In this article
H800 assessment needs the exact OEM configuration: PCIe and SXM 80 GB, or NVL 94 GB per GPU. Similar names do not establish identical host or interconnect requirements.
Use the installed OEM identity
Lenovo documents withdrawn H800 PCIe products with 80 GB and NVL products with 94 GB HBM3 per GPU and a 400 W board limit. Dell separately documents H800 SXM configurations. These records identify an existing machine; they do not prove current availability. Record the server identity, accelerator part number and mounting format. Two 80 GB listings do not establish identical memory or interconnect behaviour. NVL capacity is per GPU, not a combined pair total. The SXM power figure belongs to that module and must not be assigned to PCIe cards.
| Variant | Local memory, GB | Memory type | Published board power, W |
|---|---|---|---|
| H800 PCIe | 80 | HBM2e | 350 |
| H800 SXM5 | 80 | HBM3 | 700 |
| H800 NVL per GPU | 94 | HBM3 | 400 |
The product or OEM specification establishes the configuration: manufacturer source.
Qualify Hopper software without renaming the device
H800 belongs to the Hopper family, but an inference environment must be qualified on the actual accelerator. Do not rename a configuration to H100 in a benchmark record because software shares an architecture path. Preserve the runtime, driver, engine package, model revision and selected precision. Compare a small correctness workload before testing concurrency. Kernel support and numerical behaviour are version-sensitive; the existence of a CUDA context does not confirm that the chosen quantized checkpoint runs through its intended optimised implementation.
The software boundary is documented in the inference compatibility reference.
Measure the interconnect actually present
A distributed inference configuration needs its own connectivity map. The capacity label says nothing about which peers can exchange data directly or how collectives are scheduled. Test the intended tensor-parallel arrangement, inspect device placement and retain communication measurements. An H100 result should not be copied into an H800 table, even when model and memory size match. For a mostly single-device workload, compare request latency and cache pressure independently from the multi-device test so a communication bottleneck is not mistaken for insufficient local memory.
Keep rendering claims tied to an engine
An H800 CUDA workload does not establish an RTX graphics feature set. Rendering evaluation needs the exact engine, plugin versions and supported backend. For Cycles, test headless execution with a representative scene and verify memory allocation, material output and completion under sustained operation. The scene budget includes more than source file size. Geometry expansion and acceleration structures may change peak memory. A successful frame is evidence for that rendering setup, not a universal claim about interactive graphics or all server rendering products.
Renderer requirements are separate in the Cycles GPU manual.
Document the limits of an archived deployment
An installed H800 server should retain its OEM firmware, cooling and power configuration in the acceptance record. Recheck stability after a driver or engine update rather than treating an archived product specification as permanent software certification. Track failed allocations, hardware errors and controlled restart recovery. Where a field has not been established from the matching primary document, leave it unresolved. This informational profile does not announce a Retrivium hardware inventory, a purchase offer or completed OpenRouter provider approval.
Related reading: RAM and VRAM and a reproducible inference benchmark. GPU catalogue records the scope, model variants and unresolved specifications.