# NVIDIA Quadro P4000: 8GB and the 105W single-slot board

Specifications and qualification steps for NVIDIA Quadro P4000, covering memory variants, LLM backends, Cycles and system integration.

Author: Retrivium team
Updated: 2026-11-02
Canonical URL: https://retrivium.ai/journal/quadro-p4000-llm-rendering/
Language: en

NVIDIA Quadro P4000 is assessed here as an exact Pascal board configuration. Its published 8 GB capacity is the starting point for a workload qualification, not a measured serving or rendering result.

## Exact model and memory variants

P4000 is an 8 GB GDDR5 Pascal card rated105 W in an active full-height single-slot design. It predates the RTX 4000 generations.

| Variant | Memory | Published board power | Cooling / format |
|---|---|---|---|
| NVIDIA Quadro P4000 | 8 GB GDDR5 | 105 W | Active; Full-height single slot |

Specifications: [Official product/support documentation](https://www.nvidia.com/content/dam/en-zz/Solutions/design-visualization/quadro-product-literature/301283-DS-NV-Quadro-Pascal-P4000-US-03Feb17-NV-fnl-WEB.pdf).

## LLM backend and memory budget

PascalCC6.1 is outside current vLLM support. Evaluate quantized GGUF work with an explicit llama.cpp sm_61 CUDA12.x build, recorded driver and measured full/partial offload; capacity is not evidence of modern kernel support.

The current vLLM requirement is compute capability7.5 or higher; this architecture is below that floor.

Compatibility evidence: [llama.cpp CUDA build configuration](https://github.com/ggml-org/llama.cpp/blob/master/ggml/src/ggml-cuda/CMakeLists.txt) and the [NVIDIA architecture matrix](https://docs.nvidia.com/datacenter/tesla/drivers/cuda-toolkit-driver-and-architecture-matrix.html). The current [vLLM capability floor](https://docs.vllm.ai/en/stable/getting_started/installation/gpu/) excludes this architecture.

## Cycles and batch rendering

CUDA/OptiX rendering is conditional on the verified Cycles5.2 requirements and actual scene fit. Pascal has no RTX RT cores, and GPU OIDN has a higher capability floor than rendering itself.

[Blender 5.2 LTS GPU rendering manual](https://docs.blender.org/manual/en/latest/render/cycles/gpu_rendering.html).

## Integration into a server or workstation

Single-slot mechanical fit can make an existing host usable for a controlled experiment, but not automatically qualified for sustained service. Preserve105 W specification context and intake clearance, alongside the old-toolchain recovery procedure.

## A concrete qualification scenario

An administrator finds P4000 in a narrow workstation and wants to distinguish a software failure from insufficient8 GB capacity. Run the retained architecture-specific runtime first with a tiny control artifact. Then vary only context for the intended test. Render a separate small scene afterward. Record the failure stage and selected backend so that a package rejection is not mislabeled as out-of-memory.

## 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 P4000; physical variant and reported device identifier |
| Memory boundary | 8 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 |

A narrow single-slot installation does not remove the need to retain the Pascal driver and rebuildable inference artifact alongside the 8 GB observation.

Further reading: [Build llama.cpp CUDA binaries for multiple GPU architectures](/journal/llama-cpp-portable-cuda-build/), [Used GPUs: which checks are needed before a pilot?](/journal/used-gpu-health-check/), [NVIDIA and AMD GPU catalogue](/journal/nvidia-amd-gpu-catalog/).