MiniMax M2.7 hits context wall

This reads like a reminder that for agent workflows, context budget is the real bottleneck, not raw model quality or even token speed.

• –SSD/mmap spillover was a dead end in practice: it extended memory on paper, but latency and pauses made the setup unusable.
• –10k context caused truncated tool outputs and recursive compaction, which is fatal for search-heavy tasks that need room for prompts, results, and reasoning.
• –40k in-memory improved throughput, but Hermes still timed out on multi-step research, showing that model capability cannot compensate for a cramped working set.
• –The takeaway for local research rigs is blunt: if you want reliable tool use, prioritize VRAM/RAM for a large context window before chasing more parameters or higher raw TPS.