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Hardware
GPU Infrastructure
Choose the right GPU for LLM inference and training. Compare consumer, datacenter, and cloud GPU options. Understand VRAM requirements and costs.
NVIDIA GPU Comparison
| GPU | VRAM | FP16 TFLOPS | Type | Cost (New) |
|---|---|---|---|---|
| RTX 4090 | 24GB | ~83 | Consumer | $1,600 |
| RTX 4080 | 16GB | ~49 | Consumer | $1,000 |
| A10G | 24GB | ~31 | Cloud (AWS) | ~$1/hr |
| L4 | 24GB | ~121 | Cloud (GCP) | ~$0.80/hr |
| A100 40GB | 40GB | ~312 | Datacenter | ~$2/hr |
| A100 80GB | 80GB | ~312 | Datacenter | ~$3/hr |
| H100 80GB | 80GB | ~990 | Datacenter | ~$4/hr |
| H200 141GB | 141GB | ~990 | Datacenter | ~$6/hr |
VRAM Requirements by Model Size
| Model | FP16 | Q8 (8-bit) | Q4 (4-bit) | Recommended GPU |
|---|---|---|---|---|
| 7B | 14GB | 7GB | 4GB | RTX 4060 Ti 16GB |
| 13B | 26GB | 13GB | 7GB | RTX 4090 24GB |
| 30-34B | 68GB | 34GB | 17GB | 2x RTX 4090 or A100 |
| 70B | 140GB | 70GB | 35GB | 2x A100 80GB or H100 |
| 405B | 810GB | 405GB | 202GB | 8x H100 (DGX) |
π‘ Formula: VRAM (FP16) β Parameters Γ 2 bytes. Add ~20% overhead for KV cache during inference.
Cloud GPU Pricing (On-demand)
| Provider | GPU | Instance | $/hr |
|---|---|---|---|
| AWS | 1x A10G | g5.xlarge | $1.00 |
| AWS | 8x A100 | p4d.24xlarge | $32.77 |
| GCP | 1x L4 | g2-standard-4 | $0.70 |
| GCP | 8x H100 | a3-highgpu-8g | $32.00 |
| Azure | 1x A100 | NC24ads_A100_v4 | $3.67 |
| Lambda Labs | 1x A100 | gpu_1x_a100 | $1.10 |
| RunPod | 1x A100 | On-demand | $1.64 |
Quantization for Less VRAM
GGUF (llama.cpp)
CPU + GPU hybrid. Q4_K_M is the sweet spot for quality vs size.
AWQ
4-bit, GPU-optimized. Best for vLLM production inference.
GPTQ
4-bit, widely supported. Good for consumer GPUs.
FP8
8-bit, minimal quality loss. Requires H100/Ada GPUs.
Build vs Rent Decision
| Factor | Build (Buy GPUs) | Rent (Cloud) |
|---|---|---|
| Upfront Cost | High ($10K-$500K+) | None |
| Break-even | ~6-12 months 24/7 usage | Never (pay per use) |
| Best For | Continuous training, privacy | Burst workloads, experimentation |
| Maintenance | You handle everything | Provider handles |