## Turn 1

*   Error message: `llama-server: failed to allocate KV cache`
    *   Requested context size (`ctx`): `262144` (256k tokens)
    *   Available GPU memory: `1024 MiB` (approx. 1 GB)

    *   The user is trying to allocate a KV cache for a very large context window (256k tokens).
    *   The system only has ~1 GB of free VRAM.
    *   KV cache size is proportional to `context_size * number of layers * number of heads * head_dim`. For a 256k context, even with quantization, the memory requirement is significantly higher than 1 GB.

    *   *Root Cause:* Insufficient GPU VRAM to accommodate the requested context window (256k tokens). The requested memory exceeds the available 1024 MiB.

    *   *Action 1:* Reduce the context window size (e.g., to 4096 or 8192) to fit within the available memory.
    *   *Action 2:* Use a smaller model or a more aggressive quantization (e.g., 4-bit or 8-bit) to free up more VRAM, or offload more layers to the CPU (though this will be slow).

    *   *Root Cause:* The requested context window (256,144 tokens) requires significantly more GPU memory than the 1,024 MiB currently available.
    *   *Action 1:* Reduce the `--ctx-size` parameter to a smaller value (e.g., 4096 or 8192).
    *   *Action 2:* Use a smaller model or a more compressed quantization (e.g., Q4_K_M) to reduce the base model's memory footprint.