{
  "schema_version": "openagent.resource.v1",
  "id": "res_deepseek_r1",
  "slug": "deepseek-r1",
  "status": "published",
  "identity": {
    "name": "DeepSeek-R1",
    "one_liner": "Open reasoning model family for developers testing long-form reasoning, coding, and local AI workflows.",
    "short_description": "DeepSeek-R1 is an MIT-licensed open reasoning model release from DeepSeek, widely used by developers who want to evaluate transparent reasoning behavior, distilled model variants, and local or self-hosted inference paths."
  },
  "classification": {
    "resource_type": "model",
    "primary_category": "models",
    "subcategories": [
      "open-weights",
      "local-ai",
      "local-inference",
      "self-hosted",
      "research"
    ]
  },
  "positioning": {
    "why_it_matters": "DeepSeek-R1 matters because it made reasoning-oriented open models feel practical for more teams. It gives builders a concrete alternative to closed reasoning APIs when they need model weights, reproducible evaluation, local experiments, or self-hosted deployment.",
    "best_for": [
      "Developers comparing open reasoning models against hosted reasoning APIs",
      "Teams testing local or self-hosted coding and analysis workflows",
      "Researchers studying distilled reasoning models and evaluation behavior"
    ],
    "not_for": [
      "Users who want a fully managed consumer chatbot",
      "Teams that cannot run their own model evaluation, safety checks, or inference stack"
    ],
    "use_cases": [
      "local-ai",
      "self-hosted-ai"
    ],
    "target_audience": [
      "developer",
      "researcher"
    ],
    "maturity": "active"
  },
  "decision_signals": {
    "deployment_modes": [
      "local",
      "self_hosted",
      "cloud"
    ],
    "open_source": true,
    "local_first": true,
    "self_hostable": true,
    "has_api": false,
    "has_gui": false,
    "supports_mcp": false,
    "supports_docker": false
  },
  "facts": {
    "license": "MIT",
    "pricing_model": "open_source",
    "github_stars": 91963,
    "github_forks": 11727,
    "github_repo_full_name": "deepseek-ai/DeepSeek-R1",
    "last_verified_at": "2026-06-02"
  },
  "capabilities": {
    "core_capabilities": [
      "local-inference"
    ],
    "integrations": [
      "Hugging Face",
      "Ollama",
      "vLLM",
      "SGLang",
      "llama.cpp"
    ],
    "interfaces": [
      "repo",
      "docs",
      "demo"
    ]
  },
  "links": {
    "primary_url": "https://github.com/deepseek-ai/DeepSeek-R1",
    "items": [
      {
        "type": "github",
        "label": "GitHub",
        "url": "https://github.com/deepseek-ai/DeepSeek-R1"
      },
      {
        "type": "homepage",
        "label": "Homepage",
        "url": "https://www.deepseek.com/"
      },
      {
        "type": "huggingface",
        "label": "Demo",
        "url": "https://huggingface.co/deepseek-ai/DeepSeek-R1"
      },
      {
        "type": "homepage",
        "label": "Source",
        "url": "https://ollama.com/library/deepseek-r1"
      }
    ]
  },
  "media": {
    "thumbnail_url": "https://github.com/deepseek-ai.png",
    "og_image_url": "https://github.com/deepseek-ai.png",
    "thumbnail_brief": {
      "resource_type": "model",
      "visual_motif": "reasoning path grid with nested steps and a compact open model badge",
      "background_style": "minimal technical editorial card with pale surface and dark ink",
      "title_overlay": "DeepSeek-R1",
      "subtitle": "Open reasoning model family",
      "avoid": [
        "benchmark-heavy poster",
        "unverified DeepSeek logos",
        "generic robot imagery"
      ]
    }
  },
  "tags": {
    "category": [
      "model",
      "open-source"
    ],
    "capability": [
      "local-inference"
    ],
    "constraint": [
      "open-source",
      "self-hosted",
      "local-first",
      "open-weights"
    ],
    "scenario": [
      "local-ai",
      "self-hosted-ai"
    ]
  },
  "relationships": {},
  "machine_readable": {
    "canonical_url": "https://www.openagent.bot/models/deepseek-r1",
    "json_url": "https://www.openagent.bot/models/deepseek-r1.json",
    "markdown_url": "https://www.openagent.bot/models/deepseek-r1.md"
  },
  "seo": {
    "title": "DeepSeek-R1: Open reasoning model for local AI workflows",
    "description": "DeepSeek-R1 profile: what the open reasoning model is, when to use it, how it compares, official links, command line, and structured OpenAgent data."
  },
  "editorial": {
    "featured_reason": "A high-signal open reasoning model that many builders use as a baseline for local and self-hosted AI experiments.",
    "trust_note": "Verified from source links and project metadata.",
    "core_strengths": [
      {
        "title": "Reasoning-first open model release",
        "description": "DeepSeek-R1 is designed around reasoning tasks rather than only short chat responses.",
        "why_it_matters": "That makes it useful when a workflow needs multi-step analysis, coding support, or explainable reasoning traces."
      },
      {
        "title": "Strong local evaluation path",
        "description": "The model family is available through public repositories and model hubs, with smaller distilled variants that are easier to test locally.",
        "why_it_matters": "Teams can start with local experiments before deciding whether to self-host larger models."
      },
      {
        "title": "Useful baseline for open reasoning comparisons",
        "description": "DeepSeek-R1 is commonly used as a reference point when evaluating newer open reasoning models.",
        "why_it_matters": "A known baseline helps builders avoid choosing a model only because it is new or popular."
      }
    ],
    "use_case_notes": [
      {
        "title": "Coding and debugging support",
        "description": "Use it to test reasoning-heavy coding assistance, issue diagnosis, and step-by-step technical explanations."
      },
      {
        "title": "Local reasoning experiments",
        "description": "Try distilled variants locally when you want to understand latency, quality, and hardware requirements before hosting a larger model."
      },
      {
        "title": "Self-hosted analysis workflows",
        "description": "Evaluate it for internal workflows where data control or cost makes hosted reasoning APIs less attractive."
      }
    ],
    "compare_notes": [
      {
        "title": "Choose DeepSeek-R1 when reasoning behavior matters more than chat polish",
        "summary": "General chat models can be smoother for casual interaction, but DeepSeek-R1 is worth testing when reasoning quality and open deployment are the main criteria.",
        "against": "general chat models"
      },
      {
        "title": "Keep DeepSeek-R1 as a reasoning baseline",
        "summary": "DeepSeek V4 is the newer family to evaluate for current long-context, coding, and tool-call behavior; R1 remains useful as a known reasoning comparison point.",
        "against": "DeepSeek V4"
      }
    ],
    "getting_started": [
      {
        "label": "Read the GitHub repository",
        "url": "https://github.com/deepseek-ai/DeepSeek-R1",
        "type": "github"
      },
      {
        "label": "Open the Hugging Face model page",
        "url": "https://huggingface.co/deepseek-ai/DeepSeek-R1",
        "type": "huggingface"
      },
      {
        "label": "Try the Ollama library page",
        "url": "https://ollama.com/library/deepseek-r1",
        "type": "install"
      }
    ],
    "command_line": [
      {
        "label": "Run DeepSeek-R1 with Ollama",
        "command": "ollama run deepseek-r1",
        "description": "Use this for a quick local test after installing Ollama and confirming your machine has enough memory for the selected variant."
      },
      {
        "label": "Clone the official repository",
        "command": "git clone https://github.com/deepseek-ai/DeepSeek-R1.git",
        "description": "Use the repository for official release notes, model links, and evaluation context."
      }
    ],
    "seo_article": {
      "intro": "DeepSeek-R1 is one of the clearest starting points for anyone comparing open reasoning models. It is not a consumer assistant by itself; it is a model release that helps developers test reasoning-heavy workflows outside a closed hosted API.",
      "what_it_is": "DeepSeek-R1 is an open model resource to evaluate by workload, serving path, context behavior, license terms, and how reliably it supports the agent or local AI tasks you actually plan to run.",
      "why_it_matters": "Reasoning models are useful when a task requires more than a fluent answer. Coding, debugging, math-like analysis, planning, and technical review all benefit from models that can sustain multi-step reasoning. DeepSeek-R1 gives open AI builders a widely used baseline for those evaluations.",
      "how_it_works": "Run DeepSeek-R1 on a fixed prompt set from your own workflow. Compare quality, latency, context handling, retry behavior, deployment path, and license fit against nearby open models before adopting it.",
      "use_cases": [
        {
          "title": "Coding agent evaluation",
          "description": "Use DeepSeek-R1 to test whether an open model can reason through bug reports, code changes, and multi-step implementation plans."
        },
        {
          "title": "Local research assistant prototypes",
          "description": "Run smaller variants locally to see whether reasoning quality is enough for document review, planning, or analytical note-taking."
        },
        {
          "title": "Self-hosted reasoning API tests",
          "description": "Use it as a baseline when deciding whether a team can replace some hosted reasoning calls with internal infrastructure."
        }
      ],
      "alternatives": [
        {
          "title": "Compare against Qwen, Gemma, and OLMo on your own tasks",
          "summary": "DeepSeek-R1 has strong momentum, but model choice should still come from task-specific evaluation rather than popularity alone.",
          "against": "other open model families"
        },
        {
          "title": "Add DeepSeek V4 to current DeepSeek comparisons",
          "summary": "DeepSeek-R1 should no longer be the only DeepSeek page in a model shortlist. Use it as a reasoning baseline while testing V4-Pro and V4-Flash for current long-context and agent workflows.",
          "against": "DeepSeek V4"
        }
      ],
      "getting_started": [
        {
          "label": "Review the repository first",
          "url": "https://github.com/deepseek-ai/DeepSeek-R1",
          "type": "github"
        },
        {
          "label": "Inspect the Hugging Face model page",
          "url": "https://huggingface.co/deepseek-ai/DeepSeek-R1",
          "type": "huggingface"
        }
      ],
      "faq": [
        {
          "question": "What should I check before using DeepSeek-R1?",
          "answer": "Run DeepSeek-R1 on a fixed prompt set from your own workflow. Compare quality, latency, context handling, retry behavior, deployment path, and license fit against nearby open models before adopting it."
        },
        {
          "question": "Is DeepSeek-R1 open source?",
          "answer": "DeepSeek-R1 is listed with MIT based on the official source links in this profile. Re-check the repository, model card, or docs before production use."
        },
        {
          "question": "Who should evaluate DeepSeek-R1?",
          "answer": "DeepSeek-R1 is most worth evaluating for developers comparing open reasoning models against hosted reasoning APIs."
        },
        {
          "question": "Can DeepSeek-R1 run locally?",
          "answer": "Yes, many users test DeepSeek-R1 variants locally through runtimes such as Ollama. Larger variants still require serious hardware planning."
        },
        {
          "question": "Is DeepSeek-R1 best for every AI app?",
          "answer": "No. It is most interesting for reasoning-heavy tasks. For simple chat, retrieval, or UI workflows, another model may be easier and cheaper."
        }
      ]
    }
  },
  "timestamps": {
    "created_at": "2026-04-19T00:00:00.000Z",
    "updated_at": "2026-06-02T00:00:00.000Z",
    "published_at": "2026-04-19T00:00:00.000Z"
  }
}