Inference Engine State
STABLE_DIFFUSION_XL
98.2%
12ms
Optimized for leading open-weight architectures
The VRAM King:
Apple Mac Studio (M2 Ultra)
With 192GB of Unified memory, this card is ready for Llama 3.3 70B and deep research tasks. The ultimate choice for training.
NVIDIA GeForce RTX 3090
16GB remains the "golden ratio" for prosumer AI. Perfect for fine-tuning 8B models and stable diffusion.
GPU VRAM Leaderboard
90-Day Price Trend
Estimated Price
$5,599.99
Last Updated: 2026-03-06
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$1,999.99
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$1,799.99
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$749.99
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$1,199.99
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$899.99
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$599.99
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$499.99
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$999.99
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$799.99
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$649.99
Last Updated: 2026-03-06
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$599.99
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$289.99
Last Updated: 2026-03-06
VRAM is King: Why it Matters for Local AI
In traditional gaming, clock speeds and cache are the primary metrics. In Local AI (LLMs, Diffusion, Training), the bottleneck shifts almost entirely to VRAM capacity and Memory Bandwidth (GB/s). If your model doesn't fit in VRAM, it spills to system RAM, killing performance by up to 90%.
The RTX 50-series and RX 9000-series represent a generational leap in FP8 precision efficiency and quantization support. 24GB is currently the "Elite" standard, while 16GB is the baseline for experimental prosumers. Check our guides below to find the perfect match for DeepSeek R1 and Llama 3.