GPU Value Finder
Rank GPUs by dollars per GB of VRAM for your budget and model size — the cheapest path to the VRAM you need.
- Best for
- best value GPU for local LLM
- Main output
- GPUs ranked by memory per dollar
Pick one focused calculator or planner for the decision in front of you: memory fit, hardware comparison, operating cost, platform choice, used-GPU risk, power planning, parts sizing, or workload matching.
Rank GPUs by dollars per GB of VRAM for your budget and model size — the cheapest path to the VRAM you need.
Pick the model you want to run and see which unified-memory mini PC (Strix Halo, DGX Spark, Framework, Mac) can run it — ranked cheapest-first.
Compare two GPUs, Macs, or multi-GPU tiers on memory, planning price, power, and comfort zone.
Estimate model memory needs from parameters, quantization, and context length before choosing hardware.
Estimate what fits across VRAM and system RAM, an approximate llama.cpp layer split, and the likely offload severity.
Estimate full, LoRA, or QLoRA memory with explicit assumptions and a conservative GPU reserve.
Estimate monthly and yearly power cost from GPU preset, runtime, utility rate, or custom watt draw.
Compare hardware cost plus electricity against a recurring cloud or subscription AI bill.
Choose the cleaner platform path from CUDA needs, model size, noise sensitivity, and workflow priority.
Score listing, return-window, stress-test, VRAM-test, power, fit, and value risks before buying used.
Turn hardware wattage into PSU target, heat output, thermal risk, and noise guidance.
Size CPU, RAM, PSU, and storage around the GPU or unified-memory tier you plan to use.
Start with the job: coding, quiet Mac use, image generation, large LLMs, or budget experimentation.
The tool pages are separated by reader job, not by keyword variants. Use the VRAM calculator for model memory, the electricity calculator for operating cost, the break-even calculator for ownership payback, and the build planners when the physical rig or workload path is the real question.