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Serve local LLMs with real throughput and stable latency
Quick Answer: For most users, the RTX 4090 24GB ($1,600-$2,000) offers the best balance of VRAM, speed, and value. Budget builders should consider the RTX 4060 Ti 16GB ($450-$500), while professionals should look at the RTX 5090 32GB.
vLLM performance is mostly a memory planning problem. You need enough VRAM for model weights plus KV cache, then enough bandwidth to keep latency predictable under concurrent traffic. These picks are optimized for practical self-hosted serving, not just peak benchmark screenshots.
Compare all recommendations at a glance.
| GPU | VRAM | Price | Best For | |
|---|---|---|---|---|
RTX 4060 Ti 16GBBudget Pick | 16GB | $450-$500 | Single-model APIs, 7B-14B production serving | |
RTX 4090 24GBEditor's Choice | 24GB | $1,600-$2,000 | 14B-32B deployments, Higher concurrency | |
RTX 5090 32GBPerformance King | 32GB | $1,999+ | 32B-heavy workloads, High-context serving |
Detailed breakdown of each GPU option with pros and limitations.
Cheapest reliable 16GB option for vLLM. Great for 7B-14B services with controlled concurrency.
Best For
Limitations
Best single-GPU vLLM card for most teams. Strong throughput with enough VRAM for practical context and batching.
Best For
Highest single-card headroom in this stack. Better fit for larger models, bigger KV cache, and bursty traffic.
Best For