In this article
GP100 requires its own sm_60 qualification and source-specific235W board record.
NVIDIA Quadro GP100 is assessed here as an exact Pascal board configuration. Its published 16 GB capacity is the starting point for a workload qualification, not a measured serving or rendering result.
Exact model and memory variants
Quadro GP100 has16 GB HBM2 ECC and a 235 W active dual-slot specification. ItsPascalCC6.0 differs from theCC6.1 P-series and from TeslaP100 product identities.
| Variant | Memory | Published board power | Cooling / format |
|---|---|---|---|
| NVIDIA Quadro GP100 | 16 GB HBM2 ECC | 235 W | Active; 4.4 x 10.5 in; full-height dual slot |
Specifications: Official product/support documentation.
LLM backend and memory budget
CC 6.0 is below the current vLLM floor. A custom validated llama.cpp CUDA12.x sm_60 build may support bounded GGUF work; do not substitute the default sm_61 Pascal target or infer Tensor cores.
The current vLLM requirement is compute capability7.5 or higher; this architecture is below that floor.
Compatibility evidence: llama.cpp CUDA build configuration and the NVIDIA architecture matrix. The current vLLM capability floor excludes this architecture.
Cycles and batch rendering
Pascal Cycles candidate under the verified architecture floor; no RTX hardware ray tracing. Verify the chosen backend and scene memory, with application support required for any NVLink distributed memory.
Blender 5.2 LTS GPU rendering manual.
Integration into a server or workstation
Use the individual GPU datasheet235 W field when identifying this board. A generic historical power guide has a different250 W entry; mixing those contexts would make the installation record ambiguous. Retain the exact source and active-cooling layout.
A concrete qualification scenario
A reproducibility test fails on GP100 after an artifact was built only for another Pascal target. Record the physicalCC6.0 identity and rebuild a controlled sm_60 CUDA12.x artifact before changing weights. Validate the same model/context and reference scene afterward. Preserve both failed and corrected build identities; a successful correction demonstrates this execution path, not universal compatibility with all contemporary packages.
The evidence to retain
Keep an ordinary qualification record with the actual test outputs.
Identify the tested variant, software build and execution mode before entering observations. Leave unavailable measurements explicitly unknown.
The fields below separate published specifications from observed allocation and job completion, so a later operator can repeat the same case.
| Evidence field | What this profile must retain |
|---|---|
| Hardware identity | NVIDIA Quadro GP100; physical variant and reported device identifier |
| Memory boundary | 16 GB published; observed free memory before and after loading |
| Inference artifact | Exact weights digest, quantization, context and offload configuration |
| Render artifact | Scene digest, renderer version, backend and denoising setting |
| System envelope | Driver, container/build digest, enclosure and cooling configuration |
| Completion evidence | Application exit status, output validity and observed memory failures |
The sm_60 GP100 target must remain explicit; another Pascal artifact targeting sm_61 is not equivalent evidence for this16 GB board.
Further reading: Build llama.cpp CUDA binaries for multiple GPU architectures, Reproducible inference stacks: preserving a GPU pilot’s result, NVIDIA and AMD GPU catalogue.