Bosgame M5 Makes Local AI Stack Viable

Strong use case, but the main constraint is likely orchestration quality and memory/latency tradeoffs, not just raw model choice.

• –The 128GB unified-memory headroom is the real unlock here; it broadens model selection and makes multi-model routing much more realistic than on 16GB.
• –The tiered design makes sense for an MCP platform: keep the cheap model hot for chat/tool calls, reserve heavier models for slower paths, and avoid waking the large model on every request.
• –The biggest risk is overestimating live concurrency on a single box once KV cache, context length, and tool-call overhead start stacking up.
• –vLLM on Linux is a reasonable first pass, but the router layer and admission control will matter more than the exact trio of models.
• –For this workload, the right benchmark is not “can it run,” but “can it stay responsive for one active user plus a few bursty background jobs without queue collapse.”