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     "2026-10-17",
     "2026-10-18",
     "2026-10-19",
     "2026-10-20",
     "2026-10-21",
     "2026-10-22",
     "2026-10-23",
     "2026-10-24",
     "2026-10-25",
     "2026-10-26",
     "2026-10-27",
     "2026-10-28",
     "2026-10-29",
     "2026-10-30",
     "2026-10-31",
     "2026-11-01",
     "2026-11-02",
     "2026-11-03",
     "2026-11-04",
     "2026-11-05",
     "2026-11-06",
     "2026-11-07",
     "2026-11-08",
     "2026-11-09"
    ],
    "model_two_date_gate": true,
    "offer_id": "anthropic-claude-opus-5.5:direct",
    "provider": "anthropic",
    "channel": "direct",
    "route_key": "[\"api.anthropic.com\",\"claude-opus-5-5\",\"anthropic\",\"direct\",null]",
    "price": {
     "currency": "USD",
     "input_per_1m": 4.0,
     "output_per_1m": 20.0,
     "cache_read_per_1m": 0.2,
     "cache_write_5m_per_1m": 5.0,
     "cache_write_1h_per_1m": 8.0,
     "data_status": "published",
     "source_url": "https://platform.claude.com/docs/en/about-claude/pricing",
     "observed_at": "2026-11-09",
     "content_sha256": "b75c2ad13749a214681658715de4bb7a999164f91efed6319ec7de63f4a252a7",
     "fields": {
      "input_per_1m": {
       "data_status": "published",
       "source_url": "https://platform.claude.com/docs/en/about-claude/pricing",
       "observed_at": "2026-11-09",
       "content_sha256": "b75c2ad13749a214681658715de4bb7a999164f91efed6319ec7de63f4a252a7",
       "quote": "Claude Opus 5.5 For long-running agentic coding and knowledge work $4 / MTok $20 / MTok $5 / MTok"
      },
      "output_per_1m": {
       "data_status": "published",
       "source_url": "https://platform.claude.com/docs/en/about-claude/pricing",
       "observed_at": "2026-11-09",
       "content_sha256": "b75c2ad13749a214681658715de4bb7a999164f91efed6319ec7de63f4a252a7",
       "quote": "Claude Opus 5.5 For long-running agentic coding and knowledge work $4 / MTok $20 / MTok $5 / MTok"
      },
      "cache_read_per_1m": {
       "data_status": "published",
       "source_url": "https://platform.claude.com/docs/en/about-claude/pricing",
       "observed_at": "2026-11-09",
       "content_sha256": "b75c2ad13749a214681658715de4bb7a999164f91efed6319ec7de63f4a252a7",
       "quote": "Name Input Output 5m writes 1h writes Hits and refreshes Claude Fable 5.1 For demanding reasoning and long-horizon agentic work $10 / MTok $50 / MTok $12.50 / MTok $20 / MTok $0.25 / MTok Claude Opus 5.5 For long-running agentic coding and knowledge work $4 / MTok $20 / MTok $5 / MTok $8 / MTok $0.20 / MTok"
      },
      "cache_write_5m_per_1m": {
       "data_status": "published",
       "source_url": "https://platform.claude.com/docs/en/about-claude/pricing",
       "observed_at": "2026-11-09",
       "content_sha256": "b75c2ad13749a214681658715de4bb7a999164f91efed6319ec7de63f4a252a7",
       "quote": "Name Input Output 5m writes 1h writes Hits and refreshes Claude Fable 5.1 For demanding reasoning and long-horizon agentic work $10 / MTok $50 / MTok $12.50 / MTok $20 / MTok $0.25 / MTok Claude Opus 5.5 For long-running agentic coding and knowledge work $4 / MTok $20 / MTok $5 / MTok $8 / MTok $0.20 / MTok"
      },
      "cache_write_1h_per_1m": {
       "data_status": "published",
       "source_url": "https://platform.claude.com/docs/en/about-claude/pricing",
       "observed_at": "2026-11-09",
       "content_sha256": "b75c2ad13749a214681658715de4bb7a999164f91efed6319ec7de63f4a252a7",
       "quote": "Name Input Output 5m writes 1h writes Hits and refreshes Claude Fable 5.1 For demanding reasoning and long-horizon agentic work $10 / MTok $50 / MTok $12.50 / MTok $20 / MTok $0.25 / MTok Claude Opus 5.5 For long-running agentic coding and knowledge work $4 / MTok $20 / MTok $5 / MTok $8 / MTok $0.20 / MTok"
      }
     },
     "cache_write_per_1m": null,
     "cache_storage_per_1m_per_hour": null,
     "context_cliff": {
      "has_cliff": false,
      "data_status": "unknown",
      "reason": "no long-context threshold on the provider price page in our data"
     },
     "evidence_check": {
      "status": "pass",
      "issues": [],
      "previous_release_compared": true
     }
    },
    "context": {
     "max_input_tokens": {
      "value": 1000000,
      "data_status": "published",
      "source_url": "https://platform.claude.com/docs/en/models/overview",
      "observed_at": "2026-10-20",
      "quote": "Context window: 1M tokens; Max output: 128K tokens."
     },
     "max_output_tokens": {
      "value": 128000,
      "data_status": "published",
      "source_url": "https://platform.claude.com/docs/en/models/overview",
      "observed_at": "2026-10-20"
     }
    },
    "price_observation_dates": [
     "2026-10-16",
     "2026-10-17",
     "2026-10-18",
     "2026-10-19",
     "2026-10-20",
     "2026-10-21",
     "2026-10-22",
     "2026-10-23",
     "2026-10-24",
     "2026-10-25",
     "2026-10-26",
     "2026-10-27",
     "2026-10-28",
     "2026-10-29",
     "2026-10-30",
     "2026-10-31",
     "2026-11-01",
     "2026-11-02",
     "2026-11-03",
     "2026-11-04",
     "2026-11-05",
     "2026-11-06",
     "2026-11-07",
     "2026-11-08",
     "2026-11-09"
    ],
    "two_date_model_and_price_gate": true,
    "api_model": "claude-opus-5-5",
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    "open_weights": false,
    "tokenization": {
     "measured_at": "2026-10-23T20:14:55Z",
     "method": "count_tokens",
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     "kinds": {
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       "tokens": 639,
       "o200k_base": 430,
       "ratio": 1.486
      },
      "code": {
       "request_tokens": 881,
       "tokens": 873,
       "o200k_base": 557,
       "ratio": 1.5673
      },
      "json": {
       "request_tokens": 694,
       "tokens": 686,
       "o200k_base": 535,
       "ratio": 1.2822
      },
      "european": {
       "request_tokens": 586,
       "tokens": 578,
       "o200k_base": 320,
       "ratio": 1.8062
      },
      "cjk": {
       "request_tokens": 406,
       "tokens": 398,
       "o200k_base": 306,
       "ratio": 1.3007
      },
      "estonian": {
       "request_tokens": 555,
       "tokens": 547,
       "o200k_base": 331,
       "ratio": 1.6526
      },
      "russian": {
       "request_tokens": 468,
       "tokens": 460,
       "o200k_base": 292,
       "ratio": 1.5753
      }
     },
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     "api_model": "claude-opus-5-5",
     "reported_model_id": null
    },
    "features": {
     "structured_json": {
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      "data_status": "published",
      "source_url": "https://platform.claude.com/docs/en/build-with-claude/structured-outputs.md",
      "observed_at": "2026-10-17",
      "quote": "Structured outputs guarantee schema-compliant responses through constrained decoding:",
      "evidence": [
       {
        "kind": "provider_published",
        "source_url": "https://platform.claude.com/docs/en/build-with-claude/structured-outputs.md",
        "observed_at": "2026-10-17",
        "quote": "Structured outputs guarantee schema-compliant responses through constrained decoding:"
       },
       {
        "kind": "provider_published",
        "source_url": "https://platform.claude.com/docs/en/build-with-claude/structured-outputs.md",
        "observed_at": "2026-10-17",
        "quote": "The request carries the schema in output_config.format with type: \"json_schema\". SDK helpers set this for you."
       }
      ],
      "evidence_kind": "provider_published"
     },
     "tool_calls": {
      "value": true,
      "data_status": "published",
      "source_url": "https://platform.claude.com/docs/en/agents-and-tools/tool-use/strict-tool-use.md",
      "observed_at": "2026-10-17",
      "quote": "Setting strict: true on a tool definition guarantees Claude's tool inputs match your JSON Schema by constraining the model's token sampling to schema-valid outputs (a technique called grammar-constrained sampling).",
      "evidence": [
       {
        "kind": "provider_published",
        "source_url": "https://platform.claude.com/docs/en/agents-and-tools/tool-use/strict-tool-use.md",
        "observed_at": "2026-10-17",
        "quote": "Setting strict: true on a tool definition guarantees Claude's tool inputs match your JSON Schema by constraining the model's token sampling to schema-valid outputs (a technique called grammar-constrained sampling)."
       },
       {
        "kind": "provider_published",
        "source_url": "https://platform.claude.com/docs/en/agents-and-tools/tool-use/parallel-tool-use.md",
        "observed_at": "2026-10-17",
        "quote": "By default, Claude may call multiple tools in a single response."
       },
       {
        "kind": "provider_published",
        "source_url": "https://platform.claude.com/docs/en/build-with-claude/streaming.md",
        "observed_at": "2026-10-17",
        "quote": "Note: Current models only support emitting one complete key and value property from input at a time."
       },
       {
        "kind": "provider_published",
        "source_url": "https://platform.claude.com/docs/en/build-with-claude/extended-thinking.md",
        "observed_at": "2026-10-17",
        "quote": "Interleaved thinking lets Claude think between tool calls within a single assistant turn, reasoning about each tool result before determining what to do next."
       }
      ],
      "evidence_kind": "provider_published"
     },
     "images": {
      "value": true,
      "data_status": "published",
      "source_url": "https://platform.claude.com/docs/en/models/overview",
      "observed_at": "2026-10-20"
     }
    },
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     "training": {
      "value": "no",
      "data_status": "published",
      "source_url": "https://www.anthropic.com/legal/commercial-terms",
      "observed_at": "2026-11-09",
      "quote": "Anthropic may not train models on Customer Content from Services.",
      "answer": "no",
      "observation_dates": [
       "2026-10-16",
       "2026-10-17",
       "2026-10-18",
       "2026-10-19",
       "2026-10-20",
       "2026-10-21",
       "2026-10-22",
       "2026-10-23",
       "2026-10-24",
       "2026-10-26",
       "2026-10-27",
       "2026-10-28",
       "2026-10-29",
       "2026-10-30",
       "2026-10-31",
       "2026-11-01",
       "2026-11-02",
       "2026-11-03",
       "2026-11-05",
       "2026-11-06",
       "2026-11-07",
       "2026-11-09"
      ]
     },
     "benchmark": {
      "value": "no",
      "data_status": "published",
      "source_url": "https://www.anthropic.com/legal/commercial-terms",
      "observed_at": "2026-11-09",
      "answer": "no clause found",
      "observation_dates": [
       "2026-10-16",
       "2026-10-17",
       "2026-10-18",
       "2026-10-19",
       "2026-10-20",
       "2026-10-21",
       "2026-10-22",
       "2026-10-23",
       "2026-10-24",
       "2026-10-26",
       "2026-10-27",
       "2026-10-28",
       "2026-10-29",
       "2026-10-30",
       "2026-10-31",
       "2026-11-01",
       "2026-11-02",
       "2026-11-03",
       "2026-11-05",
       "2026-11-06",
       "2026-11-07",
       "2026-11-09"
      ]
     },
     "processing_regions": {
      "value": null,
      "data_status": "unknown",
      "source_url": null,
      "observed_at": null
     },
     "processing_countries": {
      "value": null,
      "data_status": "unknown",
      "source_url": "https://platform.claude.com/docs/en/manage-claude/data-residency",
      "observed_at": "2026-10-23",
      "quote": "\"global\" | Default. Inference may run in any available geography for optimal performance and availability.",
      "reason": "The global endpoint may run inference in any available geography; the only selectable region is the US (inference_geo \"us\", at a higher price). No EU processing option is published."
     },
     "retention_days": {
      "value": null,
      "data_status": "unknown",
      "source_url": null,
      "observed_at": null
     },
     "execution_allowed": false,
     "provider_jurisdictions": {
      "value": [
       "US",
       "IE"
      ],
      "data_status": "published",
      "source_url": "https://www.anthropic.com/legal/commercial-terms",
      "observed_at": "2026-10-23",
      "quote": "Anthropic Ireland, Limited if Customer resides in the European Economic Area (\"EEA\"), Switzerland or UK, and Anthropic, PBC if Customer resides anywhere else.",
      "reason": "Anthropic, PBC; Anthropic Ireland, Limited contracts with customers in the EEA, Switzerland and the UK."
     }
    },
    "speed": [
     {
      "route_key": "[\"api.anthropic.com\",\"claude-opus-5-5\",\"anthropic\",\"direct\",null]",
      "snapshot_key": "anthropic/claude-opus-5.5-20260921",
      "country": "AU",
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      "snapshot_key": "anthropic/claude-opus-5.5-20260921",
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      "snapshot_key": "anthropic/claude-opus-5.5-20260921",
      "country": "DE",
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       3.2,
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      [
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       1.68,
       3.38,
       0.13,
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    "model_two_date_gate": true,
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     },
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     },
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     "execution_allowed": false
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    "account_group_id": "openrouter",
    "browser_execution": {
     "enabled": false,
     "cors_verified": false,
     "reason": "Browser runs require separate checks for this model and route."
    },
    "quality": {
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     "roles": [],
     "run_dates": [],
     "group_id": null,
     "task_fit": "unverified",
     "status": "unknown",
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     "reason": "No current exact temporary admission or two-date own quality evidence."
    },
    "executors": {
     "data_status": "published",
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     "source_url": "https://openrouter.ai/api/v1/models/deepseek/deepseek-v4.1-flash-1017:batch/endpoints",
     "input_per_1m": {
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     "above_listing": 0,
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    }
   },
   {
    "model_id": "deepseek-deepseek-v4.1-flash-1017",
    "name": "DeepSeek: DeepSeek V4.1 Flash 1017",
    "snapshot_key": "deepseek/deepseek-v4.1-flash-20261017",
    "openrouter_id": "deepseek/deepseek-v4.1-flash-1017",
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    "current_snapshot": true,
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     "2026-10-23",
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     "2026-10-25",
     "2026-10-26",
     "2026-10-27",
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     "2026-11-04",
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     "2026-11-07",
     "2026-11-08",
     "2026-11-09"
    ],
    "model_two_date_gate": true,
    "offer_id": "deepseek-deepseek-v4.1-flash-1017:direct",
    "provider": "deepseek",
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    "route_key": "[\"api.deepseek.com\",\"deepseek-flash\",\"deepseek\",\"direct\",null]",
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     "data_status": "published",
     "source_url": "https://api-docs.deepseek.com/quick_start/pricing",
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       "content_sha256": "50563fd0eefea6d5547241d3f0defb7b7d50d0f17481a453343958b636a1fe51",
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      },
      "output_per_1m": {
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      "has_cliff": false,
      "data_status": "unknown",
      "reason": "no long-context threshold on the provider price page in our data"
     },
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     },
     "label": "peak-hour price",
     "note": "Off-peak is cheaper."
    },
    "context": {
     "max_input_tokens": {
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     },
     "max_output_tokens": {
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    "two_date_model_and_price_gate": true,
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     },
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       }
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     },
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      "data_status": "published",
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      "observed_at": "2026-10-17",
      "quote": "In strict mode, the model strictly adheres to the format requirements of the Function's JSON schema when outputting a tool call, ensuring that the model's output complies with the user's definition. It is supported by both thinking and non-thinking mode.",
      "evidence": [
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        "source_url": "/api-pricing/compatibility/#streaming",
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        "value": true,
        "note": "One test call on this API model; not a guarantee for every request."
       },
       {
        "kind": "provider_published",
        "source_url": "https://api-docs.deepseek.com/guides/tool_calls",
        "observed_at": "2026-10-17",
        "quote": "In strict mode, the model strictly adheres to the format requirements of the Function's JSON schema when outputting a tool call, ensuring that the model's output complies with the user's definition. It is supported by both thinking and non-thinking mode."
       },
       {
        "kind": "provider_published",
        "source_url": "https://api-docs.deepseek.com/guides/tool_calls",
        "observed_at": "2026-10-17",
        "quote": "From DeepSeek-V3.2, the API supports tool use in the thinking mode."
       }
      ],
      "evidence_kind": "published_and_measured",
      "reason": "One test call on this API model; not a guarantee for every request."
     },
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     }
    },
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      "source_url": "https://cdn.deepseek.com/policies/en-US/deepseek-terms-of-use.html",
      "observed_at": "2026-11-09",
      "quote": "4.3 Under the premise of secure encryption technology processing, strict de-identification rendering, and irreversibility to identify specific individuals, we may, to a minimal extent, use Inputs and Outputs …",
      "answer": "yes — de-identified Inputs and Outputs, with an opt-out (\"Improve the model for everyone\")",
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       "2026-10-29",
       "2026-10-30",
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       "2026-11-06",
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      ]
     },
     "benchmark": {
      "value": "no",
      "data_status": "published",
      "source_url": "https://cdn.deepseek.com/policies/en-US/deepseek-terms-of-use.html",
      "observed_at": "2026-11-09",
      "answer": "no clause found",
      "observation_dates": [
       "2026-10-16",
       "2026-10-17",
       "2026-10-18",
       "2026-10-19",
       "2026-10-20",
       "2026-10-21",
       "2026-10-22",
       "2026-10-23",
       "2026-10-24",
       "2026-10-26",
       "2026-10-27",
       "2026-10-28",
       "2026-10-29",
       "2026-10-30",
       "2026-10-31",
       "2026-11-01",
       "2026-11-02",
       "2026-11-03",
       "2026-11-04",
       "2026-11-05",
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       "2026-11-09"
      ]
     },
     "processing_regions": {
      "value": null,
      "data_status": "unknown",
      "source_url": null,
      "observed_at": null
     },
     "processing_countries": {
      "value": null,
      "data_status": "unknown",
      "source_url": "https://cdn.deepseek.com/policies/en-US/deepseek-privacy-policy.html",
      "observed_at": "2026-10-23",
      "quote": "To provide you with our services, we directly collect, process and store your Personal Data in People's Republic of China.",
      "reason": "The API documentation names no processing location; the privacy policy says personal data is stored in servers in the People's Republic of China. Not a commitment for inference."
     },
     "retention_days": {
      "value": null,
      "data_status": "unknown",
      "source_url": null,
      "observed_at": null
     },
     "execution_allowed": false,
     "provider_jurisdictions": {
      "value": [
       "CN"
      ],
      "data_status": "published",
      "source_url": "https://cdn.deepseek.com/policies/en-US/deepseek-open-platform-terms-of-service.html",
      "observed_at": "2026-10-23",
      "quote": "The establishment, execution, interpretation, and resolution of disputes under these Terms shall be governed by the laws of the People's Republic of China in the mainland.",
      "reason": "Terms governed by the law of the People's Republic of China; operator Hangzhou DeepSeek."
     }
    },
    "speed": [
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      "route_key": "[\"api.deepseek.com\",\"deepseek-flash\",\"deepseek\",\"direct\",null]",
      "snapshot_key": "deepseek/deepseek-v4.1-flash-20261017",
      "country": "AU",
      "data_status": "published",
      "mode": "median",
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       "2026-10-20",
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      "source_url": "/api/test-requests.json",
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      "reasoning_setting": "off",
      "samples": 110,
      "distributions": {
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       "quote": "### Standard pricing data | Model | Short context input | Short context output | Short context cached input | Short context 30m write | Short context 12h write | Long context input | Long context output | Long context cached input | Long context 30m write | Long context 12h write | | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | | gpt-6-astra | $10.00 | $50.00 | $1.00 | $12.50 | $25.00 | $20.00 | $75.00 | $2.00 | $25.00 | $50.00 | | gpt-6.1-sol | $2.00 | $10.00 | $0.10 | $2.50 | $5.00 | $4.00 | $15.00 | $0.20 | $5.00 | $10.00 | | gpt-6.1-terra | $1.00 | $5.00 | $0.05 | $1.25 | $2.50 | $2.00 | $7.50 | $0.10 | $2.50 | $5.00 | | gpt-6-luna | $0.10 |"
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       "quote": "### Standard pricing data | Model | Short context input | Short context output | Short context cached input | Short context 30m write | Short context 12h write | Long context input | Long context output | Long context cached input | Long context 30m write | Long context 12h write | | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | | gpt-6-astra | $10.00 | $50.00 | $1.00 | $12.50 | $25.00 | $20.00 | $75.00 | $2.00 | $25.00 | $50.00 | | gpt-6.1-sol | $2.00 | $10.00 | $0.10 | $2.50 | $5.00 | $4.00 | $15.00 | $0.20 | $5.00 | $10.00 | | gpt-6.1-terra | $1.00 | $5.00 | $0.05 | $1.25 | $2.50 | $2.00 | $7.50 | $0.10 | $2.50 | $5.00 | | gpt-6-luna | $0.10 | $0.50 |"
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      "cache_read_per_1m": {
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       "observed_at": "2026-11-09",
       "content_sha256": "f1ade44afc62fd8a12dd6e199bcecaa989a94c9b691aa620a34e1504ff62ff57",
       "quote": "### Standard pricing data | Model | Short context input | Short context output | Short context cached input | Short context 30m write | Short context 12h write | Long context input | Long context output | Long context cached input | Long context 30m write | Long context 12h write | | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | | gpt-6-astra | $10.00 | $50.00 | $1.00 | $12.50 | $25.00 | $20.00 | $75.00 | $2.00 | $25.00 | $50.00 | | gpt-6.1-sol | $2.00 | $10.00 | $0.10 | $2.50 | $5.00 | $4.00 | $15.00 | $0.20 | $5.00 | $10.00 | | gpt-6.1-terra | $1.00 | $5.00 | $0.05 | $1.25 | $2.50 | $2.00 | $7.50 | $0.10 | $2.50 | $5.00 | | gpt-6-luna | $0.10 | $0.50 | $0.01 |"
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      "cache_write_per_1m": {
       "data_status": "published",
       "source_url": "https://developers.openai.com/api/docs/pricing.md",
       "observed_at": "2026-11-09",
       "content_sha256": "f1ade44afc62fd8a12dd6e199bcecaa989a94c9b691aa620a34e1504ff62ff57",
       "quote": "### Standard pricing data | Model | Short context input | Short context output | Short context cached input | Short context 30m write | Short context 12h write | Long context input | Long context output | Long context cached input | Long context 30m write | Long context 12h write | | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | | gpt-6-astra | $10.00 | $50.00 | $1.00 | $12.50 | $25.00 | $20.00 | $75.00 | $2.00 | $25.00 | $50.00 | | gpt-6.1-sol | $2.00 | $10.00 | $0.10 | $2.50 | $5.00 | $4.00 | $15.00 | $0.20 | $5.00 | $10.00 | | gpt-6.1-terra | $1.00 | $5.00 | $0.05 | $1.25 | $2.50 | $2.00 | $7.50 | $0.10 | $2.50 | $5.00 | | gpt-6-luna | $0.10 | $0.50 | $0.01 | $0.125 |"
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      "data_status": "published",
      "source_url": "https://developers.openai.com/api/docs/pricing.md",
      "observed_at": "2026-11-09",
      "content_sha256": "f1ade44afc62fd8a12dd6e199bcecaa989a94c9b691aa620a34e1504ff62ff57",
      "fields": {
       "threshold_input_tokens": {
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        "content_sha256": "f1ade44afc62fd8a12dd6e199bcecaa989a94c9b691aa620a34e1504ff62ff57",
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        "quote": "### Standard pricing data | Model | Short context input | Short context output | Short context cached input | Short context 30m write | Short context 12h write | Long context input | Long context output | Long context cached input | Long context 30m write | Long context 12h write | | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | | gpt-6-astra | $10.00 | $50.00 | $1.00 | $12.50 | $25.00 | $20.00 | $75.00 | $2.00 | $25.00 | $50.00 | | gpt-6.1-sol | $2.00 | $10.00 | $0.10 | $2.50 | $5.00 | $4.00 | $15.00 | $0.20 | $5.00 | $10.00 | | gpt-6.1-terra | $1.00 | $5.00 | $0.05 | $1.25 | $2.50 | $2.00 | $7.50 | $0.10 | $2.50 | $5.00 | | gpt-6-luna | $0.10 | $0.50 | $0.01 | $0.125 | $0.25 | $0.20 |"
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        "data_status": "published",
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        "quote": "### Standard pricing data | Model | Short context input | Short context output | Short context cached input | Short context 30m write | Short context 12h write | Long context input | Long context output | Long context cached input | Long context 30m write | Long context 12h write | | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | | gpt-6-astra | $10.00 | $50.00 | $1.00 | $12.50 | $25.00 | $20.00 | $75.00 | $2.00 | $25.00 | $50.00 | | gpt-6.1-sol | $2.00 | $10.00 | $0.10 | $2.50 | $5.00 | $4.00 | $15.00 | $0.20 | $5.00 | $10.00 | | gpt-6.1-terra | $1.00 | $5.00 | $0.05 | $1.25 | $2.50 | $2.00 | $7.50 | $0.10 | $2.50 | $5.00 | | gpt-6-luna | $0.10 | $0.50 | $0.01 | $0.125 | $0.25 | $0.20 | $0.75 |"
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       "above_threshold_cache_read_per_1m": {
        "data_status": "published",
        "source_url": "https://developers.openai.com/api/docs/pricing.md",
        "observed_at": "2026-11-09",
        "content_sha256": "f1ade44afc62fd8a12dd6e199bcecaa989a94c9b691aa620a34e1504ff62ff57",
        "quote": "### Standard pricing data | Model | Short context input | Short context output | Short context cached input | Short context 30m write | Short context 12h write | Long context input | Long context output | Long context cached input | Long context 30m write | Long context 12h write | | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | | gpt-6-astra | $10.00 | $50.00 | $1.00 | $12.50 | $25.00 | $20.00 | $75.00 | $2.00 | $25.00 | $50.00 | | gpt-6.1-sol | $2.00 | $10.00 | $0.10 | $2.50 | $5.00 | $4.00 | $15.00 | $0.20 | $5.00 | $10.00 | | gpt-6.1-terra | $1.00 | $5.00 | $0.05 | $1.25 | $2.50 | $2.00 | $7.50 | $0.10 | $2.50 | $5.00 | | gpt-6-luna | $0.10 | $0.50 | $0.01 | $0.125 | $0.25 | $0.20 | $0.75 | $0.02 |"
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       "above_threshold_cache_write_per_1m": {
        "data_status": "published",
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        "observed_at": "2026-11-09",
        "content_sha256": "f1ade44afc62fd8a12dd6e199bcecaa989a94c9b691aa620a34e1504ff62ff57",
        "quote": "### Standard pricing data | Model | Short context input | Short context output | Short context cached input | Short context 30m write | Short context 12h write | Long context input | Long context output | Long context cached input | Long context 30m write | Long context 12h write | | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | | gpt-6-astra | $10.00 | $50.00 | $1.00 | $12.50 | $25.00 | $20.00 | $75.00 | $2.00 | $25.00 | $50.00 | | gpt-6.1-sol | $2.00 | $10.00 | $0.10 | $2.50 | $5.00 | $4.00 | $15.00 | $0.20 | $5.00 | $10.00 | | gpt-6.1-terra | $1.00 | $5.00 | $0.05 | $1.25 | $2.50 | $2.00 | $7.50 | $0.10 | $2.50 | $5.00 | | gpt-6-luna | $0.10 | $0.50 | $0.01 | $0.125 | $0.25 | $0.20 | $0.75 | $0.02 | $0.25 |"
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       "quote": "### Standard pricing data | Model | Short context input | Short context output | Short context cached input | Short context 30m write | Short context 12h write | Long context input | Long context output | Long context cached input | Long context 30m write | Long context 12h write | | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | | gpt-6-astra | $10.00 | $50.00 | $1.00 | $12.50 | $25.00 | $20.00 | $75.00 | $2.00 | $25.00 | $50.00 | | gpt-6.1-sol | $2.00 | $10.00 | $0.10 | $2.50 | $5.00 | $4.00 | $15.00 | $0.20 | $5.00 | $10.00 | | gpt-6.1-terra | $1.00 | $5.00 | $0.05 | $1.25 | $2.50 | $2.00 | $7.50 | $0.10 | $2.50 | $5.00 | | gpt-6-luna | $0.10 | $0.50 | $0.01 | $0.125 | $0.25 | $0.20 | $0.75 | $0.02 | $0.25 | $0.50 | | gpt-6-sol | $2.00 | $10.00 |"
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       "quote": "### Standard pricing data | Model | Short context input | Short context output | Short context cached input | Short context 30m write | Short context 12h write | Long context input | Long context output | Long context cached input | Long context 30m write | Long context 12h write | | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | | gpt-6-astra | $10.00 | $50.00 | $1.00 | $12.50 | $25.00 | $20.00 | $75.00 | $2.00 | $25.00 | $50.00 | | gpt-6.1-sol | $2.00 | $10.00 | $0.10 | $2.50 | $5.00 | $4.00 | $15.00 | $0.20 | $5.00 | $10.00 | | gpt-6.1-terra | $1.00 | $5.00 | $0.05 | $1.25 | $2.50 | $2.00 | $7.50 | $0.10 | $2.50 | $5.00 | | gpt-6-luna | $0.10 | $0.50 | $0.01 | $0.125 | $0.25 | $0.20 | $0.75 | $0.02 | $0.25 | $0.50 | | gpt-6-sol | $2.00 | $10.00 | $0.20 |"
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       "content_sha256": "f1ade44afc62fd8a12dd6e199bcecaa989a94c9b691aa620a34e1504ff62ff57",
       "quote": "### Standard pricing data | Model | Short context input | Short context output | Short context cached input | Short context 30m write | Short context 12h write | Long context input | Long context output | Long context cached input | Long context 30m write | Long context 12h write | | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | | gpt-6-astra | $10.00 | $50.00 | $1.00 | $12.50 | $25.00 | $20.00 | $75.00 | $2.00 | $25.00 | $50.00 | | gpt-6.1-sol | $2.00 | $10.00 | $0.10 | $2.50 | $5.00 | $4.00 | $15.00 | $0.20 | $5.00 | $10.00 | | gpt-6.1-terra | $1.00 | $5.00 | $0.05 | $1.25 | $2.50 | $2.00 | $7.50 | $0.10 | $2.50 | $5.00 | | gpt-6-luna | $0.10 | $0.50 | $0.01 | $0.125 | $0.25 | $0.20 | $0.75 | $0.02 | $0.25 | $0.50 | | gpt-6-sol | $2.00 | $10.00 | $0.20 | $2.50 |"
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      "data_status": "published",
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      "fields": {
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        "observed_at": "2026-11-09",
        "content_sha256": "f1ade44afc62fd8a12dd6e199bcecaa989a94c9b691aa620a34e1504ff62ff57",
        "quote": "Short context: ≤272K input tokens. Long context: >272K input tokens."
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       "above_threshold_input_per_1m": {
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        "content_sha256": "f1ade44afc62fd8a12dd6e199bcecaa989a94c9b691aa620a34e1504ff62ff57",
        "quote": "### Standard pricing data | Model | Short context input | Short context output | Short context cached input | Short context 30m write | Short context 12h write | Long context input | Long context output | Long context cached input | Long context 30m write | Long context 12h write | | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | | gpt-6-astra | $10.00 | $50.00 | $1.00 | $12.50 | $25.00 | $20.00 | $75.00 | $2.00 | $25.00 | $50.00 | | gpt-6.1-sol | $2.00 | $10.00 | $0.10 | $2.50 | $5.00 | $4.00 | $15.00 | $0.20 | $5.00 | $10.00 | | gpt-6.1-terra | $1.00 | $5.00 | $0.05 | $1.25 | $2.50 | $2.00 | $7.50 | $0.10 | $2.50 | $5.00 | | gpt-6-luna | $0.10 | $0.50 | $0.01 | $0.125 | $0.25 | $0.20 | $0.75 | $0.02 | $0.25 | $0.50 | | gpt-6-sol | $2.00 | $10.00 | $0.20 | $2.50 | $5.00 | $4.00 |"
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        "quote": "### Standard pricing data | Model | Short context input | Short context output | Short context cached input | Short context 30m write | Short context 12h write | Long context input | Long context output | Long context cached input | Long context 30m write | Long context 12h write | | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | | gpt-6-astra | $10.00 | $50.00 | $1.00 | $12.50 | $25.00 | $20.00 | $75.00 | $2.00 | $25.00 | $50.00 | | gpt-6.1-sol | $2.00 | $10.00 | $0.10 | $2.50 | $5.00 | $4.00 | $15.00 | $0.20 | $5.00 | $10.00 | | gpt-6.1-terra | $1.00 | $5.00 | $0.05 | $1.25 | $2.50 | $2.00 | $7.50 | $0.10 | $2.50 | $5.00 | | gpt-6-luna | $0.10 | $0.50 | $0.01 | $0.125 | $0.25 | $0.20 | $0.75 | $0.02 | $0.25 | $0.50 | | gpt-6-sol | $2.00 | $10.00 | $0.20 | $2.50 | $5.00 | $4.00 | $15.00 |"
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        "quote": "### Standard pricing data | Model | Short context input | Short context output | Short context cached input | Short context 30m write | Short context 12h write | Long context input | Long context output | Long context cached input | Long context 30m write | Long context 12h write | | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | | gpt-6-astra | $10.00 | $50.00 | $1.00 | $12.50 | $25.00 | $20.00 | $75.00 | $2.00 | $25.00 | $50.00 | | gpt-6.1-sol | $2.00 | $10.00 | $0.10 | $2.50 | $5.00 | $4.00 | $15.00 | $0.20 | $5.00 | $10.00 | | gpt-6.1-terra | $1.00 | $5.00 | $0.05 | $1.25 | $2.50 | $2.00 | $7.50 | $0.10 | $2.50 | $5.00 | | gpt-6-luna | $0.10 | $0.50 | $0.01 | $0.125 | $0.25 | $0.20 | $0.75 | $0.02 | $0.25 | $0.50 | | gpt-6-sol | $2.00 | $10.00 | $0.20 | $2.50 | $5.00 | $4.00 | $15.00 | $0.40 |"
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        "quote": "### Standard pricing data | Model | Short context input | Short context output | Short context cached input | Short context 30m write | Short context 12h write | Long context input | Long context output | Long context cached input | Long context 30m write | Long context 12h write | | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | | gpt-6-astra | $10.00 | $50.00 | $1.00 | $12.50 | $25.00 | $20.00 | $75.00 | $2.00 | $25.00 | $50.00 | | gpt-6.1-sol | $2.00 | $10.00 | $0.10 | $2.50 | $5.00 | $4.00 | $15.00 | $0.20 | $5.00 | $10.00 | | gpt-6.1-terra | $1.00 | $5.00 | $0.05 | $1.25 | $2.50 | $2.00 | $7.50 | $0.10 | $2.50 | $5.00 | | gpt-6-luna | $0.10 | $0.50 | $0.01 | $0.125 | $0.25 | $0.20 | $0.75 | $0.02 | $0.25 | $0.50 | | gpt-6-sol | $2.00 | $10.00 | $0.20 | $2.50 | $5.00 | $4.00 | $15.00 | $0.40 | $5.00 |"
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     "data_status": "published",
     "source_url": "https://www.alibabacloud.com/help/en/model-studio/model-pricing",
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       "content_sha256": "b8fd14a206eb1ef01ffca95de6dd1233ce184650f7dddd93e557d3f9f61b3a80",
       "quote": "qwen3.8-flash context caching discount International 0<Token≤1M $0.15 $0.47 1 million tokens"
      },
      "output_per_1m": {
       "data_status": "published",
       "source_url": "https://www.alibabacloud.com/help/en/model-studio/model-pricing",
       "observed_at": "2026-11-09",
       "content_sha256": "b8fd14a206eb1ef01ffca95de6dd1233ce184650f7dddd93e557d3f9f61b3a80",
       "quote": "qwen3.8-flash context caching discount International 0<Token≤1M $0.15 $0.47 1 million tokens"
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     },
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     "cache_write_5m_per_1m": null,
     "cache_write_1h_per_1m": null,
     "cache_storage_per_1m_per_hour": null,
     "cache_note": "no cache price in our data for this channel",
     "context_cliff": {
      "has_cliff": false,
      "data_status": "unknown",
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     },
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      "quote": "Context Window 1000000; Max Output Length 131072; Max Input Length (Thinking Mode) 983616."
     },
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      },
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       },
       {
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        "source_url": "https://www.alibabacloud.com/help/en/model-studio/qwen-function-calling",
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      "answer": "no clause found",
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       "2026-10-20",
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      "snapshot_key": "meta-llama/llama-3.1-8b-instruct",
      "reasons": [
       "open-weights total parameters below editorial 14B floor"
      ],
      "total_params_billions": 8.03
     },
     {
      "model_id": "meta-llama-llama-3.2-1b-instruct",
      "snapshot_key": "meta-llama/llama-3.2-1b-instruct",
      "reasons": [
       "open-weights total parameters below editorial 14B floor"
      ],
      "total_params_billions": 1.236
     },
     {
      "model_id": "meta-llama-llama-3.2-3b-instruct",
      "snapshot_key": "meta-llama/llama-3.2-3b-instruct",
      "reasons": [
       "open-weights total parameters below editorial 14B floor"
      ],
      "total_params_billions": 3.213
     },
     {
      "model_id": "meta-llama-llama-guard-4-12b",
      "snapshot_key": "meta-llama/llama-guard-4-12b",
      "reasons": [
       "open-weights total parameters below editorial 14B floor"
      ],
      "total_params_billions": 12.001
     },
     {
      "model_id": "mistralai-ministral-14b-2512",
      "snapshot_key": "mistralai/ministral-14b-2512",
      "reasons": [
       "open-weights total parameters below editorial 14B floor"
      ],
      "total_params_billions": 13.945
     },
     {
      "model_id": "mistralai-ministral-3b-2512",
      "snapshot_key": "mistralai/ministral-3b-2512",
      "reasons": [
       "open-weights total parameters below editorial 14B floor"
      ],
      "total_params_billions": 3.849
     },
     {
      "model_id": "mistralai-ministral-8b-2512",
      "snapshot_key": "mistralai/ministral-8b-2512",
      "reasons": [
       "open-weights total parameters below editorial 14B floor"
      ],
      "total_params_billions": 8.918
     },
     {
      "model_id": "mistralai-ministral-8b-2512-batch",
      "snapshot_key": "mistralai/ministral-8b-2512",
      "reasons": [
       "open-weights total parameters below editorial 14B floor"
      ],
      "total_params_billions": 8.918
     },
     {
      "model_id": "mistralai-mistral-nemo",
      "snapshot_key": "mistralai/mistral-nemo",
      "reasons": [
       "open-weights total parameters below editorial 14B floor"
      ],
      "total_params_billions": 12.248
     },
     {
      "model_id": "moondream-moondream3-preview",
      "snapshot_key": "moondream/moondream3-preview-20261013",
      "reasons": [
       "open-weights total parameters below editorial 14B floor"
      ],
      "total_params_billions": 9.269
     },
     {
      "model_id": "moondream-moondream3.1-9b-a2b",
      "snapshot_key": "moondream/moondream3.1-9b-a2b-20261013",
      "reasons": [
       "open-weights total parameters below editorial 14B floor"
      ],
      "total_params_billions": 9.274
     },
     {
      "model_id": "nvidia-nemotron-3-nano-30b-a3b",
      "snapshot_key": "nvidia/nemotron-3-nano-30b-a3b",
      "reasons": [
       "explicit tier label: nano/micro/tiny/edge"
      ],
      "total_params_billions": 31.578
     },
     {
      "model_id": "nvidia-nemotron-3-nano-omni-30b-a3b-reasoning-free",
      "snapshot_key": "nvidia/nemotron-3-nano-omni-30b-a3b-reasoning-20260428",
      "reasons": [
       "explicit tier label: nano/micro/tiny/edge"
      ],
      "total_params_billions": 33.016
     },
     {
      "model_id": "nvidia-nemotron-3.5-content-safety",
      "snapshot_key": "nvidia/nemotron-3.5-content-safety-20260604",
      "reasons": [
       "open-weights total parameters below editorial 14B floor"
      ],
      "total_params_billions": 4.3
     },
     {
      "model_id": "nvidia-nemotron-3.5-content-safety-free",
      "snapshot_key": "nvidia/nemotron-3.5-content-safety-20260604",
      "reasons": [
       "open-weights total parameters below editorial 14B floor"
      ],
      "total_params_billions": 4.3
     },
     {
      "model_id": "openai-gpt-4.1-nano",
      "snapshot_key": "openai/gpt-4.1-nano-2025-04-14",
      "reasons": [
       "explicit tier label: nano/micro/tiny/edge"
      ],
      "total_params_billions": null
     },
     {
      "model_id": "openai-gpt-4.1-nano-batch",
      "snapshot_key": "openai/gpt-4.1-nano-2025-04-14",
      "reasons": [
       "explicit tier label: nano/micro/tiny/edge"
      ],
      "total_params_billions": null
     },
     {
      "model_id": "openai-gpt-5-nano",
      "snapshot_key": "openai/gpt-5-nano-2025-08-07",
      "reasons": [
       "explicit tier label: nano/micro/tiny/edge"
      ],
      "total_params_billions": null
     },
     {
      "model_id": "openai-gpt-5-nano-batch",
      "snapshot_key": "openai/gpt-5-nano-2025-08-07",
      "reasons": [
       "explicit tier label: nano/micro/tiny/edge"
      ],
      "total_params_billions": null
     },
     {
      "model_id": "openai-gpt-5.4-nano",
      "snapshot_key": "openai/gpt-5.4-nano-20260317",
      "reasons": [
       "explicit tier label: nano/micro/tiny/edge"
      ],
      "total_params_billions": null
     },
     {
      "model_id": "openai-gpt-5.4-nano-batch",
      "snapshot_key": "openai/gpt-5.4-nano-20260317",
      "reasons": [
       "explicit tier label: nano/micro/tiny/edge"
      ],
      "total_params_billions": null
     },
     {
      "model_id": "qwen-qwen-2.5-7b-instruct",
      "snapshot_key": "qwen/qwen-2.5-7b-instruct",
      "reasons": [
       "open-weights total parameters below editorial 14B floor"
      ],
      "total_params_billions": 7.616
     },
     {
      "model_id": "qwen-qwen3-vl-8b-instruct",
      "snapshot_key": "qwen/qwen3-vl-8b-instruct",
      "reasons": [
       "open-weights total parameters below editorial 14B floor"
      ],
      "total_params_billions": 8.767
     },
     {
      "model_id": "qwen-qwen3.5-9b",
      "snapshot_key": "qwen/qwen3.5-9b-20260310",
      "reasons": [
       "open-weights total parameters below editorial 14B floor"
      ],
      "total_params_billions": 9.653
     },
     {
      "model_id": "rekaai-reka-edge",
      "snapshot_key": "rekaai/reka-edge-2603",
      "reasons": [
       "explicit tier label: nano/micro/tiny/edge",
       "open-weights total parameters below editorial 14B floor"
      ],
      "total_params_billions": 7.129
     },
     {
      "model_id": "sao10k-l3-lunaris-8b",
      "snapshot_key": "sao10k/l3-lunaris-8b",
      "reasons": [
       "open-weights total parameters below editorial 14B floor"
      ],
      "total_params_billions": 8.03
     },
     {
      "model_id": "tencent-hy-mt2-1.8b",
      "snapshot_key": "tencent/hy-mt2-1.8b-20260521",
      "reasons": [
       "open-weights total parameters below editorial 14B floor"
      ],
      "total_params_billions": 2.039
     },
     {
      "model_id": "tencent-hy-mt2-7b",
      "snapshot_key": "tencent/hy-mt2-7b-20260521",
      "reasons": [
       "open-weights total parameters below editorial 14B floor"
      ],
      "total_params_billions": 8.03
     },
     {
      "model_id": "thedrummer-unslopnemo-12b",
      "snapshot_key": "thedrummer/unslopnemo-12b",
      "reasons": [
       "open-weights total parameters below editorial 14B floor"
      ],
      "total_params_billions": 12.248
     }
    ],
    "tiny_policy": {
     "open_weights_min_total_params_billions": 14,
     "denied_tier_labels": [
      "nano",
      "micro",
      "tiny",
      "edge"
     ],
     "own_monthly_run_does_not_override_deny": false,
     "closed_weights": "Temporary admission requires an exact configured snapshot; after transition numeric own data decides independent of closed/open weights.",
     "mini_is_not_automatically_tiny": true
    },
    "temporary_deny_scope": "The 38 tiny denies and family membership only govern the temporary branch. Two valid dates switch to numeric data first, so tiny size/name alone cannot defeat a passing measured floor.",
    "one_date": "collecting only; does not open a measured branch. Before transition only exact temporary config can admit the snapshot.",
    "expiry": "At temporary_expires_at 00:00 UTC, temporary admission stops until a reviewed config is published; globally activated snapshots remain in data mode with exact route/profile evidence required.",
    "transition_scope": "immutable snapshot_key and exact route_key; other unmeasured routes retain unexpired temporary admission unless an editorial-floor failure is recorded for this snapshot"
   },
   "independent_hard_gates": [
    "free variant or zero-price free route",
    "unknown or unapproved preview snapshot",
    "deprecated snapshot",
    "unknown required capability",
    "unsupported task modality",
    "fewer than two UTC price dates",
    "unknown or insufficient offer-specific context",
    "explicit user data/speed/quota requirements"
   ],
   "execution_gate": "Live execution additionally requires verified endpoint/adapter/identity/CORS; a calculated price is not execution permission.",
   "result_basis": [
    "temporary_configured_family",
    "own_two_date_data",
    "quality_floor_failed",
    "quality_floor_unknown"
   ],
   "note": "Temporary floor chosen by the owner on 2026-10-20. Editorial 0.50 safety threshold is configurable and due for review."
  },
  "quality_state": {
   "failed_snapshots": {},
   "quality_floor_mode_by_snapshot_route": {
    "[\"anthropic/claude-haiku-5.5-20261007\",\"[\\\"api.anthropic.com\\\",\\\"claude-haiku-5-5\\\",\\\"anthropic\\\",\\\"direct\\\",null]\"]": "data",
    "[\"deepseek/deepseek-v4-pro-20260813\",\"[\\\"api.deepseek.com\\\",\\\"deepseek-v4-pro\\\",\\\"deepseek\\\",\\\"direct\\\",null]\"]": "data",
    "[\"deepseek/deepseek-v4.1-flash-20261017\",\"[\\\"api.deepseek.com\\\",\\\"deepseek-flash\\\",\\\"deepseek\\\",\\\"direct\\\",null]\"]": "data",
    "[\"google/gemini-3.8-flash-20260902\",\"[\\\"generativelanguage.googleapis.com\\\",\\\"gemini-3.8-flash\\\",\\\"google\\\",\\\"direct\\\",null]\"]": "data",
    "[\"google/gemini-4-argon-20261013\",\"[\\\"generativelanguage.googleapis.com\\\",null,\\\"google\\\",\\\"direct\\\",null]\"]": "data",
    "[\"mistralai/mistral-large-4-0-20261006\",\"[\\\"api.mistral.ai\\\",null,\\\"mistral\\\",\\\"direct\\\",null]\"]": "data",
    "[\"moonshotai/kimi-k3-20260715\",\"[\\\"api.moonshot.ai\\\",null,\\\"moonshot\\\",\\\"direct\\\",null]\"]": "data",
    "[\"openai/gpt-5.4-mini-20260317\",\"[\\\"api.openai.com\\\",null,\\\"openai\\\",\\\"direct\\\",null]\"]": "data",
    "[\"openai/gpt-6-sol-20260922\",\"[\\\"api.openai.com\\\",\\\"gpt-6-sol\\\",\\\"openai\\\",\\\"direct\\\",null]\"]": "data",
    "[\"x-ai/grok-4.7-20260916\",\"[\\\"api.x.ai\\\",\\\"grok-4.7\\\",\\\"xai\\\",\\\"direct\\\",null]\"]": "data",
    "[\"z-ai/glm-5.3-20260816\",\"[\\\"api.z.ai\\\",null,\\\"zai\\\",\\\"direct\\\",null]\"]": "data"
   }
  },
  "tokenization_map": {
   "schema_version": "2.0-r4",
   "map_version": "2026-10-23-v2.0b",
   "source": {
    "engine": "dvizhok10",
    "coefficients_path": "zamery/ai-tokenizatory/koefficienty.json",
    "coefficients_sha256": "628441a378695953ab243637485c290139ab13484e1fb91468c09a1eca17a089",
    "samples_path": "zamery/ai-tokenizatory/etalony.json",
    "samples_sha256": "a201229ce0419aeee02fb58fe686b83401fc73901c3a7daddb9c9a83473066f7",
    "audit_date": "2026-10-23",
    "method": "Tokens of each reference text as counted by the provider, minus the count of a one-character message (the message wrapper), plus one; ratio to OpenAI o200k_base. Observed.",
    "published_counter_path": "/tools/token-counter/tokens.json",
    "published_samples_path": "/tools/token-counter/reference-texts.json",
    "published_counter_sha256": "fcffa25811ea2b3811507d4d0c8c4010f7452c39f7c36c613420a5ba8dc4890d",
    "published_dataset_version": "2026.10.20-r1",
    "published_ratio_rows": 12,
    "published_ratio_values_verified": 60,
    "published_ratio_values_match_measurement_records": true,
    "engine_commit": "9dbb28e",
    "note_2026_10_23": "Estonian and Russian reference texts added and all 23 probe models re-measured on 7 kinds (zamery/ai-tokenizatory/izmerit.py, 23:13–23:19 EEST). The published token counter (/tools/token-counter) still shows the five original kinds."
   },
   "public_language_values": [
    "english",
    "german",
    "french",
    "spanish",
    "chinese",
    "japanese",
    "estonian",
    "russian",
    "other",
    "unknown"
   ],
   "public_content_type_values": [
    "latin",
    "cyrillic",
    "cjk",
    "code",
    "other",
    "unknown"
   ],
   "public_content_format_values": [
    "prose",
    "source_code",
    "json",
    "unknown"
   ],
   "samples": [
    {
     "source_sample_id": "prose_en",
     "content_format": "prose",
     "languages": [
      "english"
     ],
     "measurement_scope": "single English prose reference text",
     "reference_o200k_base_tokens": 430,
     "independent_per_language_measurement": true,
     "content_types": [
      "latin"
     ]
    },
    {
     "source_sample_id": "european",
     "content_format": "prose",
     "languages": [
      "german",
      "french",
      "spanish"
     ],
     "measurement_scope": "one mixed German, French and Spanish reference text; shared ratio, not three independent measurements",
     "reference_o200k_base_tokens": 320,
     "independent_per_language_measurement": false,
     "content_types": [
      "latin"
     ]
    },
    {
     "source_sample_id": "cjk",
     "content_format": "prose",
     "languages": [
      "chinese",
      "japanese"
     ],
     "measurement_scope": "one mixed Chinese and Japanese reference text; shared ratio, no Korean sample",
     "reference_o200k_base_tokens": 306,
     "independent_per_language_measurement": false,
     "content_types": [
      "cjk"
     ]
    },
    {
     "source_sample_id": "code",
     "content_format": "source_code",
     "languages": [],
     "measurement_scope": "one mixed Python and JavaScript sample with English identifiers/comments",
     "reference_o200k_base_tokens": 557,
     "independent_per_language_measurement": false,
     "content_types": [
      "code"
     ]
    },
    {
     "source_sample_id": "json",
     "content_format": "json",
     "languages": [],
     "measurement_scope": "one JSON invoice sample with English keys and text values",
     "reference_o200k_base_tokens": 535,
     "independent_per_language_measurement": false,
     "content_types": [
      "code",
      "latin"
     ]
    },
    {
     "source_sample_id": "estonian",
     "content_format": "prose",
     "languages": [
      "estonian"
     ],
     "measurement_scope": "single Estonian prose reference text (a school letter to parents)",
     "reference_o200k_base_tokens": 331,
     "independent_per_language_measurement": true,
     "content_types": [
      "latin"
     ]
    },
    {
     "source_sample_id": "russian",
     "content_format": "prose",
     "languages": [
      "russian"
     ],
     "measurement_scope": "single Russian prose reference text (a school letter to parents)",
     "reference_o200k_base_tokens": 292,
     "independent_per_language_measurement": true,
     "content_types": [
      "cyrillic"
     ]
    }
   ],
   "resolution": {
    "prose": "Match content_type and workload.language against samples. Match must be unique; use the existing per-model ratio without recomputing or rounding it. Shared mixed samples remain labelled as mixed-sample estimates.",
    "source_code": "Only content_type=code and content_format=source_code select the code sample, conditional on user-confirmed applicability of the measured Python/JavaScript sample with English identifiers/comments. Another programming language or unconfirmed sample coverage yields no measured ratio: exact counts or an explicit override are required.",
    "json": "content_format=json with content_type in [code, latin] selects the json sample, only after explicit sample_coverage_confirmed=true for the measured invoice JSON with English keys and text values. Other contents or missing confirmation require exact model tokens or an explicit confirmed override. Never use source_code ratios for JSON.",
    "no_measured_coefficient_for_content_types": [
     "other",
     "unknown"
    ],
    "unmatched_or_ambiguous": "No measured ratio. Use exact model-token counts or an explicit token_factor_override recorded as an assumption; otherwise return unknown cost. Do not default to English or to ratio 1.",
    "missing_model": "No ratio transfer across models or offers. Require exact tokenizer/version identity before joining; preserve measured_at and source sample.",
    "reference_basis": "o200k_base",
    "rounding": "Stored ratio is preserved exactly; the existing counter rounds the final estimated token count to the nearest whole token.",
    "mixed_language_limit": "German, French and Spanish share one measured mixed sample; Chinese and Japanese share another. These are not independent coefficients for each language and are not evidence for every Latin/CJK language. Estonian and Russian each have their own single sample (measured 2026-10-23); other Cyrillic prose is estimated by the Russian sample and labelled, other Latin prose by the European sample.",
    "coverage_confirmation": "pricing.sample_coverage_confirmed defaults to false and is never extracted by the parser. Show resolved source_sample_id and measurement_scope; only an explicit user confirmation may set true, with a user provenance record at this exact pointer. Language/type/format/basis/model/sample or relevant content changes reset it false. Confirmation must cover inputs AND visible outputs/handoffs of every step and baseline; mixed prose input/JSON output has no common measured coefficient. No confirmation means unknown cost unless exact model_tokens or an explicit token_factor_override is confirmed. Other confirmed parameters do not imply applicability.",
    "token_basis": "For reference_tokens, first convert each step total input and visible output using the applicable K_s, rounding once per quantity; reasoning_tokens are already billable model tokens. Handoff stays A visible reference quantity until B conversion with K_B. Call the existing kernel with these preconverted quantities and K_tok=1 to avoid a second conversion. A common ratio is allowed only when confirmed applicable to both input and visible output; an explicit override remains an assumption.",
    "model_tokens_binding": "K=1 in model_tokens mode requires each step counted_for_offer_id to equal the exact evaluated candidate offer in the pinned dataset, with confirmed input/output counts. Baseline binds to the same strong offer. Different or missing identities keep candidate cost unknown; do not transfer by family or inferred tokenizer similarity. Reference-token steps require counted_for_offer_id=null. An offer change clears binding and invalidates count confirmations until recount/reconfirmation; changing only the ID is insufficient."
   },
   "models": {
    "openai-gpt-5.4-mini": {
     "measured_at": "2026-10-23T20:14:03Z",
     "method": "chat usage.prompt_tokens",
     "baseline_request_tokens": 7,
     "kinds": {
      "prose_en": {
       "request_tokens": 436,
       "tokens": 430,
       "o200k_base": 430,
       "ratio": 1.0
      },
      "code": {
       "request_tokens": 563,
       "tokens": 557,
       "o200k_base": 557,
       "ratio": 1.0
      },
      "json": {
       "request_tokens": 541,
       "tokens": 535,
       "o200k_base": 535,
       "ratio": 1.0
      },
      "european": {
       "request_tokens": 326,
       "tokens": 320,
       "o200k_base": 320,
       "ratio": 1.0
      },
      "cjk": {
       "request_tokens": 312,
       "tokens": 306,
       "o200k_base": 306,
       "ratio": 1.0
      },
      "estonian": {
       "request_tokens": 337,
       "tokens": 331,
       "o200k_base": 331,
       "ratio": 1.0
      },
      "russian": {
       "request_tokens": 298,
       "tokens": 292,
       "o200k_base": 292,
       "ratio": 1.0
      }
     },
     "provider": "openai",
     "api_model": "gpt-5.4-mini",
     "reported_model_id": "gpt-5.4-mini-2026-03-17"
    },
    "openai-gpt-6-astra": {
     "measured_at": "2026-10-23T20:14:34Z",
     "method": "chat usage.prompt_tokens",
     "baseline_request_tokens": 7,
     "kinds": {
      "prose_en": {
       "request_tokens": 436,
       "tokens": 430,
       "o200k_base": 430,
       "ratio": 1.0
      },
      "code": {
       "request_tokens": 563,
       "tokens": 557,
       "o200k_base": 557,
       "ratio": 1.0
      },
      "json": {
       "request_tokens": 541,
       "tokens": 535,
       "o200k_base": 535,
       "ratio": 1.0
      },
      "european": {
       "request_tokens": 326,
       "tokens": 320,
       "o200k_base": 320,
       "ratio": 1.0
      },
      "cjk": {
       "request_tokens": 312,
       "tokens": 306,
       "o200k_base": 306,
       "ratio": 1.0
      },
      "estonian": {
       "request_tokens": 337,
       "tokens": 331,
       "o200k_base": 331,
       "ratio": 1.0
      },
      "russian": {
       "request_tokens": 298,
       "tokens": 292,
       "o200k_base": 292,
       "ratio": 1.0
      }
     },
     "provider": "openai",
     "api_model": "gpt-6-astra",
     "reported_model_id": "gpt-6-astra"
    },
    "openai-gpt-6-sol": {
     "measured_at": "2026-10-23T20:14:50Z",
     "method": "chat usage.prompt_tokens",
     "baseline_request_tokens": 7,
     "kinds": {
      "prose_en": {
       "request_tokens": 436,
       "tokens": 430,
       "o200k_base": 430,
       "ratio": 1.0
      },
      "code": {
       "request_tokens": 563,
       "tokens": 557,
       "o200k_base": 557,
       "ratio": 1.0
      },
      "json": {
       "request_tokens": 541,
       "tokens": 535,
       "o200k_base": 535,
       "ratio": 1.0
      },
      "european": {
       "request_tokens": 326,
       "tokens": 320,
       "o200k_base": 320,
       "ratio": 1.0
      },
      "cjk": {
       "request_tokens": 312,
       "tokens": 306,
       "o200k_base": 306,
       "ratio": 1.0
      },
      "estonian": {
       "request_tokens": 337,
       "tokens": 331,
       "o200k_base": 331,
       "ratio": 1.0
      },
      "russian": {
       "request_tokens": 298,
       "tokens": 292,
       "o200k_base": 292,
       "ratio": 1.0
      }
     },
     "provider": "openai",
     "api_model": "gpt-6-sol",
     "reported_model_id": "gpt-6-sol"
    },
    "anthropic-claude-opus-5.5": {
     "measured_at": "2026-10-23T20:14:55Z",
     "method": "count_tokens",
     "baseline_request_tokens": 9,
     "kinds": {
      "prose_en": {
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}