feat: Variet Engine v1.0 + 5-model tuning complete

Phase 01 (LLM Tuning):
- Gemma4 26B: 74.65 t/s (fast)
- Qwen 35B: 61.62 t/s (balanced)
- Gemma4 31B: 16.0 t/s (deep-coder)
- Qwen 27B: 16.7 t/s (deep-logic)
- Qwen 122B: 8.95 t/s (ultra, GPU 1 only)

Phase 02 (API Engine):
- FastAPI reverse proxy on port 8000
- /engine/switch hot-swap with 503 protection
- config/engine_models.json as single source of truth
- Replaced 4 individual .bat files with unified engine

File cleanup:
- scripts/ 85 files -> 9 + _archive/
- Root .bat files -> _archive/

scripts/_archive/help_gpu_flags.txt

@@ -0,0 +1,31 @@
+ggml_cuda_init: found 2 CUDA devices (Total VRAM: 24575 MiB):
+  Device 0: NVIDIA GeForce RTX 3060, compute capability 8.6, VMM: yes, VRAM: 12287 MiB
+  Device 1: NVIDIA GeForce RTX 3060, compute capability 8.6, VMM: yes, VRAM: 12287 MiB
+-dev,  --device <dev1,dev2,..>          comma-separated list of devices to use for offloading (none = don't
+                                        use --list-devices to see a list of available devices
+                                        (env: LLAMA_ARG_DEVICE)
+--list-devices                          print list of available devices and exit
+-ot,   --override-tensor <tensor name pattern>=<buffer type>,...
+                                        override tensor buffer type
+                                        (env: LLAMA_ARG_OVERRIDE_TENSOR)
+-cmoe, --cpu-moe                        keep all Mixture of Experts (MoE) weights in the CPU
+-ncmoe, --n-cpu-moe N                   keep the Mixture of Experts (MoE) weights of the first N layers in the
+-sm,   --split-mode {none,layer,row}    how to split the model across multiple GPUs, one of:
+                                        - layer (default): split layers and KV across GPUs
+                                        - row: split rows across GPUs
+                                        (env: LLAMA_ARG_SPLIT_MODE)
+-ts,   --tensor-split N0,N1,N2,...      fraction of the model to offload to each GPU, comma-separated list of
+                                        (env: LLAMA_ARG_TENSOR_SPLIT)
+-mg,   --main-gpu INDEX                 the GPU to use for the model (with split-mode = none), or for
+                                        intermediate results and KV (with split-mode = row) (default: 0)
+-fit,  --fit [on|off]                   whether to adjust unset arguments to fit in device memory ('on' or
+                                        target margin per device for --fit, comma-separated list of values,
+                                        single value is broadcast across all devices, default: 1024
+--check-tensors                         check model tensor data for invalid values (default: false)
+--op-offload, --no-op-offload           whether to offload host tensor operations to device (default: true)
+-otd,  --override-tensor-draft <tensor name pattern>=<buffer type>,...
+                                        override tensor buffer type for draft model
+-cmoed, --cpu-moe-draft                 keep all Mixture of Experts (MoE) weights in the CPU for the draft
+-ncmoed, --n-cpu-moe-draft N            keep the Mixture of Experts (MoE) weights of the first N layers in the
+-devd, --device-draft <dev1,dev2,..>    comma-separated list of devices to use for offloading the draft model
+                                        use --list-devices to see a list of available devices