: The Jetson T4000 includes 12 RT cores. The H20's specification list does not record any RT cores.

Q: What are the power requirements?

A: The H20 has a 500 W TDP with a suggested 900 W power supply. The T4000 has a 90 W TDP with a suggested 250 W power supply and uses no external power connectors.

Q: Which architecture is newer?

A: The Jetson T4000 uses the Blackwell architecture on the GB10B chip and has a release date of 2026-01-04. The H20 uses the Hopper architecture on the GH100 chip with a release date of 2024-01-31.

Q: Do either of these GPUs support graphics APIs?

A: Neither supports DirectX, OpenGL, or Vulkan. Both are compute-focused products with no display outputs.

Specification Differences

| Specification | NVIDIA H20 | NVIDIA Jetson T4000 |

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

| Chip | GH100 | GB10B |

| Architecture | Hopper | Blackwell |

| Generation | Server Hopper (Hxx) | Server Blackwell (Bxx) |

| Process Node | 5 nm | 5 nm |

| Die Size | 814 mm² | 391 mm² |

| Transistors | 80,000 million | unknown |

| Transistor Density | 98.3M / mm² | null |

| Base Clock | 1830 MHz | 1530 MHz |

| Boost Clock | 1980 MHz | 1530 MHz |

| Memory Clock | 1313 MHz 5.3 Gbps effective | 1067 MHz 8.5 Gbps effective |

| Memory Size | 96 GB | 64 GB |

| Memory Type | HBM3 | LPDDR5X |

| Memory Bus Width | 6144 bit | 256 bit |

| Memory Bandwidth | 4.03 TB/s | 273.2 GB/s |

| Shading Units | 9984 | 1536 |

| TMUs | 312 | 48 |

| ROPs | 24 | 16 |

| RT Cores | null | 12 |

| Tensor Cores | 312 | 64 |

| Pixel Rate | 47.52 GPixel/s | 24.48 GPixel/s |

| Texture Rate | 617.8 GTexel/s | 73.44 GTexel/s |

| FP32 | 39.54 TFLOPS | 4.700 TFLOPS |

| FP16 | 79.07 TFLOPS (2:1) | 4.700 TFLOPS (1:1) |

| TDP | 500 W | 90 W |

| Slot Width | SXM Module | IGP |

| Power Connectors | null | None |

| Suggested PSU | 900 W | 250 W |

| Bus Interface | PCIe 5.0 x16 | PCIe 5.0 x8 |

| Display Outputs | No outputs | No outputs |

| DirectX | N/A | N/A |

| OpenGL | N/A | N/A |

| Vulkan | N/A | N/A |

| Dimensions | null | 87 mm 3.4 inches, 100 mm 3.9 inches, 15 mm 0.6 inches |

| Release Date | 2024-01-31 | 2026-01-04 |

| Predecessor | Server Ada | Server Hopper |

| Successor | Server Blackwell | Server Rubin |

| Launch MSRP | null | 1,999 USD |