# Project information
site_name: MASS-Base
site_url: https://docs.gpustack.ai
site_author: MASS-Base
site_description: >-
  MASS-Base is an open-source GPU cluster manager designed for efficient AI model deployment.
  It lets you run models efficiently on your own GPU hardware by choosing the best inference engines,
  scheduling GPU resources, analyzing model architectures, and automatically configuring deployment parameters.

# Repository
repo_name: gpustack/gpustack
repo_url: https://github.com/gpustack/gpustack

# Copyright
copyright: Copyright &copy; 2026 GPUStack.ai

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nav:
  - Home:
      - Overview: overview.md
      - Quickstart: quickstart.md
      - Installation:
          - Requirements: installation/requirements.md
          - Installation: installation/installation.md
          - Air-Gapped Installation: installation/air-gapped.md
          - Uninstallation: installation/uninstallation.md
      - Upgrade: upgrade.md
      - Migration: migration.md
      - User Guide:
          - Playground:
              - Playgound: user-guide/playground/index.md
              - Chat: user-guide/playground/chat.md
              - Image: user-guide/playground/image.md
              - Audio: user-guide/playground/audio.md
              - Embedding: user-guide/playground/embedding.md
              - Rerank: user-guide/playground/rerank.md
          - Model Catalog: user-guide/model-catalog.md
          - Model Deployment Management: user-guide/model-deployment-management.md
          - Model Route Management: user-guide/model-route-management.md
          - Model Provider Management: user-guide/model-provider-management.md
          - Inference Backend Management: user-guide/inference-backend-management.md
          - Built-in Inference Backends: user-guide/built-in-inference-backends.md
          - Compatibility Check: user-guide/compatibility-check.md
          - Model File management: user-guide/model-file-management.md
          - Cluster Management: user-guide/cluster-management.md
          - Cloud Credential Management: user-guide/cloud-credential-management.md
          - API Key Management: user-guide/api-key-management.md
          - User Management: user-guide/user-management.md
          - Single Sign-On (SSO) Authentication: user-guide/sso.md
          - Observability: user-guide/observability.md
          - Benchmarking: user-guide/benchmarking.md
      - Using Models:
          - Using Large Language Models: using-models/using-large-language-models.md
          - Using Vision Language Models: using-models/using-vision-language-models.md
          - Using Embedding Models: using-models/using-embedding-models.md
          - Using Reranker Models: using-models/using-reranker-models.md
          - Using Image Generation Models: using-models/using-image-generation-models.md
          - Using Audio Models: using-models/using-audio-models.md
      - Tutorials:
          - Running DeepSeek R1 671B with Distributed vLLM: tutorials/running-deepseek-r1-671b-with-distributed-vllm.md
          - Running DeepSeek R1 671B with Distributed Ascend Mindie: tutorials/running-deepseek-r1-671b-with-distributed-ascend-mindie.md
          - Inference On CPUs: tutorials/inference-on-cpus.md
          - Inference with Tool Calling: tutorials/inference-with-tool-calling.md
          - Using Custom Inference Backend: tutorials/using-custom-backends.md
          - Adding a GPU Cluster Using DigitalOcean: tutorials/adding-gpucluster-using-digitalocean.md
          - Adding a GPU Cluster Using Kubernetes: tutorials/adding-gpucluster-using-kubernetes.md
          - Managing Model Routes: tutorials/managing-model-routes.md
      - Integrations:
          - Inference APIs: integrations/inference-apis.md
          - Integrate with Claude Code: integrations/integrate-with-claude-code.md
          - Integrate with Dify: integrations/integrate-with-dify.md
          - Integrate with RAGFlow: integrations/integrate-with-ragflow.md
          - Integrate with CherryStudio: integrations/integrate-with-cherrystudio.md
          - Integrate with OpenClaw: integrations/integrate-with-openclaw.md
          - Integrate with n8n: integrations/integrate-with-n8n.md
          - Integrate with MaxKB: integrations/integrate-with-maxkb.md
      - Architecture: architecture.md
      - Scheduler: scheduler.md
      - Troubleshooting: troubleshooting.md
      - FAQ: faq.md
      - API Reference: api-reference.md
      - CLI Reference:
          - Start: cli-reference/start.md
          - Download Tools: cli-reference/download-tools.md
          - Reload Config: cli-reference/reload-config.md
          - List Images: cli-reference/list-images.md
          - Save Images: cli-reference/save-images.md
          - Load Images: cli-reference/load-images.md
          - Copy Images: cli-reference/copy-images.md
      - Environment Variables: environment-variables.md
  - Inference Performance Lab:
      - Overview: performance-lab/overview.md
      - Optimizing Throughput:
          - Qwen3.5-35B-A3B:
              - H200: performance-lab/qwen3.5-35b-a3b/h200.md
          - Qwen3.5-9B:
              - H100: performance-lab/qwen3.5-9b/h100.md
          - GLM-4.5-Air:
              - A100: performance-lab/glm-4.5-air/a100.md
              - H100: performance-lab/glm-4.5-air/h100.md
          - GLM-4.x:
              - A100: performance-lab/glm-4.x/a100.md
              - H100: performance-lab/glm-4.x/h100.md
              - H200: performance-lab/glm-4.x/h200.md
          - GPT-OSS-20B:
              - A100: performance-lab/gpt-oss-20b/a100.md
              - H100: performance-lab/gpt-oss-20b/h100.md
          - GPT-OSS-120B:
              - A100: performance-lab/gpt-oss-120b/a100.md
              - H100: performance-lab/gpt-oss-120b/h100.md
          - DeepSeek-R1:
              - H200: performance-lab/deepseek-r1/h200.md
          - DeepSeek-V3.2:
              - H200: performance-lab/deepseek-v3.2/h200.md
          - Qwen3-8B:
              - 910B: performance-lab/qwen3-8b/910b.md
          - Qwen3-14B:
              - A100: performance-lab/qwen3-14b/a100.md
              - H100: performance-lab/qwen3-14b/h100.md
          - Qwen3-32B:
              - A100: performance-lab/qwen3-32b/a100.md
              - H100: performance-lab/qwen3-32b/h100.md
          - Qwen3-30B-A3B:
              - 910B: performance-lab/qwen3-30b-a3b/910b.md
          - Qwen3-235B-A22B:
              - A100: performance-lab/qwen3-235b-a22b/a100.md
              - H100: performance-lab/qwen3-235b-a22b/h100.md
      - Optimizing Latency:
          - Qwen3.5-35B-A3B:
              - H200: performance-lab/qwen3.5-35b-a3b/h200-latency.md
          - Qwen3.5-9B:
              - H100: performance-lab/qwen3.5-9b/h100-latency.md
          - Qwen3-8B:
              - H100: performance-lab/qwen3-8b/h100-latency.md
      - References:
          - The Impact of Quantization on vLLM Inference Performance: performance-lab/references/the-impact-of-quantization-on-vllm-inference-performance.md
          - Evaluating LMCache Prefill Acceleration in vLLM: performance-lab/references/evaluating-lmcache-prefill-acceleration-in-vllm.md
  - Container Image Selector: image-selector/index.html
