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Do not merge RTX 3080 10/12 GB into one memory budget; keep the variant and reference power explicit.
Two ordinary RTX 3080 variants
The official RTX 3080 exists with 10 GB and 12 GB GDDR6X. Reference board power differs: 320 W and 350 W respectively. The RTX 3080 Ti is a separate model even though its capacity is familiar. The table describes memory per GPU. Establish the actual installed variant rather than inferring it from an abbreviated name. Preserve AIB design separately. Check dimensions, supply and cooling against that board’s documentation; reference figures are not measured energy for a complete job or specifications for every partner design. Inventory precision comes before workload admission.
| Official variant | Memory per GPU | Memory type | Board power | Evidence |
|---|---|---|---|---|
| NVIDIA GeForce RTX 3080 — 10 GB | 10 GB | GDDR6X | 320 W | Specification |
| NVIDIA GeForce RTX 3080 — 12 GB | 12 GB | GDDR6X | 350 W | Specification |
Establish each LLM envelope
Match vLLM requirements to model revision, dtype and selected backend. Ampere clears the hardware floor but does not certify every quantization kernel. Test the same bounded workload on both 3080 variants first, holding context and output constant. Examine each operating boundary separately afterward. A configuration passing on 12 GB must not automatically be sent to a 10 GB worker. Weights, KV cache and runtime structures need to fit together or use explicitly described offload. More memory does not establish a predetermined context or throughput gain, since budget components behave differently in the selected engine. Preserve the actual acceptance parameters.
Test the Cycles scene twice
Blender Cycles offers CUDA/OptiX paths with driver and memory requirements. Preserve one project and its assets so both 3080 variants receive matching input. Record selected device, VRAM/RAM and image. If the smaller card finishes through host memory, that is another mode rather than equivalent local fit. Supporting backends can use RTX hardware tracing, which certifies no arbitrary renderer. Change one asset group in another experiment to investigate memory limits. Gaming results and scene file size cannot replace runtime footprint measurements or predetermine the largest supported scene. Retain evidence for each variant separately.
Classify queue workers precisely
The registry retains model name, capacity, AIB identity and device identifier. Admission uses a verified workload class instead of universal RTX 3080 capacity. Enumeration indices can change, so confirm assignment by identity. After closing an engine, verify release of memory ownership before passing the GPU to rendering. Multiple cards do not automatically pool VRAM. Evaluate supply and airflow per board and host; shared RAM and storage can constrain work too. Useful diagnosis does not require forced clocks or disabled protections. Keep the normal operating conditions documented so another worker can reproduce the task configuration.
Check incorrect assignment safely
The package contains task manifests, both inventory records and actual worker selection logs. Verify that a workload unvalidated for the 10 GB envelope cannot pass admission simply because its model name matches. This is a bounded rule check rather than an attempt to exhaust the GPU. If assignment is correct but runtime fails, investigate backend and allocations. The decision describes admissible RTX 3080 10/12 GB routes for selected LLMs and scenes. It promises neither arbitrary checkpoint fit nor automatic pooled memory or a known acceleration ratio. Its value is preserving the important distinction between two official variants.
Coding LLMs on 12GB VRAM: Budget Context and Headroom · Build a GPU Inventory CSV with nvidia-smi · GPU catalog