apiVersion: serving.kserve.io/v1beta1 kind: InferenceService metadata: annotations: serving.kserve.io/deploymentMode: RawDeployment labels: app.kubernetes.io/name: llm-reasoning app.kubernetes.io/part-of: llm-serving name: reasoning namespace: llm-serving spec: predictor: containers: - args: - --model=unsloth/DeepSeek-R1-Distill-Qwen-32B-bnb-4bit - --served-model-name=reasoning - --quantization=bitsandbytes - --dtype=float16 - --kv-cache-dtype=auto - --tensor-parallel-size=1 - --max-model-len=16384 - --gpu-memory-utilization=0.90 - --max-num-seqs=4 - --enable-chunked-prefill - --enable-prefix-caching - --reasoning-parser=deepseek_r1 - --host=0.0.0.0 - --port=8080 env: - name: VLLM_USE_FLASHINFER_SAMPLER value: '0' - name: VLLM_ATTENTION_BACKEND value: TRITON_ATTN - name: HF_HOME value: /mnt/models image: vllm/vllm-openai:v0.11.0@sha256:014a95f21c9edf6abe0aea6b07353f96baa4ec291c427bb1176dc7c93a85845c name: kserve-container ports: - containerPort: 8080 protocol: TCP readinessProbe: httpGet: path: /health port: 8080 periodSeconds: 10 resources: limits: cpu: '16' memory: 16Gi nvidia.com/gpu: '1' requests: cpu: '8' memory: 8Gi nvidia.com/gpu: '1' startupProbe: failureThreshold: 80 httpGet: path: /health port: 8080 periodSeconds: 15 volumeMounts: - mountPath: /mnt/models name: models - mountPath: /dev/shm name: shm deploymentStrategy: type: Recreate maxReplicas: 2 minReplicas: 2 nodeSelector: kubernetes.io/hostname: worker-1 runtimeClassName: nvidia volumes: - name: models persistentVolumeClaim: claimName: llm-models - emptyDir: medium: Memory sizeLimit: 2Gi name: shm