{
  "id": "A02",
  "path": "/guides/deepseek-v41-flash-1017/",
  "title": "DeepSeek V4.1 Flash 1017: Deployment Evidence",
  "summary": "Identify the exact 1017 checkpoint, resolve the vLLM recipe and keep publisher recommendations separate from measured capacity.",
  "answer": "Use the pinned 1017 card and recipe to identify the artifact and declared settings. The recipe’s 614 GB planning minimum and publisher’s context budget are not measured capacity or speed on your machine.",
  "published_on": "2026-10-18",
  "modified_on": "2026-10-18",
  "source_checked_on": "2026-10-18",
  "sources": [
    {
      "publisher": "deepseek-ai",
      "url": "https://huggingface.co/deepseek-ai/DeepSeek-V4.1-Flash-1017",
      "repository": "deepseek-ai/DeepSeek-V4.1-Flash-1017",
      "platform": "huggingface",
      "revision": "1bae0e1088993b9b82de08f59de5be5a34e42170",
      "document_path": "README.md",
      "pinned_url": "https://huggingface.co/deepseek-ai/DeepSeek-V4.1-Flash-1017/blob/1bae0e1088993b9b82de08f59de5be5a34e42170/README.md",
      "report_url": null,
      "document_sha256": "b72b796e4f4c739eca5d0ad360a7679b39118ca7eb64891f7151a527b292c42a",
      "last_commit_at": "2026-10-17T05:46:55.000Z",
      "checked_on": "2026-10-17",
      "metadata_status": "checked",
      "related_documents": [
        {
          "url": "https://huggingface.co/deepseek-ai/DeepSeek-V4.1-Flash-1017/blob/1bae0e1088993b9b82de08f59de5be5a34e42170/inference/README.md",
          "sha256": "2834402823199ee24e9a42bdf36a0fc6daf94448f444cb062c042a057a798f1c"
        }
      ],
      "record_id": "deepseek-v41-flash-1017-official"
    },
    {
      "publisher": "vllm-project",
      "url": "https://github.com/vllm-project/recipes",
      "repository": "vllm-project/recipes",
      "platform": "github",
      "revision": "d5fc1f55cee70f4e1944f2dd4f7569cb8276ad94",
      "document_path": "models/deepseek-ai/DeepSeek-V4.1-Flash.yaml",
      "pinned_url": "https://github.com/vllm-project/recipes/blob/d5fc1f55cee70f4e1944f2dd4f7569cb8276ad94/models/deepseek-ai/DeepSeek-V4.1-Flash.yaml",
      "report_url": null,
      "document_sha256": "8fa89be8c171136cc34460cd1d8d64134573c79ee64245d942a057ee4a4d449e",
      "last_commit_at": "2026-10-17T09:22:45Z",
      "checked_on": "2026-10-17",
      "metadata_status": "checked",
      "record_id": "deepseek-v41-flash-vllm"
    }
  ],
  "facts": [
    {
      "id": "deepseek-v41-flash-1017-official-fact-0",
      "label": "Recommended sampling",
      "value": "temperature 1.0; top_p 1.0",
      "classification": "publisher_declaration",
      "url": "https://huggingface.co/deepseek-ai/DeepSeek-V4.1-Flash-1017/blob/1bae0e1088993b9b82de08f59de5be5a34e42170/README.md#L81",
      "source_document_sha256": "b72b796e4f4c739eca5d0ad360a7679b39118ca7eb64891f7151a527b292c42a"
    },
    {
      "id": "deepseek-v41-flash-1017-official-fact-1",
      "label": "Published context / recommended output budget",
      "value": "1M context; max_tokens at least 256K",
      "classification": "publisher_declaration",
      "url": "https://huggingface.co/deepseek-ai/DeepSeek-V4.1-Flash-1017/blob/1bae0e1088993b9b82de08f59de5be5a34e42170/README.md#L84",
      "source_document_sha256": "b72b796e4f4c739eca5d0ad360a7679b39118ca7eb64891f7151a527b292c42a"
    },
    {
      "id": "deepseek-v41-flash-1017-official-fact-2",
      "label": "Prompt interface",
      "value": "Python encoder; no Jinja-format chat template",
      "classification": "publisher_declaration",
      "url": "https://huggingface.co/deepseek-ai/DeepSeek-V4.1-Flash-1017/blob/1bae0e1088993b9b82de08f59de5be5a34e42170/README.md#L69",
      "source_document_sha256": "b72b796e4f4c739eca5d0ad360a7679b39118ca7eb64891f7151a527b292c42a"
    },
    {
      "id": "deepseek-v41-flash-vllm-fact-4",
      "label": "Model-wide minimum vLLM",
      "value": "0.31.0",
      "classification": "recipe_declaration",
      "url": "https://github.com/vllm-project/recipes/blob/d5fc1f55cee70f4e1944f2dd4f7569cb8276ad94/models/deepseek-ai/DeepSeek-V4.1-Flash.yaml#L42",
      "source_document_sha256": "8fa89be8c171136cc34460cd1d8d64134573c79ee64245d942a057ee4a4d449e"
    },
    {
      "id": "deepseek-v41-flash-vllm-fact-6",
      "label": "Default artifact",
      "value": "deepseek-ai/DeepSeek-V4.1-Flash-1017",
      "classification": "recipe_declaration",
      "url": "https://github.com/vllm-project/recipes/blob/d5fc1f55cee70f4e1944f2dd4f7569cb8276ad94/models/deepseek-ai/DeepSeek-V4.1-Flash.yaml#L114",
      "source_document_sha256": "8fa89be8c171136cc34460cd1d8d64134573c79ee64245d942a057ee4a4d449e"
    },
    {
      "id": "deepseek-v41-flash-vllm-fact-7",
      "label": "Default precision label",
      "value": "fp8",
      "classification": "recipe_declaration",
      "url": "https://github.com/vllm-project/recipes/blob/d5fc1f55cee70f4e1944f2dd4f7569cb8276ad94/models/deepseek-ai/DeepSeek-V4.1-Flash.yaml#L114",
      "source_document_sha256": "8fa89be8c171136cc34460cd1d8d64134573c79ee64245d942a057ee4a4d449e"
    },
    {
      "id": "deepseek-v41-flash-vllm-fact-8",
      "label": "Default planning minimum (GB; recipe declaration)",
      "value": 614,
      "classification": "recipe_declaration",
      "url": "https://github.com/vllm-project/recipes/blob/d5fc1f55cee70f4e1944f2dd4f7569cb8276ad94/models/deepseek-ai/DeepSeek-V4.1-Flash.yaml#L125",
      "source_document_sha256": "8fa89be8c171136cc34460cd1d8d64134573c79ee64245d942a057ee4a4d449e"
    },
    {
      "id": "deepseek-v41-flash-vllm-fact-10",
      "label": "Shared base arguments (incomplete launch)",
      "value": [
        "--tokenizer-mode",
        "deepseek_v41"
      ],
      "classification": "recipe_declaration",
      "url": "https://github.com/vllm-project/recipes/blob/d5fc1f55cee70f4e1944f2dd4f7569cb8276ad94/models/deepseek-ai/DeepSeek-V4.1-Flash.yaml#L114",
      "source_document_sha256": "8fa89be8c171136cc34460cd1d8d64134573c79ee64245d942a057ee4a4d449e"
    },
    {
      "id": "deepseek-v41-flash-vllm-fact-13",
      "label": "Features selected by default",
      "value": [
        "spec_decoding",
        "text_only"
      ],
      "classification": "recipe_declaration",
      "url": "https://github.com/vllm-project/recipes/blob/d5fc1f55cee70f4e1944f2dd4f7569cb8276ad94/models/deepseek-ai/DeepSeek-V4.1-Flash.yaml#L114",
      "source_document_sha256": "8fa89be8c171136cc34460cd1d8d64134573c79ee64245d942a057ee4a4d449e"
    }
  ],
  "reported_results": [],
  "conditions": {
    "model_artifact": "deepseek-ai/DeepSeek-V4.1-Flash-1017",
    "weight_revision": null,
    "runtime_execution_revision": null,
    "hardware": null,
    "input_tokens": null,
    "output_tokens": null,
    "concurrency": null,
    "cache_state": null,
    "independently_measured": false
  },
  "generation": {
    "text_draft": "local Spark Qwen",
    "review": "Run AI Here with Codex",
    "image": "Codex image_gen; local Qwen Image unavailable",
    "local_first": true
  },
  "image": {
    "url": "/assets/deepseek-1017-evidence-cover.webp",
    "alt": "Conceptual model card and recipe linked to an empty run-evidence record.",
    "width": 1727,
    "height": 911,
    "sha256": "b1e56ab50ac09ff5b1d1cc47210564559aca4a05e761cf89af16ac9c81cc600f",
    "caption": "AI-generated conceptual illustration; no measured performance values."
  },
  "schema_version": "1.0.0",
  "record_type": "source_backed_explainer",
  "evidence_state": "source_reported",
  "site_reproduced": false,
  "metrics": null,
  "performance_ranking_allowed": false,
  "body_markdown": "# DeepSeek V4.1 Flash 1017: Deployment Evidence\n\nThe pinned model card and vLLM recipe identify the 1017 artifact and provide configuration starting points. They do not establish its speed on your machine. A useful deployment decision needs the exact model identity, a fully resolved recipe and evidence for the intended hardware and workload.\n\n![Conceptual model card and recipe linked to an empty run-evidence record.](/assets/deepseek-1017-evidence-cover.webp)\n\n*AI-generated conceptual illustration. Configuration documents and independent measurements are separate kinds of evidence.*\n\n## Start with the exact checkpoint\n\nThe selected recipe defaults to `deepseek-ai/DeepSeek-V4.1-Flash-1017`. Keep that identity when reading performance reports. A document about an earlier V4.1 checkpoint remains evidence about its original experiment, even if a newer recipe now selects 1017. [Pinned default artifact](https://github.com/vllm-project/recipes/blob/d5fc1f55cee70f4e1944f2dd4f7569cb8276ad94/models/deepseek-ai/DeepSeek-V4.1-Flash.yaml#L114)\n\nPreserve three separate references: the document version you read, the model artifact you intend to load and the runtime version actually executed. Recording a recipe commit alone does not establish the latter two.\n\n## What the publisher recommends\n\nThe official card recommends `temperature 1.0` and `top_p 1.0`. It declares a `1M` context and recommends a `max_tokens` budget of at least `256K`. These are publisher settings and limits; they do not demonstrate an allocation on a particular workstation or require every answer to reach that output length. [Sampling](https://huggingface.co/deepseek-ai/DeepSeek-V4.1-Flash-1017/blob/1bae0e1088993b9b82de08f59de5be5a34e42170/README.md#L81), [context and output budget](https://huggingface.co/deepseek-ai/DeepSeek-V4.1-Flash-1017/blob/1bae0e1088993b9b82de08f59de5be5a34e42170/README.md#L84)\n\nThe card supplies a Python encoding reference rather than a Jinja-format chat template. Check how the chosen serving integration handles the model's protocol; that fact alone does not mean every application needs a new custom implementation. [Prompt interface](https://huggingface.co/deepseek-ai/DeepSeek-V4.1-Flash-1017/blob/1bae0e1088993b9b82de08f59de5be5a34e42170/README.md#L69)\n\n## Read the recipe's declarations precisely\n\n| Selected declaration | Meaning for planning |\n|---|---|\n| Model-wide minimum vLLM: `0.31.0` | A documented baseline; check additional variant and hardware requirements |\n| Default precision label: `fp8` | A recipe label, not a tensor-by-tensor precision audit |\n| Default planning minimum: `614 GB` | A declared planning value for this variant, not measured peak allocation or guaranteed capacity |\n| Shared base arguments: `--tokenizer-mode deepseek_v41` | One layer of the configuration, not a complete launch command |\n| Default selected features: `spec_decoding`, `text_only` | Configuration selections, not measured acceleration or a full model-capability statement |\n\nSource: [minimum runtime](https://github.com/vllm-project/recipes/blob/d5fc1f55cee70f4e1944f2dd4f7569cb8276ad94/models/deepseek-ai/DeepSeek-V4.1-Flash.yaml#L42), [default variant and selections](https://github.com/vllm-project/recipes/blob/d5fc1f55cee70f4e1944f2dd4f7569cb8276ad94/models/deepseek-ai/DeepSeek-V4.1-Flash.yaml#L114), [planning minimum](https://github.com/vllm-project/recipes/blob/d5fc1f55cee70f4e1944f2dd4f7569cb8276ad94/models/deepseek-ai/DeepSeek-V4.1-Flash.yaml#L125).\n\n## Turn the sources into a deployment decision\n\nChoose an artifact variant and hardware profile before assembling settings. Read the shared, variant, hardware, strategy and optional-feature layers together. A copied fragment can lose the conditions that made the original configuration meaningful.\n\nUse the documents to prepare a reproducible configuration record. A planning value can help reject an unsuitable proposal, but it cannot replace a traceable allocation and successful request on the intended system. Keep advertised context, configured context, tested input length and available serving capacity as separate fields.\n\n## What a useful run report still needs\n\nFor evidence that someone actually ran the intended configuration, look for:\n\n- Exact artifact, conversion and runtime identities.\n- Device count, memory, topology and complete resolved launch settings.\n- Input and output lengths, concurrency and stopping rules.\n- Cache, warmup, sampling and speculative-decoding settings.\n- Timing definitions, repetitions, failures and uncertainty.\n\nMissing details stay unknown. The indexed sources used for this article do not establish a RunAIHere speed measurement for 1017, and this page does not supply a hardware performance ranking. RunAIHere has not independently executed or benchmarked this checkpoint.\n"
}