NVIDIA B200 SXM6 vs NVIDIA H100 CNX Comparison

Head-to-Head Benchmarks

The recorded database contains no direct head-to-head benchmark entries for the NVIDIA B200 SXM6 and NVIDIA H100 CNX. Both products hold a 50th percentile ranking against all GPUs in the database, and both carry an average benchmark score of zero. With no benchmark submissions logged for either part, the head-to-head comparison must rely entirely on the architectural and specification data recorded for each accelerator.

The most significant measurable difference lies in compute throughput. The B200 SXM6 delivers 69.34 TFLOPS of FP32 performance, while the H100 CNX delivers 53.84 TFLOPS. That places the B200 SXM6 roughly 28.8% ahead of the H100 CNX in FP32 throughput. The FP16 comparison is more complex due to differing ratio implementations. The B200 SXM6 records 69.34 TFLOPS FP16 at a 1:1 ratio, meaning the FP16 rate matches the FP32 rate. The H100 CNX records 215.4 TFLOPS FP16 at a 4:1 ratio, which means its FP16 throughput is optimized for tensor-heavy workloads at the cost of reduced precision per operation. The raw FP16 number favors the H100 CNX, but the B200 SXM6 maintains a consistent 1:1 ratio that may indicate different precision handling characteristics.

Memory bandwidth shows a substantial gap. The B200 SXM6 uses HBM3e memory with an 8192-bit bus and reaches 8.19 TB/s. The H100 CNX uses HBM2e memory with a 5120-bit bus and reaches 2.04 TB/s. The B200 SXM6 offers approximately 4.01 times the memory bandwidth of the H100 CNX. Memory capacity also differs sharply: the B200 SXM6 carries 180 GB, while the H100 CNX carries 80 GB, giving the B200 SXM6 2.25 times the capacity.

Pixel throughput is nearly identical. The B200 SXM6 reaches 43.92 GPixel/s, while the H100 CNX reaches 44.28 GPixel/s, a difference of less than 1% in favor of the H100 CNX. Texture throughput favors the B200 SXM6 at 1,083.4 GTexel/s versus 841.3 GTexel/s, a 28.8% advantage. The B200 SXM6 also holds a lead in shading units (18,944 vs 14,592), texture mapping units (592 vs 456), and tensor cores (592 vs 456). Both parts have 24 ROPs.

Clock behavior differs meaningfully. The H100 CNX has a base clock of 690 MHz and a boost clock of 1845 MHz. The B200 SXM6 has a base clock of 120 MHz and a boost clock of 1830 MHz. The H100 CNX therefore has a higher base clock by 570 MHz and a marginally higher boost clock by 15 MHz. The B200 SXM6 compensates with a much larger transistor count and die size.

Where Each One Wins

The B200 SXM6 wins decisively in memory-bound and capacity-bound workloads. Its 8.19 TB/s bandwidth versus 2.04 TB/s gives it a 4.01x advantage in raw memory throughput, which directly benefits large model training, inference with massive batch sizes, and any workload that repeatedly streams data through the memory subsystem. The 180 GB capacity versus 80 GB means the B200 SXM6 can hold larger models or larger working sets without spilling to slower storage. The FP32 advantage of 69.34 TFLOPS versus 53.84 TFLOPS also places the B200 SXM6 ahead in general-purpose compute tasks that rely on single-precision arithmetic.

The H100 CNX wins in FP16 tensor throughput on paper, with 215.4 TFLOPS versus 69.34 TFLOPS. The 4:1 ratio on the H100 CNX indicates that its FP16 path is built for high-throughput tensor operations, which matters for certain deep learning training loops that can tolerate reduced precision. The H100 CNX also holds a minor edge in pixel rate (44.28 vs 43.92 GPixel/s) and in boost clock (1845 MHz vs 1830 MHz). Its base clock of 690 MHz versus 120 MHz suggests that the H100 CNX maintains higher sustained clocks under light load conditions, which may translate to lower latency for small, frequent operations.

The H100 CNX also wins on power efficiency per the recorded data. Its TDP is 350 W versus 1000 W for the B200 SXM6, and its suggested PSU is 750 W versus 1400 W. The H100 CNX delivers 53.84 TFLOPS FP32 at 350 W, which is 0.154 TFLOPS per watt. The B200 SXM6 delivers 69.34 TFLOPS at 1000 W, which is 0.069 TFLOPS per watt. The H100 CNX achieves roughly 2.2 times the FP32 throughput per watt. In memory bandwidth per watt, however, the B200 SXM6 delivers 8.19 TB/s at 1000 W (8.19 GB/s per watt) versus 2.04 TB/s at 350 W (5.83 GB/s per watt), so the B200 SXM6 is more bandwidth-efficient per watt.

The H100 CNX is a dual-slot card with an 8-pin EPS power connection, while the B200 SXM6 is an SXM module with no display outputs. The H100 CNX has physical dimensions recorded at 267 mm length and 111 mm height. No physical dimensions are recorded for the B200 SXM6. The H100 CNX may be easier to integrate into existing PCIe-based server chassis, while the B200 SXM6 presumably requires a compatible SXM baseboard.

Architecture Differences

The B200 SXM6 uses the GB100 chip built on the Blackwell architecture, while the H100 CNX uses the GH100 chip built on the Hopper architecture. Both are fabricated by TSMC on a 5 nm process, but the transistor counts diverge substantially. The B200 SXM6 contains 208,000 million transistors on a 1628 mm² die, while the H100 CNX contains 80,000 million transistors on an 814 mm² die. The B200 SXM6 has roughly 2.6 times the transistor count and exactly 2.0 times the die area. Transistor density is 127.8 million transistors per square millimeter for the B200 SXM6 versus 98.3 million per square millimeter for the H100 CNX, indicating a denser layout on the Blackwell part.

The memory subsystems differ in type and configuration. The B200 SXM6 uses HBM3e with an 8192-bit bus and 180 GB capacity. The H100 CNX uses HBM2e with a 5120-bit bus and 80 GB capacity. The B200 SXM6 memory clock is recorded at 2000 MHz with 8 Gbps effective data rate, while the H100 CNX memory clock is recorded at 1593 MHz with 3.2 Gbps effective data rate. The B200 SXM6 has 4,096 more bits of bus width and 100 GB more capacity.

The compute configurations scale with the transistor budgets. The B200 SXM6 has 18,944 shading units, 592 TMUs, and 592 tensor cores. The H100 CNX has 14,592 shading units, 456 TMUs, and 456 tensor cores. Both have 24 ROPs. The B200 SXM6 therefore has 4,352 more shading units, 136 more TMUs, and 136 more tensor cores. Neither part has recorded ray tracing cores or display outputs.

The bus interfaces differ by generation. The B200 SXM6 uses PCIe 6.0 x16, while the H100 CNX uses PCIe 5.0 x16. Both are server-focused accelerators with no display outputs. The B200 SXM6 has no recorded power connectors, while the H100 CNX uses an 8-pin EPS connector. The B200 SXM6 has a TDP of 1000 W and a suggested PSU of 1400 W; the H100 CNX has a TDP of 350 W and a suggested PSU of 750 W.

Release timing differs by roughly a year and a half. The H100 CNX was released on 2023-03-20, and the B200 SXM6 was released on 2024-10-31. The H100 CNX lists its predecessor as Server Ada and its successor as Server Blackwell. The B200 SXM6 lists its predecessor as Server Hopper and its successor as Server Rubin. The B200 SXM6 has a recorded launch MSRP of 34,999 USD, while the H100 CNX has no launch MSRP recorded.

The FP16 ratio difference is an architectural distinction. The B200 SXM6 records FP16 at 69.34 TFLOPS with a 1:1 ratio, meaning its FP16 throughput equals its FP32 throughput. The H100 CNX records FP16 at 215.4 TFLOPS with a 4:1 ratio, meaning its FP16 path executes four times as many operations per clock as its FP32 path. This suggests different hardware partitioning for mixed-precision tensor math between the two architectures.

The API support also differs. The B200 SXM6 records DirectX, OpenGL, and Vulkan as N/A. The H100 CNX records all three as null values. Neither part exposes consumer graphics APIs, which is consistent with server-oriented accelerators.

The Verdict

The recorded data supports a clear division of use cases. The NVIDIA B200 SXM6 is the stronger choice for workloads that demand maximum memory bandwidth and capacity. Its 8.19 TB/s bandwidth is roughly four times the H100 CNX's 2.04 TB/s, and its 180 GB capacity is 2.25 times larger. These metrics matter for large-scale training runs, inference with very large batch sizes, and any application that continuously streams data through memory. The B200 SXM6 also leads in FP32 throughput by 28.8% and in texture throughput by 28.8%, making it the more capable general-purpose compute accelerator.

The NVIDIA H100 CNX is the more efficient part per watt and the more compact physical unit. It delivers 53.84 TFLOPS FP32 at 350 W, which is roughly 2.2 times the FP32 efficiency of the B200 SXM6. Its dual-slot form factor, 267 mm length, and 111 mm height allow integration into standard PCIe server slots. Its 8-pin EPS power connection and 750 W suggested PSU also place lower demands on power delivery infrastructure. The H100 CNX also records a higher FP16 throughput at 215.4 TFLOPS, though this comes with a 4:1 ratio that implies reduced precision per operation.

The choice between these two accelerators depends on whether the workload is memory-bound or efficiency-bound. The B200 SXM6 dominates on absolute bandwidth, capacity, and FP32 compute. The H100 CNX dominates on power efficiency, physical footprint, and raw FP16 throughput. The B200 SXM6 requires a 1000 W TDP and a 1400 W suggested PSU, which implies a chassis and cooling solution designed for high-power modules. The H100 CNX fits into more conventional server configurations.

The B200 SXM6 also represents a later generation with a denser transistor layout (127.8M / mm² vs 98.3M / mm²) and a newer PCIe interface (6.0 vs 5.0). Its release date of 2024-10-31 places it after the H100 CNX's 2023-03-20 release. The B200 SXM6 has a recorded launch MSRP of 34,999 USD. The H100 CNX has no recorded launch MSRP.

FAQ

Q: Which accelerator has higher FP32 throughput?

A: The NVIDIA B200 SXM6 has higher FP32 throughput at 69.34 TFLOPS, compared to 53.84 TFLOPS for the NVIDIA H100 CNX, a 28.8% advantage.

Q: How do the memory bandwidth figures compare?

A: The B200 SXM6 reaches 8.19 TB/s with HBM3e memory on an 8192-bit bus. The H100 CNX reaches 2.04 TB/s with HBM2e memory on a 5120-bit bus. The B200 SXM6 has approximately 4.01 times the memory bandwidth.

Q: What is the difference in memory capacity?

A: The B200 SXM6 has 180 GB of memory, while the H100 CNX has 80 GB. The B200 SXM6 offers 2.25 times the capacity.

Q: How does power consumption differ?

A: The B200 SXM6 has a TDP of 1000 W and a suggested PSU of 1400 W. The H100 CNX has a TDP of 350 W and a suggested PSU of 750 W. The H100 CNX is the lower-power part.

Q: What are the FP16 throughput figures for each?

A: The B200 SXM6 records 69.34 TFLOPS FP16 at a 1:1 ratio. The H100 CNX records 215.4 TFLOPS FP16 at a 4:1 ratio. The raw FP16 number is higher for the H100 CNX, but the ratio differs between the two.

Q: Which parts were released earlier and later?

A: The H100 CNX was released on 2023-03-20, and the B200 SXM6 was released on 2024-10-31. The H100 CNX lists its successor as Server Blackwell, and the B200 SXM6 lists its predecessor as Server Hopper.