can you choose between different parameters of the same model with the built-in router like llama-swap? I.e., use Qwen3.5 thinking and instruct without having to reload the model. Thats my main use for llama-swap for qwen3.5 and gemma4 but if its built into llama.cpp, Id look into going that route

my llama-swap config example for qwen3.5-9b with selections between thinking, thinking-coding, and instruct.

  "Qwen3.5-9B":
    cmd: >
      /usr/local/bin/llama-server
       --port ${PORT}
      --host 127.0.0.1
      --model /models/qwen35/Huihui-Qwen3.5-9B.i1-IQ4_XS.gguf
      --mmproj /models/qwen35/Huihui-Qwen3.5-9B.mmproj-f16.gguf
      --cache-type-k q8_0
      --cache-type-v q8_0
      --image-min-tokens 1024 
      --n-gpu-layers auto
      --split-mode none
      --main-gpu 0
      --threads 8
      --threads-batch 8
      --ctx-size 32384
      --flash-attn on 
      --parallel 1 
      --batch-size 2048 
      --ubatch-size 512
      --jinja
      --cache-ram 2048 
    filters:
      stripParams: "temperature, top_p, top_k, min_p, presence_penalty, repeat_penalty"
      
      setParamsByID:
        "${MODEL_ID}:thinking":
          chat_template_kwargs:
            enable_thinking: true
          temperature: 1.0
          top_p: 0.95
          top_k: 20
          min_p: 0.0
          presence_penalty: 1.5
          repeat_penalty: 1.0


        "${MODEL_ID}:thinking-coding":
          chat_template_kwargs:
            enable_thinking: true
          temperature: 0.6
          top_p: 0.95
          top_k: 20
          min_p: 0.0
          presence_penalty: 0.0 
          repeat_penalty: 1.0


        "${MODEL_ID}:instruct":
          chat_template_kwargs:
            enable_thinking: false
          temperature: 0.7
          top_p: 0.8
          top_k: 20
          min_p: 0.0
          presence_penalty: 1.5
          repeat_penalty: 1.0  =