Added recipes for nemotron-nano-3 and qwen3-coder-next

recipes/nemotron-3-nano-nvfp4.yaml

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+# Recipe: Nemotron-3-Nano-NVFP4
+# Nemotron-3-Nano model with NVFP4 quantization support
+# Currently can only be run in solo mode, cluster mode fails with error
+
+recipe_version: "1"
+name: Nemotron-3-Nano-NVFP4
+description: vLLM serving Nemotron-3-Nano-NVFP4 on a SINGLE NODE ONLY!
+
+# HuggingFace model to download (optional, for --download-model)
+model: nvidia/NVIDIA-Nemotron-3-Nano-30B-A3B-NVFP4
+
+# Container image to use
+container: vllm-node
+
+# This model can only run on single node (solo)
+solo_only: true
+
+# No mods required
+mods: 
+  - mods/nemotron-nano
+
+# Default settings (can be overridden via CLI)
+defaults:
+  port: 8000
+  host: 0.0.0.0
+  tensor_parallel: 1
+  gpu_memory_utilization: 0.7
+  max_model_len: 131072
+
+# Environment variables
+env:
+  VLLM_USE_FLASHINFER_MOE_FP4: 1
+  VLLM_FLASHINFER_MOE_BACKEND: "throughput"
+
+# The vLLM serve command template
+command: |
+  vllm serve nvidia/NVIDIA-Nemotron-3-Nano-30B-A3B-NVFP4  \
+     --max-model-len {max_model_len} \
+     --port {port} --host {host} \
+     --trust-remote-code \
+     --enable-auto-tool-choice  \
+     --tool-call-parser qwen3_coder \
+     --reasoning-parser-plugin nano_v3_reasoning_parser.py \
+     --reasoning-parser nano_v3  \
+     --kv-cache-dtype fp8  \
+     --load-format fastsafetensors  \
+     --gpu-memory-utilization {gpu_memory_utilization}