{
  "version": 1,
  "fallback": "en",
  "ui": {
    "fallbackLabel": {
      "zh": "选择模型",
      "en": "Select model"
    },
    "triggerLabel": {
      "zh": "选择模型，当前 {model}",
      "en": "Select model, currently {model}"
    },
    "loading": {
      "zh": "正在加载模型…",
      "en": "Loading models…"
    },
    "empty": {
      "zh": "没有可用的模型。",
      "en": "No models available."
    },
    "effortLabel": {
      "zh": "推理等级",
      "en": "Reasoning effort"
    },
    "moreLabel": {
      "zh": "更多模型",
      "en": "More models"
    },
    "noEffort": {
      "zh": "当前模型未提供推理等级。",
      "en": "This model offers no reasoning levels."
    }
  },
  "settings": {
    "title": {
      "zh": "Claude Style",
      "en": "Claude Style"
    },
    "brandTitle": {
      "zh": "修改品牌标识",
      "en": "Brand mark"
    },
    "brandDesc": {
      "zh": "显示的LOGO",
      "en": "Which brand mark the sidebar shows. \"Off\" leaves the host's own brand area untouched."
    },
    "collapseTitle": {
      "zh": "重绘设置弹层",
      "en": "Collapse the sidebar settings area"
    },
    "collapseDesc": {
      "zh": "把侧栏底栏的设置入口收进账户弹层。",
      "en": "Fold the sidebar footer's settings entry into the account popover. Off hands the footer back to the host entirely: no account row, no mirrored popover entries."
    },
    "autoPopoverTitle": {
      "zh": "自动弹出弹层",
      "en": "Open popovers on hover"
    },
    "autoPopoverDesc": {
      "zh": "鼠标移入即展开账户、模型和权限弹层。",
      "en": "Hover opens the account, model, and permission popovers. Off switches them to click-to-open."
    },
    "composerTitle": {
      "zh": "对话框样式改动范围",
      "en": "Composer restyle"
    },
    "composerDesc": {
      "zh": "重绘输入区，可选新会话页、对话内或两者。",
      "en": "Which input area the skin restyles: the new-conversation page, the conversation, or both. The hero brand mark and headline are unaffected."
    },
    "usernameTitle": {
      "zh": "用户名",
      "en": "Username"
    },
    "usernameDesc": {
      "zh": "显示在新会话欢迎语中；留空则使用宿主解析到的系统用户名。",
      "en": "Shown in the new-conversation greeting. Leave empty to use the system username resolved by the host."
    },
    "usernamePlaceholder": {
      "zh": "自动解析系统用户",
      "en": "Auto-detect host user"
    },
    "brandOff": {
      "zh": "关闭",
      "en": "Off"
    },
    "brandClaude": {
      "zh": "Claude",
      "en": "Claude"
    },
    "brandAnthropic": {
      "zh": "Anthropic",
      "en": "Anthropic"
    },
    "scopeOff": {
      "zh": "关闭",
      "en": "Off"
    },
    "scopeHero": {
      "zh": "仅首页",
      "en": "Home only"
    },
    "scopeConversation": {
      "zh": "仅对话",
      "en": "Conversation only"
    },
    "scopeAll": {
      "zh": "全部",
      "en": "All"
    },
    "banLocaleTitle": {
      "zh": "封号彩蛋语言",
      "en": "Account-hold easter egg language"
    },
    "banLocaleDesc": {
      "zh": "账户横条彩蛋（点侧栏底栏账户弹层顶部那行用户名）里那页封号界面使用的语言。它是独立设置，不跟随界面语言——那页是 Claude 的原界面，按它本来的语言读才对。",
      "en": "The language the account-hold page is written in (click the account row at the top of the sidebar footer's popover). It is its own choice rather than following the interface language: the page reproduces Claude's own screen, so it reads the way Claude wrote it."
    },
    "banLocaleZh": {
      "zh": "中文",
      "en": "中文"
    },
    "banLocaleEn": {
      "zh": "English",
      "en": "English"
    },
    "unavailable": {
      "zh": "设置存储不可用，改动不会被保存。",
      "en": "The settings store is unavailable, so changes will not be saved."
    }
  },
  "ban": {
    "signOut": {
      "zh": "退出登录",
      "en": "Sign out"
    },
    "title": {
      "zh": "你的账户已被暂停",
      "en": "Your account is on hold"
    },
    "lead": {
      "zh": "由于活动异常，我们已于 <strong>{time}</strong> 暂停你的账户。你的对话与数据都还在。",
      "en": "We put your account on hold on <strong>{time}</strong> because of unusual activity. Your chats and data are safe."
    },
    "leadError": {
      "zh": "如果你认为这次暂停是误判，可以申请账户复核。",
      "en": "If you think this hold is an error, you can request an account review."
    },
    "nextLabel": {
      "zh": "接下来会发生什么：",
      "en": "What happens next:"
    },
    "step1Title": {
      "zh": "提交复核申请",
      "en": "Request a review"
    },
    "step1Desc": {
      "zh": "告诉我们当时发生了什么。",
      "en": "Tell us more about what happened."
    },
    "step2Title": {
      "zh": "我们会复核你的账户",
      "en": "We’ll review your account"
    },
    "step2Desc": {
      "zh": "团队成员会把你的申请与账户活动放在一起复核。",
      "en": "A team member will review your request and account activity together."
    },
    "step3Title": {
      "zh": "我们会把结果邮件给你",
      "en": "We’ll email you the outcome"
    },
    "step3Desc": {
      "zh": "复核大约需要 10 天。",
      "en": "Reviews take about 10 days."
    },
    "review": {
      "zh": "申请复核",
      "en": "Request a review"
    },
    "whatYouCanDo": {
      "zh": "你可以做的事",
      "en": "What you can do"
    },
    "exportTitle": {
      "zh": "导出你的数据",
      "en": "Export your data"
    },
    "exportDesc": {
      "zh": "我们会把你的对话、项目和设置打包供你下载。这可能需要一些时间。",
      "en": "We’ll package up your conversations, projects, and settings for download. This might take some time to complete."
    },
    "deleteTitle": {
      "zh": "删除你的账户",
      "en": "Delete your account"
    },
    "deleteDesc": {
      "zh": "你可以永久删除账户与数据。此操作不可撤销。",
      "en": "You can permanently delete your account and data. This can’t be undone."
    }
  },
  "exact": {
    "deepseek-flash": {
      "zh": "最新旗舰 Flash：百万上下文，长程 Agent 的 KV 缓存成本降到约 1/4。",
      "en": "Latest flagship Flash: 1M context with the KV-cache cost of long-horizon agents cut to about a quarter."
    },
    "deepseek-v4-flash": {
      "zh": "快速、高效、经济；适合目标明确、常规或并行任务。",
      "en": "Fast, efficient, and economical; suited to focused, routine, or parallel tasks."
    },
    "deepseek-v4-pro": {
      "zh": "自主编码、知识与复杂推理更强；适合质量优先的复杂任务，成本更高。",
      "en": "Stronger agentic coding, knowledge, and difficult reasoning; suited to complex or quality-critical tasks at higher cost."
    },
    "deepseek-v4-flash-vision-exp": {
      "zh": "实验性多模态：视觉理解大幅补强，多模态 Agent 能力接近 Opus-4.8。",
      "en": "Experimental multimodal Flash: much stronger visual understanding, multimodal agent ability approaching Opus-4.8."
    },
    "deepseek-v3.2": {
      "zh": "上一代通用模型，长上下文与成本仍然能打。",
      "en": "Previous-generation generalist; still competitive on long context and cost."
    },
    "claude-opus-4.8": {
      "zh": "旗舰：编程、Agent 与专业工作最强，长程任务一致性最好。",
      "en": "Flagship: strongest coding, agentic and professional work, with the consistency for long-running tasks."
    },
    "claude-sonnet-5": {
      "zh": "主力档：成本与能力平衡，部分场景追平 Opus。",
      "en": "The workhorse: balanced cost and capability, matching Opus in some cases."
    },
    "gpt-5.4": {
      "zh": "前沿通用模型，首个原生电脑操作能力，整合 Codex 编码能力。",
      "en": "Frontier generalist with native computer use and Codex-grade coding."
    },
    "gemini-3.8-flash": {
      "zh": "最强 Flash：跑分直逼旗舰，强化编程、Agent 与多步推理，价格仍低。",
      "en": "The strongest Flash: benchmark scores near flagship, with reinforced coding, agent workflows and multi-step reasoning."
    },
    "glm-5.3": {
      "zh": "前沿编码能力，擅长长程自主任务。",
      "en": "Frontier coding with strong long-horizon autonomy."
    },
    "glm-5.3-flash": {
      "zh": "GLM-5 系列首个原生多模态；18B 激活，性能追平 Opus-4.8，成本极低。",
      "en": "The GLM-5 series' first natively multimodal model; 18B active, matching Opus-4.8 at very low cost."
    },
    "glm-5.3-flashx": {
      "zh": "GLM-5.3-Flash 的高吞吐版本。",
      "en": "High-throughput variant of GLM-5.3-Flash."
    },
    "kimi-k3": {
      "zh": "开放 3T 级模型：原生视觉、百万上下文，编程与知识工作强。",
      "en": "Open 3T-class model: native vision, 1M context, strong at coding and knowledge work."
    },
    "kimi-for-coding": {
      "zh": "编程专用：稳定、便宜，适合日常改代码。",
      "en": "Coding-tuned: steady and cheap for everyday code work."
    },
    "kimi-for-coding-highspeed": {
      "zh": "与 K2.7 Code 同一模型，输出约 5–6 倍速，单价约 2 倍。",
      "en": "Same model as K2.7 Code at roughly 5–6x output speed and 2x the price."
    },
    "qwen3.8-max": {
      "zh": "通义旗舰：多模态与综合能力最强。",
      "en": "Qwen's flagship: strongest multimodality and overall capability."
    },
    "step-5-preview": {
      "zh": "阶跃下一代旗舰预览，百万上下文。",
      "en": "StepFun's next-generation flagship preview with a million-token context."
    },
    "step-3.7-flash": {
      "zh": "原生多模态，超高速：约 400 token/s，目前最快的一档。",
      "en": "Natively multimodal and extremely fast: around 400 tokens/s."
    },
    "minimax-m3": {
      "zh": "编程与 Agent 前沿，百万上下文，原生多模态。",
      "en": "Coding and agentic frontier with 1M context and native multimodality."
    },
    "grok-4.5": {
      "zh": "xAI 最强模型，主打编程。",
      "en": "xAI's strongest model, aimed at programming."
    },
    "doubao-seed-2.1": {
      "zh": "字节旗舰系列，分层定位，中文与多模态均衡。",
      "en": "ByteDance's flagship line, tiered, balanced across Chinese and multimodality."
    },
    "ernie-5.0": {
      "zh": "超稀疏 MoE，预训练成本极低，中文知识强。",
      "en": "Ultra-sparse MoE with very low training cost and strong Chinese knowledge."
    },
    "mistral-large-3": {
      "zh": "宽松许可的开源权重模型，综合能力强。",
      "en": "Permissively licensed open-weight model with strong overall capability."
    }
  },
  "aliases": {
    "deepseek-v4.1-flash": "deepseek-flash",
    "deepseek-v41-flash": "deepseek-flash",
    "k3": "kimi-k3",
    "k3-256k": "kimi-k3",
    "kimi-k2.7-code": "kimi-for-coding",
    "kimi-for-coding-highspeed-256k": "kimi-for-coding-highspeed",
    "ernie-5": "ernie-5.0",
    "minimax-m3-1m": "minimax-m3"
  },
  "brands": {
    "note": "Which brand mark a row shows. Every id names a vendored icon in src/assets/icons/lobe/ or src/assets/icons/providers/; scripts/build.mjs fails the build on an id that is not there. This is presentation data, kept out of the bundle like the rest of this document, and it is separate from the copy rules above: a vendor's mark and a vendor's description line change for different reasons. `providers` is keyed by the harness provider route id, which is exactly the group id the picker receives (`deepseek-official`, `zai`, `google-vertex`, …) — it is the mark on a level-2 group header. `models` is an ordered, anchored rule list resolved against the model id, exactly like `families` and with the same discipline: first match wins, so a broad rule must sit below the narrow ones and every rule must name its vendor (`step` cannot match `step-3.7-flash` by accident only if no earlier rule already claimed it). A model no rule matches falls back to its provider's mark; a provider no rule matches shows no mark, and the row keeps its alignment.",
    "providers": {
      "deepseek-official": "deepseek",
      "deepseek": "deepseek",
      "anthropic": "anthropic",
      "openai": "openai",
      "openai-codex": "codex",
      "google": "google",
      "google-vertex": "vertexai",
      "amazon-bedrock": "bedrock",
      "azure-openai-responses": "azure",
      "baseten": "baseten",
      "cerebras": "cerebras",
      "cloudflare-ai-gateway": "cloudflare",
      "cloudflare-workers-ai": "cloudflare",
      "fireworks": "fireworks",
      "github-copilot": "githubcopilot",
      "groq": "groq",
      "huggingface": "huggingface",
      "kimi-coding": "kimi",
      "minimax": "minimax",
      "minimax-cn": "minimax",
      "mistral": "mistral",
      "moonshotai": "moonshot",
      "moonshotai-cn": "moonshot",
      "nvidia": "nvidia",
      "opencode": "opencode",
      "opencode-go": "opencode",
      "openrouter": "openrouter",
      "qwen-token-plan": "qwen",
      "qwen-token-plan-cn": "qwen",
      "qwen-token-plan-individual": "qwen",
      "together": "together",
      "vercel-ai-gateway": "vercel",
      "xai": "xai",
      "xiaomi": "xiaomimimo",
      "xiaomi-token-plan-ams": "xiaomimimo",
      "xiaomi-token-plan-cn": "xiaomimimo",
      "xiaomi-token-plan-sgp": "xiaomimimo",
      "zai": "zai",
      "zai-coding-cn": "zai",
      "ant-ling": "antgroup"
    },
    "models": [
      {
        "match": "deepseek",
        "brand": "deepseek"
      },
      {
        "match": "claude",
        "brand": "anthropic"
      },
      {
        "match": "codex",
        "brand": "codex",
        "note": "Before the OpenAI rule: a Codex row shows the Codex mark, not the parent mark."
      },
      {
        "match": "gpt|(^|[/-])o[1-9](-|$)",
        "brand": "openai"
      },
      {
        "match": "gemini",
        "brand": "gemini",
        "note": "A Gemini row shows the model line's mark; the provider group header above it shows Google's, because providers resolve from `providers` and never from here."
      },
      {
        "match": "glm",
        "brand": "zai"
      },
      {
        "match": "kimi|(^|-)k3($|-)",
        "brand": "kimi"
      },
      {
        "match": "qwen",
        "brand": "qwen"
      },
      {
        "match": "step",
        "brand": "stepfun"
      },
      {
        "match": "minimax|(^|-)m[23]($|-)",
        "brand": "minimax"
      },
      {
        "match": "muse-spark|llama",
        "brand": "meta"
      },
      {
        "match": "celeris",
        "brand": "celestoai"
      },
      {
        "match": "mercury|inception",
        "brand": "inception"
      },
      {
        "match": "grok",
        "brand": "xai"
      },
      {
        "match": "doubao|seed|volc",
        "brand": "bytedance"
      },
      {
        "match": "ernie",
        "brand": "baidu"
      },
      {
        "match": "hunyuan|(^|-)hy\\d",
        "brand": "tencent"
      },
      {
        "match": "mistral|magistral|codestral",
        "brand": "mistral"
      },
      {
        "match": "north|command-?[ar]|cohere",
        "brand": "cohere"
      },
      {
        "match": "phi-?\\d",
        "brand": "microsoft"
      },
      {
        "match": "nova",
        "brand": "nova"
      },
      {
        "match": "sonar|perplexity",
        "brand": "perplexity"
      }
    ]
  },
  "families": [
    {
      "match": "^deepseek.*(v4[-.]?1|4[-.]?1).*flash$|^deepseek-flash$",
      "key": "deepseek-flash",
      "note": "Anchored on `deepseek` on purpose: an unanchored /flash$/ would hand this copy to glm-5.3-flash, step-3.7-flash and every other vendor's flash tier."
    },
    {
      "match": "deepseek.*vision",
      "key": "deepseek-v4-flash-vision-exp"
    },
    {
      "match": "deepseek.*pro",
      "key": "deepseek-v4-pro"
    },
    {
      "match": "deepseek.*flash",
      "key": "deepseek-v4-flash"
    },
    {
      "match": "deepseek.*(r1|reasoner|think)",
      "text": {
        "zh": "DeepSeek 推理专用：先思考再作答，适合数学、算法与难题。",
        "en": "DeepSeek reasoning-first: thinks before answering; best for math, algorithms and hard problems."
      }
    },
    {
      "match": "deepseek",
      "text": {
        "zh": "DeepSeek 通用模型：中文与代码均衡，长上下文性价比高。",
        "en": "DeepSeek generalist: balanced Chinese and code, strong long-context value."
      }
    },
    {
      "match": "claude.*opus",
      "note": "Family copy stays version-agnostic, so it carries no superlatives: 'strongest' is only true of the current generation and would mislabel an older Opus. Superlatives belong in version-pinned exact entries.",
      "text": {
        "zh": "Claude 旗舰档：编程、Agent 与专业工作，长程一致性见长。",
        "en": "Claude flagship tier: coding, agentic and professional work, strong on long-run consistency."
      }
    },
    {
      "match": "claude.*sonnet",
      "text": {
        "zh": "Claude 主力档：成本与能力平衡，日常首选。",
        "en": "Claude workhorse: balanced cost and capability, the everyday default."
      }
    },
    {
      "match": "claude.*haiku",
      "text": {
        "zh": "Claude 轻量档：低延迟、低成本，适合简单与高频任务。",
        "en": "Claude lightweight: low latency and cost for simple, high-frequency tasks."
      }
    },
    {
      "match": "claude",
      "text": {
        "zh": "Anthropic Claude 模型。",
        "en": "Anthropic Claude model."
      }
    },
    {
      "match": "codex",
      "text": {
        "zh": "OpenAI 编码专用：长程代码任务与重构。",
        "en": "OpenAI coding specialist for long-horizon code work and refactors."
      }
    },
    {
      "match": "gpt-?5",
      "text": {
        "zh": "OpenAI 通用模型，推理与编码均衡。",
        "en": "OpenAI generalist with balanced reasoning and coding."
      }
    },
    {
      "match": "(^|[/-])o[1-9](-|$)",
      "text": {
        "zh": "OpenAI 推理专用：先思考再作答，适合数学、算法与难题。",
        "en": "OpenAI reasoning-first: thinks before answering; best for math, algorithms and hard problems."
      }
    },
    {
      "match": "gpt-oss|oss-\\d",
      "text": {
        "zh": "OpenAI 开源权重系列：可自托管，成本低。",
        "en": "OpenAI's open-weight line: self-hostable at low cost."
      }
    },
    {
      "match": "gpt",
      "text": {
        "zh": "OpenAI 通用模型。",
        "en": "OpenAI general model."
      }
    },
    {
      "match": "gemini.*(pro|ultra)",
      "text": {
        "zh": "Gemini 旗舰档：世界知识与多模态见长，适合复杂长程任务。",
        "en": "Gemini flagship tier: world knowledge and multimodality for complex, long-horizon work."
      }
    },
    {
      "match": "gemini.*flash",
      "text": {
        "zh": "Gemini Flash：速度与成本优先。",
        "en": "Gemini Flash: speed and cost first."
      }
    },
    {
      "match": "gemini",
      "text": {
        "zh": "Google Gemini 模型。",
        "en": "Google Gemini model."
      }
    },
    {
      "match": "glm.*flashx",
      "key": "glm-5.3-flashx"
    },
    {
      "match": "glm.*flash",
      "text": {
        "zh": "GLM Flash：原生多模态，激活参数少、成本低。",
        "en": "GLM Flash: natively multimodal with few active parameters at low cost."
      }
    },
    {
      "match": "glm",
      "text": {
        "zh": "智谱 GLM：结构化输出与编码能力突出，适合 Agent 工作流。",
        "en": "Zhipu GLM: strong structured output and coding, well suited to agent workflows."
      }
    },
    {
      "match": "kimi.*(k3|k-?3)|^k3",
      "key": "kimi-k3"
    },
    {
      "match": "kimi.*(code|k2[-.]?7)",
      "key": "kimi-for-coding"
    },
    {
      "match": "kimi",
      "text": {
        "zh": "Moonshot Kimi：长文本见长，中文写作与知识工作强。",
        "en": "Moonshot Kimi: strong on long documents, Chinese writing and knowledge work."
      }
    },
    {
      "match": "qwen.*max",
      "key": "qwen3.8-max"
    },
    {
      "match": "qwen.*(coder|code)",
      "text": {
        "zh": "Qwen 代码专用：补全、生成与仓库级修改。",
        "en": "Qwen coding specialist for completion, generation and repo-level edits."
      }
    },
    {
      "match": "qwen.*(flash|turbo)",
      "text": {
        "zh": "Qwen 轻量档：响应快、成本低。",
        "en": "Qwen lightweight tier: fast responses at low cost."
      }
    },
    {
      "match": "qwen.*plus",
      "text": {
        "zh": "Qwen 中端档：能力与成本折中。",
        "en": "Qwen mid tier: a middle ground between capability and cost."
      }
    },
    {
      "match": "qwen.*a\\d+b",
      "note": "MoE ids spell out total and active parameters (`2.4t-a95b`, `235b-a22b`); the active count must win over the size rule below, which would otherwise read the trailing `95b` as a small dense model.",
      "text": {
        "zh": "大尺寸 MoE：总参大、激活参数少，单位成本低于同规模稠密模型。",
        "en": "Large MoE: many total parameters but few active, so it costs less than a dense model of the same size."
      }
    },
    {
      "match": "qwen.*[-_]\\d+b($|[^a-z])",
      "note": "Anchored to a separator so the digits start a segment: an unanchored \\d+b matches the `95b` inside `a95b` and calls a 2.4T MoE a small dense model.",
      "text": {
        "zh": "小尺寸稠密模型：可本地或低成本部署。",
        "en": "Small dense model: cheap to serve, or run locally."
      }
    },
    {
      "match": "qwen",
      "text": {
        "zh": "阿里通义千问：中文与多模态均衡。",
        "en": "Alibaba Qwen: balanced Chinese and multimodality."
      }
    },
    {
      "match": "step.*5",
      "key": "step-5-preview"
    },
    {
      "match": "step.*flash",
      "key": "step-3.7-flash"
    },
    {
      "match": "step",
      "text": {
        "zh": "阶跃星辰 Step 模型。",
        "en": "StepFun Step model."
      }
    },
    {
      "match": "minimax.*m3|(^|-)m3($|-)",
      "key": "minimax-m3"
    },
    {
      "match": "minimax|(^|-)m2[-.]?\\d",
      "text": {
        "zh": "MiniMax：性价比高，编程与长上下文兼顾。",
        "en": "MiniMax: good value, covering coding and long context."
      }
    },
    {
      "match": "muse-spark",
      "note": "Meta's agentic/coding line, separate from the Llama open-weight line — it must not inherit the Llama rule's copy.",
      "text": {
        "zh": "Meta 的 Agent 与编码线：面向 agentic 工作流与竞技编程，首答准确率更高。",
        "en": "Meta's agentic and coding line: built for agent workflows and competitive programming, with higher first-attempt accuracy."
      }
    },
    {
      "match": "celeris",
      "note": "Diffusion LLM, so the copy leads with latency rather than the usual capability framing.",
      "text": {
        "zh": "扩散式 LLM：实时级响应（实测中位约 1600 token/s），智能接近 GPT-5。",
        "en": "Diffusion LLM: real-time responses (about 1,600 tokens/s median) at near-GPT-5 intelligence."
      }
    },
    {
      "match": "mercury-?\\d|inception",
      "text": {
        "zh": "Inception Labs 扩散式 LLM：首个带推理的扩散模型，输出超 1000 token/s。",
        "en": "Inception Labs diffusion LLM: the first diffusion model with reasoning, over 1,000 tokens/s."
      }
    },
    {
      "match": "apodex",
      "text": {
        "zh": "面向复杂专业工作的 Agent 模型：金融与科研场景见长。",
        "en": "Agentic model for complex professional work, strong in finance and scientific research."
      }
    },
    {
      "match": "motif",
      "text": {
        "zh": "韩国 Motif Technologies 全自研开源权重 MoE：314B 总参 / 13.2B 激活。",
        "en": "Korea's Motif Technologies in-house open-weight MoE: 314B total / 13.2B active."
      }
    },
    {
      "match": "grok",
      "text": {
        "zh": "xAI Grok：风格直接，编程与实时知识强。",
        "en": "xAI Grok: direct style, strong at coding and current knowledge."
      }
    },
    {
      "match": "doubao|seed-?\\d|volc",
      "text": {
        "zh": "字节豆包：中文与多模态均衡，分层定位。",
        "en": "ByteDance Doubao: balanced Chinese and multimodality, tiered by use."
      }
    },
    {
      "match": "ernie",
      "text": {
        "zh": "百度文心：中文知识与检索增强强。",
        "en": "Baidu ERNIE: strong Chinese knowledge and retrieval augmentation."
      }
    },
    {
      "match": "hunyuan|(^|-)hy\\d",
      "text": {
        "zh": "腾讯混元：中文与 Agent 场景均衡。",
        "en": "Tencent Hunyuan: balanced for Chinese and agent scenarios."
      }
    },
    {
      "match": "codestral",
      "text": {
        "zh": "Mistral 代码专用：补全与生成。",
        "en": "Mistral coding specialist for completion and generation."
      }
    },
    {
      "match": "mistral|magistral",
      "text": {
        "zh": "Mistral：宽松许可，欧洲开源权重代表。",
        "en": "Mistral: permissively licensed European open-weight line."
      }
    },
    {
      "match": "llama",
      "text": {
        "zh": "Meta Llama 开源权重模型。",
        "en": "Meta Llama open-weight model."
      }
    },
    {
      "match": "north",
      "text": {
        "zh": "Cohere North：编码与 Agent 场景。",
        "en": "Cohere North: coding and agent scenarios."
      }
    },
    {
      "match": "command-?[ar]|cohere",
      "text": {
        "zh": "Cohere Command：企业检索与工具调用见长。",
        "en": "Cohere Command: strong at enterprise retrieval and tool use."
      }
    },
    {
      "match": "phi-?\\d",
      "text": {
        "zh": "微软 Phi 小模型：体积小、可本地部署。",
        "en": "Microsoft Phi small model: compact and locally deployable."
      }
    },
    {
      "match": "nova",
      "text": {
        "zh": "Amazon Nova 模型。",
        "en": "Amazon Nova model."
      }
    },
    {
      "match": "sonar|perplexity",
      "text": {
        "zh": "Perplexity Sonar：联网检索增强。",
        "en": "Perplexity Sonar: search-augmented."
      }
    }
  ],
  "tiers": [
    {
      "match": "flash|mini|lite|nano|turbo|air|small|swift|highspeed|fast|instant",
      "text": {
        "zh": "轻量档：响应快、成本低，适合简单或高频任务。",
        "en": "Lightweight tier: fast and cheap, for simple or high-frequency tasks."
      }
    },
    {
      "match": "pro|max|ultra|opus|thinking|reasoner|plus|large|advanced|heavy|frontier",
      "text": {
        "zh": "高能力档：适合复杂或质量优先的任务，成本更高。",
        "en": "High-capability tier: for complex, quality-first work at higher cost."
      }
    },
    {
      "match": "a\\d+b",
      "note": "MoE active-parameter suffix (`a95b`, `a23b`); tried before the dense rule so the active count is not mistaken for a total.",
      "text": {
        "zh": "MoE 架构：总参大、激活参数少，单位成本低于同规模稠密模型。",
        "en": "MoE: many total parameters but few active, so it costs less than a dense model of the same size."
      }
    },
    {
      "match": "(^|[-_])\\d+b($|[^a-z])",
      "note": "Anchored so the digits start a segment: unanchored, `a95b` and `a23b` read as small dense models.",
      "text": {
        "zh": "小尺寸稠密模型：可本地或低成本部署。",
        "en": "Small dense model: cheap to serve, or run locally."
      }
    }
  ]
}