{
  "id": "qwen38-flash-next-official",
  "title": "Qwen3.8-Flash-Next: official model and deployment card",
  "kind": "model",
  "source_type": "official_model_card",
  "summary": "Publisher model card with serving links and distinct thinking-mode settings. Use its exact artifact identity alongside the selected engine recipe.",
  "runtime": "vLLM / SGLang / TokenSpeed",
  "runtime_topics": [
    "vLLM",
    "SGLang",
    "TokenSpeed"
  ],
  "hardware_topics": [],
  "platform_topics": [],
  "model_label": "Qwen3.8-Flash-Next",
  "model_family": "Qwen",
  "model_id": "Qwen/Qwen3.8-Flash-Next",
  "model_release_date": null,
  "model_artifact": {
    "id": "Qwen/Qwen3.8-Flash-Next",
    "revision": "de4b8e4d43b917e7706784d8bb445c9af86a3540",
    "format": null
  },
  "evidence_state": "source_reported",
  "site_reproduced": false,
  "record_type": "curated_reference",
  "performance_ranking_allowed": false,
  "metrics": null,
  "metrics_status": "site_metrics_unmeasured; attributed_source_figures_in_editorial.reported_results",
  "conditions": {
    "model_revision": "de4b8e4d43b917e7706784d8bb445c9af86a3540",
    "weight_hash": null,
    "runtime_execution_revision": null,
    "input_tokens": null,
    "output_tokens": null,
    "concurrency": null,
    "cache_state": null,
    "quantization": null,
    "speculative_decoding": null,
    "temperature": null,
    "top_p": null
  },
  "reported_setup": {
    "system": null,
    "node_count": null,
    "parallelism": null,
    "kv_dtype": null,
    "context_limit_tokens": null,
    "experiment_date": null
  },
  "test_profiles": [],
  "deployment_options": [],
  "recipe_parameters": null,
  "measurement_scope": "official_capability_and_deployment",
  "notes": [
    "The card separates thinking and non-thinking sampling.",
    "Serving references point to model-specific vLLM, SGLang and TokenSpeed documentation."
  ],
  "limitations": [
    "Runtime support and usable context depend on the selected build and precision."
  ],
  "comparison_status": "not_comparable",
  "editorial_status": "source_derived_detailed_article",
  "public_benchmark_snapshot": false,
  "source": {
    "publisher": "Qwen",
    "url": "https://huggingface.co/Qwen/Qwen3.8-Flash-Next",
    "repository": "Qwen/Qwen3.8-Flash-Next",
    "platform": "huggingface",
    "revision": "de4b8e4d43b917e7706784d8bb445c9af86a3540",
    "document_path": "README.md",
    "pinned_url": "https://huggingface.co/Qwen/Qwen3.8-Flash-Next/blob/de4b8e4d43b917e7706784d8bb445c9af86a3540/README.md",
    "report_url": null,
    "document_sha256": "35ca37ccc366f1ba478dab33841a2c0c18ce53fd62f291ca05341f7728b225b2",
    "last_commit_at": "2026-08-27T05:03:36.000Z",
    "checked_on": "2026-10-17",
    "metadata_status": "checked"
  },
  "license": {
    "declared_spdx": "other",
    "declared_name": "qwen-community-1.0",
    "scope": "Publisher model-card declaration; inspect the linked LICENSE and artifact-specific terms."
  },
  "editorial": {
    "version": 1,
    "published_on": "2026-10-17",
    "modified_on": "2026-10-17",
    "byline": "Run AI Here editorial",
    "creation_method": "AI-assisted source reading and original editorial synthesis; no independent model execution.",
    "answer": "Publisher model card with serving links and distinct thinking-mode settings. Use its exact artifact identity alongside the selected engine recipe.",
    "sections": [
      {
        "heading": "How is the model’s size counted?",
        "paragraphs": [
          "The card describes a 125B language-model component with 6B active parameters, plus 51B of n-gram embeddings and a 4B multi-token prediction component. The vLLM recipe uses a 176B summary label. Those counts cover different components; neither label should be substituted for the size of a downloaded artifact. The card lists 48 layers and a repeated hybrid of Gated DeltaNet and sparse attention."
        ],
        "citations": [
          "https://huggingface.co/Qwen/Qwen3.8-Flash-Next/blob/de4b8e4d43b917e7706784d8bb445c9af86a3540/README.md#L46"
        ]
      },
      {
        "heading": "Is the open checkpoint natively a million-token model?",
        "paragraphs": [
          "The published native window is 262,144 tokens. Reaching 1,000,000 tokens requires the documented extension configuration; the hosted Qwen3.8-Flash product and the open Flash-Next checkpoint also have different production features. Record the actual RoPE settings and total input-plus-output budget before evaluating long tasks."
        ],
        "citations": [
          "https://huggingface.co/Qwen/Qwen3.8-Flash-Next/blob/de4b8e4d43b917e7706784d8bb445c9af86a3540/README.md#L71"
        ]
      },
      {
        "heading": "How do thinking and non-thinking settings differ?",
        "paragraphs": [
          "Thinking mode uses temperature 1.0, top_p 0.95 and presence_penalty 0.0; non-thinking uses 0.7, 0.80 and 1.5 respectively. Both recommendations retain top_k 20, min_p 0.0 and repetition_penalty 1.0. The card also preserves historical thinking blocks by default. Changing that conversation policy changes both the prompt and cache behavior."
        ],
        "citations": [
          "https://huggingface.co/Qwen/Qwen3.8-Flash-Next/blob/de4b8e4d43b917e7706784d8bb445c9af86a3540/README.md#L342"
        ]
      },
      {
        "heading": "How should its benchmark table be read?",
        "paragraphs": [
          "The coding evaluations specify harnesses, sampling and context. In particular, DeepSWE reports the better result from Claude Code and mini-SWE-agent rather than one universally shared harness. For vision tables, pass@3 and the mean over three attempts are different statistics. Keep the footnote for the selected task instead of treating every published cell as directly comparable."
        ],
        "citations": [
          "https://huggingface.co/Qwen/Qwen3.8-Flash-Next/blob/de4b8e4d43b917e7706784d8bb445c9af86a3540/README.md#L227"
        ]
      }
    ],
    "facts": [
      {
        "name": "LM component / active / n-gram / MTP",
        "value": "125B / 6B / 51B / 4B",
        "classification": "publisher_declaration",
        "evidence_url": "https://huggingface.co/Qwen/Qwen3.8-Flash-Next/blob/de4b8e4d43b917e7706784d8bb445c9af86a3540/README.md#L46",
        "source_document_sha256": "35ca37ccc366f1ba478dab33841a2c0c18ce53fd62f291ca05341f7728b225b2"
      },
      {
        "name": "Layers",
        "value": 48,
        "classification": "publisher_declaration",
        "evidence_url": "https://huggingface.co/Qwen/Qwen3.8-Flash-Next/blob/de4b8e4d43b917e7706784d8bb445c9af86a3540/README.md#L50",
        "source_document_sha256": "35ca37ccc366f1ba478dab33841a2c0c18ce53fd62f291ca05341f7728b225b2"
      },
      {
        "name": "Native / extended context",
        "value": "262144 / up to 1000000 tokens",
        "classification": "publisher_declaration",
        "evidence_url": "https://huggingface.co/Qwen/Qwen3.8-Flash-Next/blob/de4b8e4d43b917e7706784d8bb445c9af86a3540/README.md#L71",
        "source_document_sha256": "35ca37ccc366f1ba478dab33841a2c0c18ce53fd62f291ca05341f7728b225b2"
      },
      {
        "name": "Thinking sampling",
        "value": "temperature 1.0; top_p 0.95; top_k 20",
        "classification": "publisher_declaration",
        "evidence_url": "https://huggingface.co/Qwen/Qwen3.8-Flash-Next/blob/de4b8e4d43b917e7706784d8bb445c9af86a3540/README.md#L342",
        "source_document_sha256": "35ca37ccc366f1ba478dab33841a2c0c18ce53fd62f291ca05341f7728b225b2"
      },
      {
        "name": "Non-thinking sampling",
        "value": "temperature 0.7; top_p 0.80; presence_penalty 1.5",
        "classification": "publisher_declaration",
        "evidence_url": "https://huggingface.co/Qwen/Qwen3.8-Flash-Next/blob/de4b8e4d43b917e7706784d8bb445c9af86a3540/README.md#L343",
        "source_document_sha256": "35ca37ccc366f1ba478dab33841a2c0c18ce53fd62f291ca05341f7728b225b2"
      }
    ],
    "reported_results": [],
    "source_document_sha256": "35ca37ccc366f1ba478dab33841a2c0c18ce53fd62f291ca05341f7728b225b2"
  }
}