Custom MCP with a variety of functions, I have different Qwen profiles with a variety of subagent numbers and cache pools, my default is 192k pool with 64k initial context that can grow 32k at a time up to 128k, allowing 3x64k, 2x96k or 1x128k and 1x64k subagents. Qwen uses Pi harness. Model I use specifically is ukisai/Swift-1.5-Qwen3.8-27B-GSQ-RCO-GGUF
What hardware and inference engine do you use? On my Radeon R9700, at least with llama.cpp and some others, the GPU provides as many tok/sec with a single stream as with concurrent ones, so it's just as fast and supports longer contexts to swap contexts to RAM on turn boundaries.
I've experienced the same. Are you saying you're using different context sizes with parallel invocations or just that it's possible to have longer contexts? I've been setting my config to ensure I don't blow out context server side but have not tried to manage it client side.
Why not using a proxy in claudecode to forward all the claude-* model to anthropic as a standard proxy forwarder and route other models to other providers (openrouter, vllm, ..)? This way Claude's model can get all the context from other models as all in the same harness. To use other models than claude-* you can use agents files.
Ps: as you won't use your proxy to distill or alter claudecode requests to anthropic you should be compliant with anthropic rules.
Probably depends if you're trying to treat it as "subagent(s)" or as two different models working on the same stream of thought/context.
Both are, I think, valid options. Depends on the workflow you're looking for.