The GPU comparison chart compares major GPUs for machine learning and gaming workloads. Filter by use case and minimum VRAM to find the right GPU for local LLM inference, ML training, or high-performance gaming.
Choosing a GPU for LLM Inference
For local LLM inference, VRAM is the primary constraint. Rule of thumb: 2 bytes × model parameters for FP16 precision. A 7B model needs ~14GB VRAM. A 13B model needs ~26GB. The RTX 4090 (24GB) is the best consumer option for 7B-13B models.
ML Training vs Inference
Training needs more VRAM and compute than inference — typically 6-10x more memory for gradients and optimizer states. For serious training, cloud GPUs (A100, H100) are more practical than consumer hardware. For inference of open-source models, consumer RTX 4090 or workstation A4000/A6000 cards offer good price/performance.
FAQ
Is this GPU comparison tool free?
Yes, completely free with no signup required.
How much VRAM do I need for LLM inference?
Rule of thumb: multiply model parameters by 2 bytes for FP16, or 1 byte for INT8 quantization. A 7B parameter model needs ~14GB VRAM in FP16 or ~7GB in INT8. A 13B model needs ~26GB FP16. For production inference with batching, add 20-30% overhead.
What GPU should I buy for local LLM inference?
For running 7B-13B models locally, an RTX 4090 (24GB VRAM) or RTX 4080 (16GB) are popular consumer choices. For larger models (70B), you'll need multiple GPUs or cloud compute. The RTX 4090 offers the best consumer price/performance ratio for local AI.
What is TFLOPS and why does it matter?
TFLOPS (teraflops) measures floating-point operations per second — a proxy for raw compute speed. Higher TFLOPS means faster matrix multiplications, which is the core operation in neural network inference and training. However, memory bandwidth and VRAM capacity often bottleneck LLM performance more than raw FLOPS.
Is the pricing data current?
GPU prices fluctuate with market conditions and availability. The price tiers shown are approximate ranges based on typical market pricing. Always check current prices on major retailers before purchasing.