Local LLMs vs Cloud APIs: VRAM Limits, Cost Break-Even, and Routing Design

Engineers are advised against relying exclusively on either on-premises hardware or hosted provider APIs, and should instead decide which workloads suit each. The choice depends on three factors: available GPU memory, the token volume at which costs break even, and data isolation requirements. Model weights must fit in memory, and quantization can cut memory needs roughly fourfold, while mixture-of-experts designs reduce per-token compute. Based on the article's estimates, a roughly $2,500 workstation costs about $83 monthly, and pays off against frontier cloud pricing at around 8 million tokens per month. Local deployment offers physical data isolation, whereas hosted APIs rely on contractual safeguards, and on-premises setups must manage growing KV cache demands for long contexts.