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Report CPU, system RAM, GPU and VRAM separately. A working mixed configuration is evidence for that workload, not a promise of fully GPU-resident performance.
If Ollama reports CPU and GPU use, the model may be partially placed in system memory and partially on the accelerator. That can be a supported configuration rather than a defect. Determine actual placement and judge whether its quality and latency suit the task.
Inspect the loaded model
After a known request, use ollama ps and save processor placement, context and retention information. Observe the system at a defined point after loading. A momentary activity chart does not show the full allocation of a loaded model.
Include the exact tag and installed Ollama version. Two files with the same family name can have different precision or size. A useful report identifies the artifact and request settings, so another operator can compare the same work rather than a vaguely similar model.
Separate capacity from speed
Additional system RAM can make more storage and partial-placement options possible when supported by the backend. It does not become interchangeable with VRAM. A machine can run an artifact that exceeds its GPU-only capacity yet take longer to respond.
For example, a workstation with substantial RAM and a smaller card may execute a heavier model in a mixed mode. Whether that is useful depends on the required result and waiting time. Do not label the machine unsuitable merely because it is not fully GPU-resident, or describe it as equivalent to a larger accelerator.
Identify why placement changed
Check artifact size, context, simultaneous requests and other GPU processes. Fix the model and compare two moderate context settings. Inspect the placement and timing after each change rather than changing several variables at once.
If the GPU is shared with other authorised work, record its initial occupancy. Close only your own unnecessary tasks or arrange a test window. The same configuration can behave differently when another user needs the card, so the tested schedule belongs in the operating profile.
Measure whether mixed execution is useful
Prepare several similarly sized tasks with verifiable answers. Record first-answer delay, total completion, memory and the responsiveness of other agreed workloads. A delay acceptable for batch processing may be unsuitable for an interactive assistant.
Repeat from a fresh application session and preserve the working settings. If considering a larger GPU, specify which limitation it should improve: full placement, context or concurrency. That makes the equipment discussion concrete instead of treating every mixed result as an automatic reason to purchase more hardware.
Turn the check into a practical next step
Report CPU, system RAM, GPU and VRAM separately. A working mixed configuration is evidence for that workload, not a promise of fully GPU-resident performance.
For the documented details, consult the primary documentation; configuration reference. Continue with ollama does not use gpu and ollama context length setting.