Before cloud routing, check whether your GPU can run the LLM
Cloud API routing is useful when a workload needs managed scale, frontier capability, or provider-only features. But for local coding agents, personal assistants, and repeated background tasks, the first question should often be simpler: can the machine already run a good-enough model?
What changed
apiroute.dev now points more directly to localai.apiroute.dev.
The companion site localai.apiroute.dev estimates whether a selected GPU and system RAM can run a local LLM at practical quantization levels. It exposes model data, hardware presets, local application scenarios, and machine-readable guides for agents.
Use local first when
- The workload uses open-weight models such as Llama, Qwen, DeepSeek, or Mistral variants.
- Privacy, offline operation, or fixed hardware cost matters more than managed API convenience.
- The selected quantization fits GPU VRAM with enough headroom for context and runtime overhead.
- A local coding helper, Telegram bot, vault agent, or small routing layer runs many repeated steps.
Use cloud/API when
- The local fit is red or leaves too little VRAM headroom for the intended context.
- The task needs frontier reasoning, provider-hosted vision, high reliability, or managed scaling.
- Long context, fast output, or high-quality final answers matter more than fixed local cost.
- Production routing needs provider SLAs, hosted inference, billing records, or team access controls.
The two-step routing flow
- 1. Check local fit: use localai.apiroute.dev to estimate VRAM, quantization, RAM pressure, and the likely local setup.
- 2. Compare cloud fallback: if local fit is yellow or red, use apiroute.dev to compare paid API routes by cost, context, output limit, and capability.
Agent-readable surfaces
Both tools expose machine-readable files so agents do not have to scrape HTML. localai.apiroute.dev provides local model and hardware planning data; apiroute.dev provides API pricing, route recommendation contracts, token-waste checks, and commercial disclosure boundaries.
Editorial note
Local hardware estimates are planning data, not benchmarks. Real memory use depends on backend, context length, KV cache, driver stack, quantization file, offloading, and runtime settings. Cloud/API prices should still be verified with provider pages before production routing or purchasing decisions.