> ## Documentation Index
> Fetch the complete documentation index at: https://docs.laozhang.ai/llms.txt
> Use this file to discover all available pages before exploring further.

# 模型与价格总表

> 按用途和厂商查询老张API当前在线模型：模型 ID、输入输出与按次价格、缓存和阶梯价格、令牌分组、调用接口，以及最近上线的模型。

export const MODELS = [{
  "n": "gpt-6.1-sol",
  "v": "OpenAI",
  "k": "text",
  "t": "文本对话",
  "p": "输入 $2 · 输出 $10 / 1M tokens",
  "a": "vendor-openai-text"
}, {
  "n": "gpt-6-astra",
  "v": "OpenAI",
  "k": "text",
  "t": "文本对话",
  "p": "输入 $10 · 输出 $50 / 1M tokens",
  "a": "vendor-openai-text"
}, {
  "n": "gpt-6-luna",
  "v": "OpenAI",
  "k": "text",
  "t": "文本对话",
  "p": "输入 $0.1 · 输出 $0.5 / 1M tokens",
  "a": "vendor-openai-text"
}, {
  "n": "gpt-6-sol",
  "v": "OpenAI",
  "k": "text",
  "t": "文本对话",
  "p": "输入 $2 · 输出 $10 / 1M tokens",
  "a": "vendor-openai-text"
}, {
  "n": "gpt-5.6-luna",
  "v": "OpenAI",
  "k": "text",
  "t": "文本对话",
  "p": "输入 $0.2 · 输出 $1.2 / 1M tokens",
  "a": "vendor-openai-text"
}, {
  "n": "gpt-5.6-sol",
  "v": "OpenAI",
  "k": "text",
  "t": "文本对话",
  "p": "输入 $4 · 输出 $20 / 1M tokens",
  "a": "vendor-openai-text"
}, {
  "n": "gpt-5.6-terra",
  "v": "OpenAI",
  "k": "text",
  "t": "文本对话",
  "p": "输入 $2 · 输出 $12 / 1M tokens",
  "a": "vendor-openai-text"
}, {
  "n": "gpt-5.5",
  "v": "OpenAI",
  "k": "text",
  "t": "文本对话",
  "p": "输入 $5 · 输出 $30 / 1M tokens",
  "a": "vendor-openai-text"
}, {
  "n": "gpt-5.5-pro",
  "v": "OpenAI",
  "k": "text",
  "t": "文本对话",
  "p": "输入 $30 · 输出 $180 / 1M tokens",
  "a": "vendor-openai-text"
}, {
  "n": "gpt-5.4",
  "v": "OpenAI",
  "k": "text",
  "t": "文本对话",
  "p": "输入 $2.5 · 输出 $15 / 1M tokens",
  "a": "vendor-openai-text"
}, {
  "n": "gpt-5.4-mini",
  "v": "OpenAI",
  "k": "text",
  "t": "文本对话",
  "p": "输入 $0.75 · 输出 $4.5 / 1M tokens",
  "a": "vendor-openai-text"
}, {
  "n": "gpt-5.4-nano",
  "v": "OpenAI",
  "k": "text",
  "t": "文本对话",
  "p": "输入 $0.2 · 输出 $1.25 / 1M tokens",
  "a": "vendor-openai-text"
}, {
  "n": "gpt-5.4-pro",
  "v": "OpenAI",
  "k": "text",
  "t": "文本对话",
  "p": "输入 $30 · 输出 $180 / 1M tokens",
  "a": "vendor-openai-text"
}, {
  "n": "gpt-5.2",
  "v": "OpenAI",
  "k": "text",
  "t": "文本对话",
  "p": "输入 $1.75 · 输出 $14 / 1M tokens",
  "a": "vendor-openai-text"
}, {
  "n": "gpt-5.2-2025-12-11",
  "v": "OpenAI",
  "k": "text",
  "t": "文本对话",
  "p": "输入 $1.75 · 输出 $14 / 1M tokens",
  "a": "vendor-openai-text"
}, {
  "n": "gpt-5.1",
  "v": "OpenAI",
  "k": "text",
  "t": "文本对话",
  "p": "输入 $1.25 · 输出 $10 / 1M tokens",
  "a": "vendor-openai-text"
}, {
  "n": "gpt-5.1-2025-11-13",
  "v": "OpenAI",
  "k": "text",
  "t": "文本对话",
  "p": "输入 $1.25 · 输出 $10 / 1M tokens",
  "a": "vendor-openai-text"
}, {
  "n": "gpt-5",
  "v": "OpenAI",
  "k": "text",
  "t": "文本对话",
  "p": "输入 $1.25 · 输出 $10 / 1M tokens",
  "a": "vendor-openai-text"
}, {
  "n": "gpt-5-chat",
  "v": "OpenAI",
  "k": "text",
  "t": "文本对话",
  "p": "输入 $1.25 · 输出 $10 / 1M tokens",
  "a": "vendor-openai-text"
}, {
  "n": "gpt-5-mini",
  "v": "OpenAI",
  "k": "text",
  "t": "文本对话",
  "p": "输入 $0.25 · 输出 $2 / 1M tokens",
  "a": "vendor-openai-text"
}, {
  "n": "gpt-5-nano",
  "v": "OpenAI",
  "k": "text",
  "t": "文本对话",
  "p": "输入 $0.05 · 输出 $0.4 / 1M tokens",
  "a": "vendor-openai-text"
}, {
  "n": "gpt-5-pro",
  "v": "OpenAI",
  "k": "text",
  "t": "文本对话",
  "p": "输入 $15 · 输出 $120 / 1M tokens",
  "a": "vendor-openai-text"
}, {
  "n": "gpt-5-pro-2025-10-06",
  "v": "OpenAI",
  "k": "text",
  "t": "文本对话",
  "p": "输入 $15 · 输出 $120 / 1M tokens",
  "a": "vendor-openai-text"
}, {
  "n": "gpt-5-2025-08-07",
  "v": "OpenAI",
  "k": "text",
  "t": "文本对话",
  "p": "输入 $1.25 · 输出 $10 / 1M tokens",
  "a": "vendor-openai-text"
}, {
  "n": "gpt-5-mini-2025-08-07",
  "v": "OpenAI",
  "k": "text",
  "t": "文本对话",
  "p": "输入 $0.25 · 输出 $2 / 1M tokens",
  "a": "vendor-openai-text"
}, {
  "n": "gpt-5-nano-2025-08-07",
  "v": "OpenAI",
  "k": "text",
  "t": "文本对话",
  "p": "输入 $0.05 · 输出 $0.4 / 1M tokens",
  "a": "vendor-openai-text"
}, {
  "n": "gpt-4.1",
  "v": "OpenAI",
  "k": "text",
  "t": "文本对话",
  "p": "输入 $2 · 输出 $8 / 1M tokens",
  "a": "vendor-openai-text"
}, {
  "n": "gpt-4.1-mini",
  "v": "OpenAI",
  "k": "text",
  "t": "文本对话",
  "p": "输入 $0.4 · 输出 $1.6 / 1M tokens",
  "a": "vendor-openai-text"
}, {
  "n": "gpt-4.1-nano",
  "v": "OpenAI",
  "k": "text",
  "t": "文本对话",
  "p": "输入 $0.1 · 输出 $0.4 / 1M tokens",
  "a": "vendor-openai-text"
}, {
  "n": "gpt-4.1-2025-04-14",
  "v": "OpenAI",
  "k": "text",
  "t": "文本对话",
  "p": "输入 $2 · 输出 $8 / 1M tokens",
  "a": "vendor-openai-text"
}, {
  "n": "gpt-4.1-mini-2025-04-14",
  "v": "OpenAI",
  "k": "text",
  "t": "文本对话",
  "p": "输入 $0.4 · 输出 $1.6 / 1M tokens",
  "a": "vendor-openai-text"
}, {
  "n": "gpt-4.1-nano-2025-04-14",
  "v": "OpenAI",
  "k": "text",
  "t": "文本对话",
  "p": "输入 $0.1 · 输出 $0.4 / 1M tokens",
  "a": "vendor-openai-text"
}, {
  "n": "gpt-4o",
  "v": "OpenAI",
  "k": "text",
  "t": "文本对话",
  "p": "输入 $2.5 · 输出 $10 / 1M tokens",
  "a": "vendor-openai-text"
}, {
  "n": "gpt-4o-audio-preview",
  "v": "OpenAI",
  "k": "audio",
  "t": "语音与音频",
  "p": "输入 $2.5 · 输出 $10 / 1M tokens",
  "a": "vendor-openai-audio"
}, {
  "n": "gpt-4o-mini",
  "v": "OpenAI",
  "k": "text",
  "t": "文本对话",
  "p": "输入 $0.15 · 输出 $0.6 / 1M tokens",
  "a": "vendor-openai-text"
}, {
  "n": "gpt-4o-mini-audio-preview",
  "v": "OpenAI",
  "k": "audio",
  "t": "语音与音频",
  "p": "输入 $2 · 输出 $8 / 1M tokens",
  "a": "vendor-openai-audio"
}, {
  "n": "gpt-4o-mini-transcribe",
  "v": "OpenAI",
  "k": "audio",
  "t": "语音与音频",
  "p": "输入 $1.5 · 输出 $6 / 1M tokens",
  "a": "vendor-openai-audio"
}, {
  "n": "gpt-4o-mini-tts",
  "v": "OpenAI",
  "k": "audio",
  "t": "语音与音频",
  "p": "输入 $1.2 · 输出 $18 / 1M tokens",
  "a": "vendor-openai-audio"
}, {
  "n": "gpt-4o-transcribe",
  "v": "OpenAI",
  "k": "audio",
  "t": "语音与音频",
  "p": "输入 $8 · 输出 $16 / 1M tokens",
  "a": "vendor-openai-audio"
}, {
  "n": "o4-mini",
  "v": "OpenAI",
  "k": "text",
  "t": "文本对话",
  "p": "输入 $1.1 · 输出 $4.4 / 1M tokens",
  "a": "vendor-openai-text"
}, {
  "n": "o4-mini-2025-04-16",
  "v": "OpenAI",
  "k": "text",
  "t": "文本对话",
  "p": "输入 $1.1 · 输出 $4.4 / 1M tokens",
  "a": "vendor-openai-text"
}, {
  "n": "gpt-4o-2024-11-20",
  "v": "OpenAI",
  "k": "text",
  "t": "文本对话",
  "p": "输入 $2.5 · 输出 $10 / 1M tokens",
  "a": "vendor-openai-text"
}, {
  "n": "gpt-4o-2024-08-06",
  "v": "OpenAI",
  "k": "text",
  "t": "文本对话",
  "p": "输入 $2.5 · 输出 $10 / 1M tokens",
  "a": "vendor-openai-text"
}, {
  "n": "gpt-4o-mini-2024-07-18",
  "v": "OpenAI",
  "k": "text",
  "t": "文本对话",
  "p": "输入 $0.15 · 输出 $0.6 / 1M tokens",
  "a": "vendor-openai-text"
}, {
  "n": "gpt-4o-2024-05-13",
  "v": "OpenAI",
  "k": "text",
  "t": "文本对话",
  "p": "输入 $5 · 输出 $15 / 1M tokens",
  "a": "vendor-openai-text"
}, {
  "n": "gpt-3.5-turbo",
  "v": "OpenAI",
  "k": "text",
  "t": "文本对话",
  "p": "输入 $0.5 · 输出 $1.5 / 1M tokens",
  "a": "vendor-openai-text"
}, {
  "n": "gpt-3.5-turbo-0125",
  "v": "OpenAI",
  "k": "text",
  "t": "文本对话",
  "p": "输入 $0.5 · 输出 $1.5 / 1M tokens",
  "a": "vendor-openai-text"
}, {
  "n": "gpt-3.5-turbo-0613",
  "v": "OpenAI",
  "k": "text",
  "t": "文本对话",
  "p": "输入 $1.5 · 输出 $1.95 / 1M tokens",
  "a": "vendor-openai-text"
}, {
  "n": "gpt-3.5-turbo-1106",
  "v": "OpenAI",
  "k": "text",
  "t": "文本对话",
  "p": "输入 $1 · 输出 $2 / 1M tokens",
  "a": "vendor-openai-text"
}, {
  "n": "gpt-3.5-turbo-16k",
  "v": "OpenAI",
  "k": "text",
  "t": "文本对话",
  "p": "输入 $3 · 输出 $3.9 / 1M tokens",
  "a": "vendor-openai-text"
}, {
  "n": "gpt-3.5-turbo-16k-0613",
  "v": "OpenAI",
  "k": "text",
  "t": "文本对话",
  "p": "输入 $3 · 输出 $3.9 / 1M tokens",
  "a": "vendor-openai-text"
}, {
  "n": "gpt-3.5-turbo-instruct",
  "v": "OpenAI",
  "k": "text",
  "t": "文本对话",
  "p": "输入 $1.5 · 输出 $1.95 / 1M tokens",
  "a": "vendor-openai-text"
}, {
  "n": "o3",
  "v": "OpenAI",
  "k": "text",
  "t": "文本对话",
  "p": "输入 $3 · 输出 $12 / 1M tokens",
  "a": "vendor-openai-text"
}, {
  "n": "o3-mini",
  "v": "OpenAI",
  "k": "text",
  "t": "文本对话",
  "p": "输入 $1.1 · 输出 $4.4 / 1M tokens",
  "a": "vendor-openai-text"
}, {
  "n": "o3-mini-low",
  "v": "OpenAI",
  "k": "text",
  "t": "文本对话",
  "p": "输入 $1.1 · 输出 $4.4 / 1M tokens",
  "a": "vendor-openai-text"
}, {
  "n": "o3-mini-medium",
  "v": "OpenAI",
  "k": "text",
  "t": "文本对话",
  "p": "输入 $1.1 · 输出 $4.4 / 1M tokens",
  "a": "vendor-openai-text"
}, {
  "n": "o3-pro",
  "v": "OpenAI",
  "k": "text",
  "t": "文本对话",
  "p": "输入 $20 · 输出 $80 / 1M tokens",
  "a": "vendor-openai-text"
}, {
  "n": "text-embedding-3-large",
  "v": "OpenAI",
  "k": "embedding",
  "t": "向量嵌入",
  "p": "输入 $0.13 · 输出 $0.13 / 1M tokens",
  "a": "vendor-openai-embedding"
}, {
  "n": "text-embedding-3-small",
  "v": "OpenAI",
  "k": "embedding",
  "t": "向量嵌入",
  "p": "输入 $0.02 · 输出 $0.02 / 1M tokens",
  "a": "vendor-openai-embedding"
}, {
  "n": "o3-pro-2025-06-10",
  "v": "OpenAI",
  "k": "text",
  "t": "文本对话",
  "p": "输入 $20 · 输出 $80 / 1M tokens",
  "a": "vendor-openai-text"
}, {
  "n": "o3-2025-04-16",
  "v": "OpenAI",
  "k": "text",
  "t": "文本对话",
  "p": "输入 $3 · 输出 $12 / 1M tokens",
  "a": "vendor-openai-text"
}, {
  "n": "o3-mini-2025-01-31",
  "v": "OpenAI",
  "k": "text",
  "t": "文本对话",
  "p": "输入 $1.1 · 输出 $4.4 / 1M tokens",
  "a": "vendor-openai-text"
}, {
  "n": "o3-mini-2025-01-31-high",
  "v": "OpenAI",
  "k": "text",
  "t": "文本对话",
  "p": "输入 $1.1 · 输出 $4.4 / 1M tokens",
  "a": "vendor-openai-text"
}, {
  "n": "o3-mini-2025-01-31-low",
  "v": "OpenAI",
  "k": "text",
  "t": "文本对话",
  "p": "输入 $1.1 · 输出 $4.4 / 1M tokens",
  "a": "vendor-openai-text"
}, {
  "n": "o3-mini-2025-01-31-medium",
  "v": "OpenAI",
  "k": "text",
  "t": "文本对话",
  "p": "输入 $1.1 · 输出 $4.4 / 1M tokens",
  "a": "vendor-openai-text"
}, {
  "n": "gpt-image-2.5-flare",
  "v": "OpenAI",
  "k": "image",
  "t": "图像生成与编辑",
  "p": "输入 $5 · 输出 $30 / 1M tokens",
  "a": "vendor-openai-image"
}, {
  "n": "gpt-image-2.5-flare-vip",
  "v": "OpenAI",
  "k": "image",
  "t": "图像生成与编辑",
  "p": "$0.03 / 次",
  "a": "vendor-openai-image"
}, {
  "n": "gpt-image-2.5-sunburst",
  "v": "OpenAI",
  "k": "image",
  "t": "图像生成与编辑",
  "p": "输入 $5 · 输出 $30 / 1M tokens",
  "a": "vendor-openai-image"
}, {
  "n": "gpt-image-2.5-sunburst-vip",
  "v": "OpenAI",
  "k": "image",
  "t": "图像生成与编辑",
  "p": "$0.03 / 次",
  "a": "vendor-openai-image"
}, {
  "n": "gpt-image-2.5-web",
  "v": "OpenAI",
  "k": "image",
  "t": "图像生成与编辑",
  "p": "$0.03 / 次",
  "a": "vendor-openai-image"
}, {
  "n": "gpt-image-2.5-flare-2026-09-08",
  "v": "OpenAI",
  "k": "image",
  "t": "图像生成与编辑",
  "p": "输入 $5 · 输出 $30 / 1M tokens",
  "a": "vendor-openai-image"
}, {
  "n": "gpt-image-2.5-sunburst-2026-09-08",
  "v": "OpenAI",
  "k": "image",
  "t": "图像生成与编辑",
  "p": "输入 $5 · 输出 $30 / 1M tokens",
  "a": "vendor-openai-image"
}, {
  "n": "gpt-image-2",
  "v": "OpenAI",
  "k": "image",
  "t": "图像生成与编辑",
  "p": "$0.03 / 次",
  "a": "vendor-openai-image"
}, {
  "n": "gpt-image-2-all",
  "v": "OpenAI",
  "k": "image",
  "t": "图像生成与编辑",
  "p": "$0.03 / 次",
  "a": "vendor-openai-image"
}, {
  "n": "gpt-image-2-vip",
  "v": "OpenAI",
  "k": "image",
  "t": "图像生成与编辑",
  "p": "$0.03 / 次",
  "a": "vendor-openai-image"
}, {
  "n": "gpt-image-2-web",
  "v": "OpenAI",
  "k": "image",
  "t": "图像生成与编辑",
  "p": "$0.03 / 次",
  "a": "vendor-openai-image"
}, {
  "n": "text-embedding-ada-002",
  "v": "OpenAI",
  "k": "embedding",
  "t": "向量嵌入",
  "p": "输入 $0.1 · 输出 $0.1 / 1M tokens",
  "a": "vendor-openai-embedding"
}, {
  "n": "gpt-image-1.5",
  "v": "OpenAI",
  "k": "image",
  "t": "图像生成与编辑",
  "p": "输入 $5 · 输出 $32 / 1M tokens",
  "a": "vendor-openai-image"
}, {
  "n": "gpt-image-1.5-2025-12-16",
  "v": "OpenAI",
  "k": "image",
  "t": "图像生成与编辑",
  "p": "输入 $5 · 输出 $32 / 1M tokens",
  "a": "vendor-openai-image"
}, {
  "n": "gpt-image-1",
  "v": "OpenAI",
  "k": "image",
  "t": "图像生成与编辑",
  "p": "输入 $5 · 输出 $40 / 1M tokens",
  "a": "vendor-openai-image"
}, {
  "n": "gpt-image-1-mini",
  "v": "OpenAI",
  "k": "image",
  "t": "图像生成与编辑",
  "p": "输入 $2 · 输出 $8 / 1M tokens",
  "a": "vendor-openai-image"
}, {
  "n": "o1",
  "v": "OpenAI",
  "k": "text",
  "t": "文本对话",
  "p": "输入 $15 · 输出 $60 / 1M tokens",
  "a": "vendor-openai-text"
}, {
  "n": "o1-mini",
  "v": "OpenAI",
  "k": "text",
  "t": "文本对话",
  "p": "输入 $1.1 · 输出 $4.4 / 1M tokens",
  "a": "vendor-openai-text"
}, {
  "n": "o1-preview",
  "v": "OpenAI",
  "k": "text",
  "t": "文本对话",
  "p": "输入 $15 · 输出 $60 / 1M tokens",
  "a": "vendor-openai-text"
}, {
  "n": "o1-pro",
  "v": "OpenAI",
  "k": "text",
  "t": "文本对话",
  "p": "输入 $180 · 输出 $720 / 1M tokens",
  "a": "vendor-openai-text"
}, {
  "n": "tts-1",
  "v": "OpenAI",
  "k": "audio",
  "t": "语音与音频",
  "p": "输入 $30 · 输出 $30 / 1M tokens",
  "a": "vendor-openai-audio"
}, {
  "n": "tts-1-hd",
  "v": "OpenAI",
  "k": "audio",
  "t": "语音与音频",
  "p": "输入 $60 · 输出 $60 / 1M tokens",
  "a": "vendor-openai-audio"
}, {
  "n": "whisper-1",
  "v": "OpenAI",
  "k": "audio",
  "t": "语音与音频",
  "p": "输入 $60 · 输出 $0 / 1M tokens",
  "a": "vendor-openai-audio"
}, {
  "n": "o1-pro-2025-03-19",
  "v": "OpenAI",
  "k": "text",
  "t": "文本对话",
  "p": "输入 $180 · 输出 $720 / 1M tokens",
  "a": "vendor-openai-text"
}, {
  "n": "o1-2024-12-17",
  "v": "OpenAI",
  "k": "text",
  "t": "文本对话",
  "p": "输入 $15 · 输出 $60 / 1M tokens",
  "a": "vendor-openai-text"
}, {
  "n": "o1-mini-2024-09-12",
  "v": "OpenAI",
  "k": "text",
  "t": "文本对话",
  "p": "输入 $1.1 · 输出 $4.4 / 1M tokens",
  "a": "vendor-openai-text"
}, {
  "n": "o1-preview-2024-09-12",
  "v": "OpenAI",
  "k": "text",
  "t": "文本对话",
  "p": "输入 $15 · 输出 $60 / 1M tokens",
  "a": "vendor-openai-text"
}, {
  "n": "omni-moderation-latest",
  "v": "OpenAI",
  "k": "moderation",
  "t": "内容审核",
  "p": "输入 $0.2 · 输出 $0.2 / 1M tokens",
  "a": "vendor-openai-moderation"
}, {
  "n": "gpt-oss-120b",
  "v": "OpenAI",
  "k": "text",
  "t": "文本对话",
  "p": "输入 $0.5 · 输出 $2 / 1M tokens",
  "a": "vendor-openai-text"
}, {
  "n": "gpt-oss-20b",
  "v": "OpenAI",
  "k": "text",
  "t": "文本对话",
  "p": "输入 $0.1 · 输出 $0.4 / 1M tokens",
  "a": "vendor-openai-text"
}, {
  "n": "omni-moderation-2024-09-26",
  "v": "OpenAI",
  "k": "moderation",
  "t": "内容审核",
  "p": "输入 $0.2 · 输出 $0.2 / 1M tokens",
  "a": "vendor-openai-moderation"
}, {
  "n": "gemini-3.8-flash",
  "v": "Google",
  "k": "text",
  "t": "文本对话",
  "p": "输入 $0.75 · 输出 $3.75 / 1M tokens",
  "a": "vendor-google-text"
}, {
  "n": "gemini-3.7-flash",
  "v": "Google",
  "k": "text",
  "t": "文本对话",
  "p": "输入 $0.75 · 输出 $3.75 / 1M tokens",
  "a": "vendor-google-text"
}, {
  "n": "gemini-3.6-flash",
  "v": "Google",
  "k": "text",
  "t": "文本对话",
  "p": "输入 $1.5 · 输出 $7.5 / 1M tokens",
  "a": "vendor-google-text"
}, {
  "n": "gemini-3.5-flash",
  "v": "Google",
  "k": "text",
  "t": "文本对话",
  "p": "输入 $1.5 · 输出 $9 / 1M tokens",
  "a": "vendor-google-text"
}, {
  "n": "gemini-3.5-flash-lite",
  "v": "Google",
  "k": "text",
  "t": "文本对话",
  "p": "输入 $0.3 · 输出 $2.502 / 1M tokens",
  "a": "vendor-google-text"
}, {
  "n": "gemini-3.1-flash-image",
  "v": "Google",
  "k": "image",
  "t": "图像生成与编辑",
  "p": "$0.055 / 次",
  "a": "vendor-google-image"
}, {
  "n": "gemini-3.1-flash-image-preview",
  "v": "Google",
  "k": "image",
  "t": "图像生成与编辑",
  "p": "$0.055 / 次",
  "a": "vendor-google-image"
}, {
  "n": "gemini-3.1-flash-lite",
  "v": "Google",
  "k": "text",
  "t": "文本对话",
  "p": "输入 $0.25 · 输出 $1.5 / 1M tokens",
  "a": "vendor-google-text"
}, {
  "n": "gemini-3.1-flash-lite-image",
  "v": "Google",
  "k": "image",
  "t": "图像生成与编辑",
  "p": "$0.025 / 次",
  "a": "vendor-google-image"
}, {
  "n": "gemini-3.1-flash-lite-preview",
  "v": "Google",
  "k": "text",
  "t": "文本对话",
  "p": "输入 $0.25 · 输出 $1.5 / 1M tokens",
  "a": "vendor-google-text"
}, {
  "n": "gemini-3.1-pro-preview",
  "v": "Google",
  "k": "text",
  "t": "文本对话",
  "p": "输入 $2 · 输出 $12 / 1M tokens",
  "a": "vendor-google-text"
}, {
  "n": "gemini-3-flash-preview",
  "v": "Google",
  "k": "text",
  "t": "文本对话",
  "p": "输入 $0.44 · 输出 $2.64 / 1M tokens",
  "a": "vendor-google-text"
}, {
  "n": "gemini-3-pro-image",
  "v": "Google",
  "k": "image",
  "t": "图像生成与编辑",
  "p": "$0.09 / 次",
  "a": "vendor-google-image"
}, {
  "n": "gemini-3-pro-image-preview",
  "v": "Google",
  "k": "image",
  "t": "图像生成与编辑",
  "p": "$0.09 / 次",
  "a": "vendor-google-image"
}, {
  "n": "gemini-2.5-flash",
  "v": "Google",
  "k": "text",
  "t": "文本对话",
  "p": "输入 $0.3 · 输出 $2.4 / 1M tokens",
  "a": "vendor-google-text"
}, {
  "n": "gemini-2.5-flash-image",
  "v": "Google",
  "k": "image",
  "t": "图像生成与编辑",
  "p": "$0.02 / 次",
  "a": "vendor-google-image"
}, {
  "n": "gemini-2.5-flash-lite",
  "v": "Google",
  "k": "text",
  "t": "文本对话",
  "p": "输入 $0.1 · 输出 $0.4 / 1M tokens",
  "a": "vendor-google-text"
}, {
  "n": "gemini-2.5-flash-nothinking",
  "v": "Google",
  "k": "text",
  "t": "文本对话",
  "p": "输入 $0.3 · 输出 $2.4 / 1M tokens",
  "a": "vendor-google-text"
}, {
  "n": "gemini-2.5-pro",
  "v": "Google",
  "k": "text",
  "t": "文本对话",
  "p": "输入 $1.25 · 输出 $10 / 1M tokens",
  "a": "vendor-google-text"
}, {
  "n": "gemini-nano-banana-2.1",
  "v": "Google",
  "k": "image",
  "t": "图像生成与编辑",
  "p": "$0.045 / 次",
  "a": "vendor-google-image"
}, {
  "n": "grok-4.7",
  "v": "xAI",
  "k": "text",
  "t": "文本对话",
  "p": "输入 $2 · 输出 $6 / 1M tokens",
  "a": "vendor-xai-text"
}, {
  "n": "grok-4.6",
  "v": "xAI",
  "k": "text",
  "t": "文本对话",
  "p": "输入 $2 · 输出 $6 / 1M tokens",
  "a": "vendor-xai-text"
}, {
  "n": "grok-4.5",
  "v": "xAI",
  "k": "text",
  "t": "文本对话",
  "p": "输入 $2 · 输出 $6 / 1M tokens",
  "a": "vendor-xai-text"
}, {
  "n": "grok-4.3",
  "v": "xAI",
  "k": "text",
  "t": "文本对话",
  "p": "输入 $1.25 · 输出 $2.5 / 1M tokens",
  "a": "vendor-xai-text"
}, {
  "n": "grok-4-1-fast-non-reasoning",
  "v": "xAI",
  "k": "text",
  "t": "文本对话",
  "p": "输入 $0.2 · 输出 $0.5 / 1M tokens",
  "a": "vendor-xai-text"
}, {
  "n": "grok-4-1-fast-reasoning",
  "v": "xAI",
  "k": "text",
  "t": "文本对话",
  "p": "输入 $0.2 · 输出 $0.5 / 1M tokens",
  "a": "vendor-xai-text"
}, {
  "n": "grok-4-fast-non-reasoning",
  "v": "xAI",
  "k": "text",
  "t": "文本对话",
  "p": "输入 $0.2 · 输出 $0.5 / 1M tokens",
  "a": "vendor-xai-text"
}, {
  "n": "grok-4-fast-reasoning",
  "v": "xAI",
  "k": "text",
  "t": "文本对话",
  "p": "输入 $0.2 · 输出 $0.5 / 1M tokens",
  "a": "vendor-xai-text"
}, {
  "n": "grok-3",
  "v": "xAI",
  "k": "text",
  "t": "文本对话",
  "p": "输入 $3 · 输出 $15 / 1M tokens",
  "a": "vendor-xai-text"
}, {
  "n": "grok-3-mini",
  "v": "xAI",
  "k": "text",
  "t": "文本对话",
  "p": "输入 $0.3 · 输出 $1.8 / 1M tokens",
  "a": "vendor-xai-text"
}, {
  "n": "grok-imagine-image-2.0",
  "v": "xAI",
  "k": "image",
  "t": "图像生成与编辑",
  "p": "$0.055 / 次",
  "a": "vendor-xai-image"
}, {
  "n": "grok-imagine-image",
  "v": "xAI",
  "k": "image",
  "t": "图像生成与编辑",
  "p": "$0.025 / 次",
  "a": "vendor-xai-image"
}, {
  "n": "grok-imagine-image-quality",
  "v": "xAI",
  "k": "image",
  "t": "图像生成与编辑",
  "p": "$0.045 / 次",
  "a": "vendor-xai-image"
}, {
  "n": "deepseek-v4-flash",
  "v": "DeepSeek",
  "k": "text",
  "t": "文本对话",
  "p": "输入 $0.44 · 输出 $1.32 / 1M tokens",
  "a": "vendor-deepseek"
}, {
  "n": "deepseek-v4-flash-vision-exp",
  "v": "DeepSeek",
  "k": "text",
  "t": "文本对话",
  "p": "输入 $0.44 · 输出 $1.32 / 1M tokens",
  "a": "vendor-deepseek"
}, {
  "n": "deepseek-v4-pro",
  "v": "DeepSeek",
  "k": "text",
  "t": "文本对话",
  "p": "输入 $1.74 · 输出 $3.48 / 1M tokens",
  "a": "vendor-deepseek"
}, {
  "n": "deepseek-v3.2",
  "v": "DeepSeek",
  "k": "text",
  "t": "文本对话",
  "p": "输入 $0.28 · 输出 $0.42 / 1M tokens",
  "a": "vendor-deepseek"
}, {
  "n": "deepseek-v3.2-thinking",
  "v": "DeepSeek",
  "k": "text",
  "t": "文本对话",
  "p": "输入 $0.28 · 输出 $0.42 / 1M tokens",
  "a": "vendor-deepseek"
}, {
  "n": "deepseek-v3.1",
  "v": "DeepSeek",
  "k": "text",
  "t": "文本对话",
  "p": "输入 $0.5 · 输出 $1.5 / 1M tokens",
  "a": "vendor-deepseek"
}, {
  "n": "deepseek-v3",
  "v": "DeepSeek",
  "k": "text",
  "t": "文本对话",
  "p": "输入 $0.286 · 输出 $1.144 / 1M tokens",
  "a": "vendor-deepseek"
}, {
  "n": "deepseek-r1",
  "v": "DeepSeek",
  "k": "text",
  "t": "文本对话",
  "p": "输入 $0.57 · 输出 $2.28 / 1M tokens",
  "a": "vendor-deepseek"
}, {
  "n": "text-embedding-v4",
  "v": "阿里巴巴",
  "k": "embedding",
  "t": "向量嵌入",
  "p": "输入 $0.07 · 输出 $0.07 / 1M tokens",
  "a": "vendor-阿里巴巴-embedding"
}, {
  "n": "qwen3.6-plus",
  "v": "阿里巴巴",
  "k": "text",
  "t": "文本对话",
  "p": "输入 $0.273973 · 输出 $1.6438 / 1M tokens",
  "a": "vendor-阿里巴巴-text"
}, {
  "n": "qwen3.5-122b-a10b",
  "v": "阿里巴巴",
  "k": "text",
  "t": "文本对话",
  "p": "输入 $0.12 · 输出 $0.96 / 1M tokens",
  "a": "vendor-阿里巴巴-text"
}, {
  "n": "qwen3.5-27b",
  "v": "阿里巴巴",
  "k": "text",
  "t": "文本对话",
  "p": "输入 $0.09 · 输出 $0.72 / 1M tokens",
  "a": "vendor-阿里巴巴-text"
}, {
  "n": "qwen3.5-35b-a3b",
  "v": "阿里巴巴",
  "k": "text",
  "t": "文本对话",
  "p": "输入 $0.06 · 输出 $0.48 / 1M tokens",
  "a": "vendor-阿里巴巴-text"
}, {
  "n": "qwen3.5-397b-a17b",
  "v": "阿里巴巴",
  "k": "text",
  "t": "文本对话",
  "p": "输入 $0.18 · 输出 $1.08 / 1M tokens",
  "a": "vendor-阿里巴巴-text"
}, {
  "n": "qwen3.5-flash",
  "v": "阿里巴巴",
  "k": "text",
  "t": "文本对话",
  "p": "输入 $0.027397 · 输出 $0.273973 / 1M tokens",
  "a": "vendor-阿里巴巴-text"
}, {
  "n": "qwen3.5-plus",
  "v": "阿里巴巴",
  "k": "text",
  "t": "文本对话",
  "p": "输入 $0.109589 · 输出 $0.657534 / 1M tokens",
  "a": "vendor-阿里巴巴-text"
}, {
  "n": "qwen3.5-flash-2026-02-23",
  "v": "阿里巴巴",
  "k": "text",
  "t": "文本对话",
  "p": "输入 $0.027397 · 输出 $0.273973 / 1M tokens",
  "a": "vendor-阿里巴巴-text"
}, {
  "n": "qwen3.5-plus-2026-02-15",
  "v": "阿里巴巴",
  "k": "text",
  "t": "文本对话",
  "p": "输入 $0.109589 · 输出 $0.657534 / 1M tokens",
  "a": "vendor-阿里巴巴-text"
}, {
  "n": "qwen3-235b-a22b",
  "v": "阿里巴巴",
  "k": "text",
  "t": "文本对话",
  "p": "输入 $1 · 输出 $10 / 1M tokens",
  "a": "vendor-阿里巴巴-text"
}, {
  "n": "qwen3-coder-480b-a35b-instruct",
  "v": "阿里巴巴",
  "k": "text",
  "t": "文本对话",
  "p": "输入 $3 · 输出 $15 / 1M tokens",
  "a": "vendor-阿里巴巴-text"
}, {
  "n": "qwen3-coder-flash",
  "v": "阿里巴巴",
  "k": "text",
  "t": "文本对话",
  "p": "输入 $0.136986 · 输出 $0.547945 / 1M tokens",
  "a": "vendor-阿里巴巴-text"
}, {
  "n": "qwen3-coder-plus",
  "v": "阿里巴巴",
  "k": "text",
  "t": "文本对话",
  "p": "输入 $0.547945 · 输出 $2.1918 / 1M tokens",
  "a": "vendor-阿里巴巴-text"
}, {
  "n": "qwen3-max",
  "v": "阿里巴巴",
  "k": "text",
  "t": "文本对话",
  "p": "输入 $0.342466 · 输出 $1.3699 / 1M tokens",
  "a": "vendor-阿里巴巴-text"
}, {
  "n": "qwen3-max-preview",
  "v": "阿里巴巴",
  "k": "text",
  "t": "文本对话",
  "p": "输入 $0.821918 · 输出 $3.2877 / 1M tokens",
  "a": "vendor-阿里巴巴-text"
}, {
  "n": "qwen3-next-80b-a3b-instruct",
  "v": "阿里巴巴",
  "k": "text",
  "t": "文本对话",
  "p": "输入 $0.15 · 输出 $1.2 / 1M tokens",
  "a": "vendor-阿里巴巴-text"
}, {
  "n": "qwen3-omni-flash",
  "v": "阿里巴巴",
  "k": "text",
  "t": "文本对话",
  "p": "输入 $2 · 输出 $20 / 1M tokens",
  "a": "vendor-阿里巴巴-text"
}, {
  "n": "qwen3-vl-235b-a22b-instruct",
  "v": "阿里巴巴",
  "k": "text",
  "t": "文本对话",
  "p": "输入 $0.3 · 输出 $3 / 1M tokens",
  "a": "vendor-阿里巴巴-text"
}, {
  "n": "qwen3-vl-235b-a22b-thinking",
  "v": "阿里巴巴",
  "k": "text",
  "t": "文本对话",
  "p": "输入 $0.3 · 输出 $3 / 1M tokens",
  "a": "vendor-阿里巴巴-text"
}, {
  "n": "qwen3-vl-30b-a3b-thinking",
  "v": "阿里巴巴",
  "k": "text",
  "t": "文本对话",
  "p": "输入 $0.12 · 输出 $1.2 / 1M tokens",
  "a": "vendor-阿里巴巴-text"
}, {
  "n": "qwen3-vl-32b-thinking",
  "v": "阿里巴巴",
  "k": "text",
  "t": "文本对话",
  "p": "输入 $0.3 · 输出 $3 / 1M tokens",
  "a": "vendor-阿里巴巴-text"
}, {
  "n": "qwen3-vl-flash",
  "v": "阿里巴巴",
  "k": "text",
  "t": "文本对话",
  "p": "输入 $0.1 · 输出 $0.8 / 1M tokens",
  "a": "vendor-阿里巴巴-text"
}, {
  "n": "qwen3-vl-plus",
  "v": "阿里巴巴",
  "k": "text",
  "t": "文本对话",
  "p": "输入 $0.136986 · 输出 $1.3699 / 1M tokens",
  "a": "vendor-阿里巴巴-text"
}, {
  "n": "qwen3-vl-flash-2025-10-15",
  "v": "阿里巴巴",
  "k": "text",
  "t": "文本对话",
  "p": "输入 $0.1 · 输出 $0.8 / 1M tokens",
  "a": "vendor-阿里巴巴-text"
}, {
  "n": "qwen3-coder-plus-2025-09-23",
  "v": "阿里巴巴",
  "k": "text",
  "t": "文本对话",
  "p": "输入 $0.547945 · 输出 $2.1918 / 1M tokens",
  "a": "vendor-阿里巴巴-text"
}, {
  "n": "qwen3-max-2025-09-23",
  "v": "阿里巴巴",
  "k": "text",
  "t": "文本对话",
  "p": "输入 $0.821918 · 输出 $3.2877 / 1M tokens",
  "a": "vendor-阿里巴巴-text"
}, {
  "n": "qwen3-vl-plus-2025-09-23",
  "v": "阿里巴巴",
  "k": "text",
  "t": "文本对话",
  "p": "输入 $0.136986 · 输出 $1.3699 / 1M tokens",
  "a": "vendor-阿里巴巴-text"
}, {
  "n": "qwen3-omni-flash-2025-09-15",
  "v": "阿里巴巴",
  "k": "text",
  "t": "文本对话",
  "p": "输入 $2 · 输出 $20 / 1M tokens",
  "a": "vendor-阿里巴巴-text"
}, {
  "n": "qwen3-coder-plus-2025-07-22",
  "v": "阿里巴巴",
  "k": "text",
  "t": "文本对话",
  "p": "输入 $0.547945 · 输出 $2.1918 / 1M tokens",
  "a": "vendor-阿里巴巴-text"
}, {
  "n": "qwen3-235b-a22b-instruct-2507",
  "v": "阿里巴巴",
  "k": "text",
  "t": "文本对话",
  "p": "输入 $1 · 输出 $10 / 1M tokens",
  "a": "vendor-阿里巴巴-text"
}, {
  "n": "qwen3-235b-a22b-thinking-2507",
  "v": "阿里巴巴",
  "k": "text",
  "t": "文本对话",
  "p": "输入 $1.6 · 输出 $12.8 / 1M tokens",
  "a": "vendor-阿里巴巴-text"
}, {
  "n": "qwen3-30b-a3b-instruct-2507",
  "v": "阿里巴巴",
  "k": "text",
  "t": "文本对话",
  "p": "输入 $0.2 · 输出 $0.8 / 1M tokens",
  "a": "vendor-阿里巴巴-text"
}, {
  "n": "qwen3-30b-a3b-thinking-2507",
  "v": "阿里巴巴",
  "k": "text",
  "t": "文本对话",
  "p": "输入 $0.2 · 输出 $2.4 / 1M tokens",
  "a": "vendor-阿里巴巴-text"
}, {
  "n": "wan2.7-i2v",
  "v": "阿里巴巴",
  "k": "video",
  "t": "视频生成",
  "p": "见模型文档",
  "a": "vendor-阿里巴巴-video"
}, {
  "n": "wan2.7-r2v",
  "v": "阿里巴巴",
  "k": "video",
  "t": "视频生成",
  "p": "见模型文档",
  "a": "vendor-阿里巴巴-video"
}, {
  "n": "wan2.7-t2v",
  "v": "阿里巴巴",
  "k": "video",
  "t": "视频生成",
  "p": "见模型文档",
  "a": "vendor-阿里巴巴-video"
}, {
  "n": "wan2.7-videoedit",
  "v": "阿里巴巴",
  "k": "video",
  "t": "视频生成",
  "p": "见模型文档",
  "a": "vendor-阿里巴巴-video"
}, {
  "n": "wan2.6-i2v",
  "v": "阿里巴巴",
  "k": "video",
  "t": "视频生成",
  "p": "见模型文档",
  "a": "vendor-阿里巴巴-video"
}, {
  "n": "wan2.6-r2v",
  "v": "阿里巴巴",
  "k": "video",
  "t": "视频生成",
  "p": "见模型文档",
  "a": "vendor-阿里巴巴-video"
}, {
  "n": "wan2.6-r2v-flash",
  "v": "阿里巴巴",
  "k": "video",
  "t": "视频生成",
  "p": "见模型文档",
  "a": "vendor-阿里巴巴-video"
}, {
  "n": "wan2.6-t2v",
  "v": "阿里巴巴",
  "k": "video",
  "t": "视频生成",
  "p": "见模型文档",
  "a": "vendor-阿里巴巴-video"
}, {
  "n": "qwen-plus-latest",
  "v": "阿里巴巴",
  "k": "text",
  "t": "文本对话",
  "p": "输入 $0.109589 · 输出 $0.273973 / 1M tokens",
  "a": "vendor-阿里巴巴-text"
}, {
  "n": "qwen-vl-ocr-latest",
  "v": "阿里巴巴",
  "k": "text",
  "t": "文本对话",
  "p": "输入 $0.044 · 输出 $0.07348 / 1M tokens",
  "a": "vendor-阿里巴巴-text"
}, {
  "n": "qvq-plus",
  "v": "阿里巴巴",
  "k": "text",
  "t": "文本对话",
  "p": "输入 $0.28 · 输出 $0.7 / 1M tokens",
  "a": "vendor-阿里巴巴-text"
}, {
  "n": "qwen-long",
  "v": "阿里巴巴",
  "k": "text",
  "t": "文本对话",
  "p": "输入 $0.07 · 输出 $0.28 / 1M tokens",
  "a": "vendor-阿里巴巴-text"
}, {
  "n": "qwen-max",
  "v": "阿里巴巴",
  "k": "text",
  "t": "文本对话",
  "p": "输入 $1.6 · 输出 $6.4 / 1M tokens",
  "a": "vendor-阿里巴巴-text"
}, {
  "n": "qwen-max-longcontext",
  "v": "阿里巴巴",
  "k": "text",
  "t": "文本对话",
  "p": "输入 $3.2 · 输出 $3.2 / 1M tokens",
  "a": "vendor-阿里巴巴-text"
}, {
  "n": "qwen-mt-plus",
  "v": "阿里巴巴",
  "k": "text",
  "t": "文本对话",
  "p": "输入 $2 · 输出 $8 / 1M tokens",
  "a": "vendor-阿里巴巴-text"
}, {
  "n": "qwen-mt-turbo",
  "v": "阿里巴巴",
  "k": "text",
  "t": "文本对话",
  "p": "输入 $0.2 · 输出 $0.5 / 1M tokens",
  "a": "vendor-阿里巴巴-text"
}, {
  "n": "qwen-plus",
  "v": "阿里巴巴",
  "k": "text",
  "t": "文本对话",
  "p": "输入 $0.109589 · 输出 $0.273973 / 1M tokens",
  "a": "vendor-阿里巴巴-text"
}, {
  "n": "qwen-turbo",
  "v": "阿里巴巴",
  "k": "text",
  "t": "文本对话",
  "p": "输入 $0.2 · 输出 $0.6 / 1M tokens",
  "a": "vendor-阿里巴巴-text"
}, {
  "n": "qwen-vl-max",
  "v": "阿里巴巴",
  "k": "text",
  "t": "文本对话",
  "p": "输入 $0.2 · 输出 $0.8 / 1M tokens",
  "a": "vendor-阿里巴巴-text"
}, {
  "n": "qwen-vl-ocr",
  "v": "阿里巴巴",
  "k": "text",
  "t": "文本对话",
  "p": "输入 $0.72 · 输出 $0.72 / 1M tokens",
  "a": "vendor-阿里巴巴-text"
}, {
  "n": "qwen-vl-plus",
  "v": "阿里巴巴",
  "k": "text",
  "t": "文本对话",
  "p": "输入 $0.2 · 输出 $0.6 / 1M tokens",
  "a": "vendor-阿里巴巴-text"
}, {
  "n": "qwen-vl-ocr-2025-11-20",
  "v": "阿里巴巴",
  "k": "text",
  "t": "文本对话",
  "p": "输入 $0.044 · 输出 $0.07348 / 1M tokens",
  "a": "vendor-阿里巴巴-text"
}, {
  "n": "qwen-plus-2025-09-11",
  "v": "阿里巴巴",
  "k": "text",
  "t": "文本对话",
  "p": "输入 $0.109589 · 输出 $0.273973 / 1M tokens",
  "a": "vendor-阿里巴巴-text"
}, {
  "n": "qwen-plus-2025-07-14",
  "v": "阿里巴巴",
  "k": "text",
  "t": "文本对话",
  "p": "输入 $0.4 · 输出 $4 / 1M tokens",
  "a": "vendor-阿里巴巴-text"
}, {
  "n": "seedream-5-0-flash-260915",
  "v": "字节跳动",
  "k": "image",
  "t": "图像生成与编辑",
  "p": "$0.018 / 次",
  "a": "vendor-字节跳动-image"
}, {
  "n": "seedream-5-0-pro-260628",
  "v": "字节跳动",
  "k": "image",
  "t": "图像生成与编辑",
  "p": "$0.12 / 次",
  "a": "vendor-字节跳动-image"
}, {
  "n": "seedream-5-0-260128",
  "v": "字节跳动",
  "k": "image",
  "t": "图像生成与编辑",
  "p": "$0.035 / 次",
  "a": "vendor-字节跳动-image"
}, {
  "n": "seedream-4-5-251128",
  "v": "字节跳动",
  "k": "image",
  "t": "图像生成与编辑",
  "p": "$0.045 / 次",
  "a": "vendor-字节跳动-image"
}, {
  "n": "seedream-4-0-250828",
  "v": "字节跳动",
  "k": "image",
  "t": "图像生成与编辑",
  "p": "$0.035 / 次",
  "a": "vendor-字节跳动-image"
}, {
  "n": "doubao-seedance-2-5-260628",
  "v": "字节跳动",
  "k": "video",
  "t": "视频生成",
  "p": "见模型文档",
  "a": "vendor-字节跳动-video"
}, {
  "n": "doubao-seedance-2-0-mini-260615",
  "v": "字节跳动",
  "k": "video",
  "t": "视频生成",
  "p": "见模型文档",
  "a": "vendor-字节跳动-video"
}, {
  "n": "seed-2-0-lite-260428",
  "v": "字节跳动",
  "k": "text",
  "t": "文本对话",
  "p": "输入 $0.25 · 输出 $2 / 1M tokens",
  "a": "vendor-字节跳动-text"
}, {
  "n": "seed-2-0-mini-260428",
  "v": "字节跳动",
  "k": "text",
  "t": "文本对话",
  "p": "输入 $0.1 · 输出 $0.4 / 1M tokens",
  "a": "vendor-字节跳动-text"
}, {
  "n": "seed-2-0-code-preview-260328",
  "v": "字节跳动",
  "k": "text",
  "t": "文本对话",
  "p": "输入 $0.5 · 输出 $3 / 1M tokens",
  "a": "vendor-字节跳动-text"
}, {
  "n": "seed-2-0-pro-260328",
  "v": "字节跳动",
  "k": "text",
  "t": "文本对话",
  "p": "输入 $0.5 · 输出 $3 / 1M tokens",
  "a": "vendor-字节跳动-text"
}, {
  "n": "doubao-seedance-2-0-260128",
  "v": "字节跳动",
  "k": "video",
  "t": "视频生成",
  "p": "见模型文档",
  "a": "vendor-字节跳动-video"
}, {
  "n": "doubao-seedance-2-0-fast-260128",
  "v": "字节跳动",
  "k": "video",
  "t": "视频生成",
  "p": "见模型文档",
  "a": "vendor-字节跳动-video"
}, {
  "n": "glm-5.2",
  "v": "智谱",
  "k": "text",
  "t": "文本对话",
  "p": "输入 $1.142 · 输出 $3.997 / 1M tokens",
  "a": "vendor-智谱"
}, {
  "n": "glm-5.1",
  "v": "智谱",
  "k": "text",
  "t": "文本对话",
  "p": "输入 $0.84 · 输出 $3.36 / 1M tokens",
  "a": "vendor-智谱"
}, {
  "n": "glm-5",
  "v": "智谱",
  "k": "text",
  "t": "文本对话",
  "p": "输入 $0.56 · 输出 $2.52 / 1M tokens",
  "a": "vendor-智谱"
}, {
  "n": "glm-4.7",
  "v": "智谱",
  "k": "text",
  "t": "文本对话",
  "p": "输入 $0.6 · 输出 $2.16 / 1M tokens",
  "a": "vendor-智谱"
}, {
  "n": "glm-4.6",
  "v": "智谱",
  "k": "text",
  "t": "文本对话",
  "p": "输入 $0.5 · 输出 $2 / 1M tokens",
  "a": "vendor-智谱"
}, {
  "n": "kimi-k2.5",
  "v": "Moonshot",
  "k": "text",
  "t": "文本对话",
  "p": "输入 $0.6 · 输出 $3.15 / 1M tokens",
  "a": "vendor-moonshot"
}, {
  "n": "MiniMax-M2.5",
  "v": "MiniMax",
  "k": "text",
  "t": "文本对话",
  "p": "输入 $0.3 · 输出 $1.2 / 1M tokens",
  "a": "vendor-minimax"
}, {
  "n": "MiniMax-M2.1",
  "v": "MiniMax",
  "k": "text",
  "t": "文本对话",
  "p": "输入 $0.3 · 输出 $1.2 / 1M tokens",
  "a": "vendor-minimax"
}, {
  "n": "flux-2-flex",
  "v": "Black Forest Labs",
  "k": "image",
  "t": "图像生成与编辑",
  "p": "$0.06 / 次",
  "a": "vendor-black-forest-labs"
}, {
  "n": "flux-2-max",
  "v": "Black Forest Labs",
  "k": "image",
  "t": "图像生成与编辑",
  "p": "$0.07 / 次",
  "a": "vendor-black-forest-labs"
}, {
  "n": "flux-2-pro",
  "v": "Black Forest Labs",
  "k": "image",
  "t": "图像生成与编辑",
  "p": "$0.03 / 次",
  "a": "vendor-black-forest-labs"
}, {
  "n": "flux-kontext-max",
  "v": "Black Forest Labs",
  "k": "image",
  "t": "图像生成与编辑",
  "p": "$0.07 / 次",
  "a": "vendor-black-forest-labs"
}, {
  "n": "flux-kontext-pro",
  "v": "Black Forest Labs",
  "k": "image",
  "t": "图像生成与编辑",
  "p": "$0.035 / 次",
  "a": "vendor-black-forest-labs"
}, {
  "n": "step-3.5-flash",
  "v": "阶跃星辰",
  "k": "text",
  "t": "文本对话",
  "p": "输入 $0.1 · 输出 $0.3 / 1M tokens",
  "a": "vendor-阶跃星辰"
}];

export const MODEL_TYPES = [["", "全部"], ["text", "文本对话"], ["image", "图像生成与编辑"], ["video", "视频生成"], ["embedding", "向量嵌入"], ["audio", "语音与音频"], ["moderation", "内容审核"]];

export const ModelSearch = () => {
  const [q, setQ] = useState('');
  const [type, setType] = useState('');
  const normalized = q.trim().toLowerCase();
  const active = normalized || type;
  const matches = active ? MODELS.filter(model => (!type || model.k === type) && (!normalized || [model.n, model.v, model.t].join(' ').toLowerCase().includes(normalized))) : [];
  const results = matches.slice(0, 40);
  return <div className="lp-search">
      <label className="lp-search-label" htmlFor="lp-model-search">搜索模型</label>
      <input id="lp-model-search" className="lp-search-input" value={q} onChange={event => setQ(event.target.value)} placeholder="输入模型 ID 或厂商，如 gpt-6 / gemini / seedream" autoComplete="off" />
      <div className="lp-type-filter">
        {MODEL_TYPES.map(([key, label]) => <button type="button" key={key || 'all'} className={'lp-type-chip' + (type === key ? ' lp-type-chip-active' : '')} aria-pressed={type === key} onClick={() => setType(key)}>{label}</button>)}
      </div>
      {active ? <div className="lp-search-results">
          {results.length ? <p className="lp-search-hint">{('共 {total} 个匹配，显示前 {shown} 个；点击结果跳到对应价格表。').replace('{total}', matches.length).replace('{shown}', results.length)}</p> : null}
          {results.length ? results.map(model => <a className="lp-search-result" href={'#' + model.a} key={model.n}>
              <span className="lp-result-main">
                <span className="lp-result-name">{model.n}</span>
                <span>{model.v} · {model.t}</span>
              </span>
              <span className="lp-result-price">{model.p}</span>
            </a>) : <p className="lp-no-results">没有找到匹配的在线模型。</p>}
        </div> : null}
    </div>;
};

<div className="lp-layout">
  <div className="lp-rail">
    <div className="lp-rail-inner">
      <span className="lp-rail-title">本页目录</span>
      <a className="lp-rail-link" href="#use-cases">按用途选模型</a><a className="lp-rail-link" href="#recently-added">最近上线</a><a className="lp-rail-link" href="#model-catalog">按厂商查价格</a><a className="lp-rail-link" href="#tiered-pricing">阶梯计价</a><a className="lp-rail-link" href="#pricing-basis">价格说明</a><a className="lp-rail-link" href="#commercial-terms">企业采购</a><a className="lp-rail-link" href="#faq">常见问题</a>
      <span className="lp-rail-subtitle">厂商</span>
      <div className="lp-rail-vendors"><a className="lp-rail-link lp-vendor-link" href="#vendor-openai">OpenAI</a><a className="lp-rail-link lp-vendor-link" href="#vendor-google">Google</a><a className="lp-rail-link lp-vendor-link" href="#vendor-xai">xAI</a><a className="lp-rail-link lp-vendor-link" href="#vendor-deepseek">DeepSeek</a><a className="lp-rail-link lp-vendor-link" href="#vendor-阿里巴巴">阿里巴巴</a><a className="lp-rail-link lp-vendor-link" href="#vendor-字节跳动">字节跳动</a><a className="lp-rail-link lp-vendor-link" href="#vendor-智谱">智谱</a><a className="lp-rail-link lp-vendor-link" href="#vendor-moonshot">Moonshot</a><a className="lp-rail-link lp-vendor-link" href="#vendor-minimax">MiniMax</a><a className="lp-rail-link lp-vendor-link" href="#vendor-black-forest-labs">Black Forest Labs</a><a className="lp-rail-link lp-vendor-link" href="#vendor-阶跃星辰">阶跃星辰</a></div>
    </div>
  </div>

  <div className="lp-content">
    <h1 className="lp-title">模型与价格总表</h1>

    <p className="lp-lead">老张API当前在线 222 个模型，可按用途或厂商查找模型 ID、单价、令牌分组和调用接口。数据更新于 2026/10/07 17:29（UTC+8），实际扣费以调用日志为准。</p>

    <ModelSearch />

    | 项目 | 内容 |
    | - | - |
    | 在线模型 | 222 个，来自 11 个厂商；按量计费 195 个，按次计费 27 个 |
    | 价格单位 | 美元；按量模型为每 1M tokens，按次模型为每次调用，视频模型见对应文档 |
    | 令牌分组 | 决定线路与价格；分组后的「×倍率」表示按列出价格乘以该倍率 |
    | 数据来源 | [老张API公开价格配置](https://api.laozhang.ai/api/pricing)，本页按其生成 |

    <div className="lp-actions">
      <a href="https://api.laozhang.ai/account/pricing">控制台实时价格</a>
      <a href="https://api.laozhang.ai/log">调用日志</a>
      <a href="/pricing">计费模式与分组</a>
      <a href="/faq/model-availability">模型可用性与权限</a>
    </div>

    <h2 id="use-cases">按用途选模型</h2>

    <p>先按用途确定模型范围，再到接入文档查看请求格式。模型数为当前在线数量。</p>

    | 用途 | 模型数 | 调用接口 | 接入文档 |
    | - | -: | - | - |
    | 文本对话 | 161 | OpenAI 兼容、Gemini 原生、Anthropic Messages、Responses | [文本生成](/api-capabilities/text-generation) |
    | 图像生成与编辑 | 35 | OpenAI 兼容、Images、Gemini 原生 | [图像生成与编辑](/api-capabilities/image-generation-guide) |
    | 视频生成 | 12 | OpenAI 兼容 | [Wan](/api-capabilities/wan-video-generation)、[Seedance 2](/api-capabilities/seedance2-video-generation) |
    | 向量嵌入 | 4 | Embeddings、OpenAI 兼容 | [Embeddings](/api-capabilities/text-embedding) |
    | 语音与音频 | 8 | OpenAI 兼容 | [音频转录与语音生成](/api-capabilities/audio-transcription) |
    | 内容审核 | 2 | OpenAI 兼容 | [Moderation](/api-capabilities/moderation) |

    <h2 id="recently-added">最近上线</h2>

    近 60 天首次出现在老张API公开价格配置中的模型，按日期从新到旧排列。上线说明见[公告](/changelog)。

    | 日期 | 模型 ID | 厂商 | 用途 | 价格 |
    | - | - | - | - | - |
    | 2026-10-07 | [`gemini-nano-banana-2.1`](#vendor-google-image) | Google | 图像生成与编辑 | \$0.045 / 次 |
    | 2026-10-05 | [`gpt-6.1-sol`](#vendor-openai-text) | OpenAI | 文本对话 | 输入 \$2 · 输出 \$10 / 1M tokens |
    | 2026-10-05 | [`deepseek-v3`](#vendor-deepseek) | DeepSeek | 文本对话 | 输入 \$0.286 · 输出 \$1.144 / 1M tokens |
    | 2026-10-05 | [`deepseek-v3.1`](#vendor-deepseek) | DeepSeek | 文本对话 | 输入 \$0.5 · 输出 \$1.5 / 1M tokens |
    | 2026-09-25 | [`seedream-5-0-flash-260915`](#vendor-字节跳动-image) | 字节跳动 | 图像生成与编辑 | \$0.018 / 次 |
    | 2026-09-25 | [`seedream-5-0-pro-260628`](#vendor-字节跳动-image) | 字节跳动 | 图像生成与编辑 | \$0.12 / 次 |
    | 2026-09-24 | [`gpt-6-luna`](#vendor-openai-text) | OpenAI | 文本对话 | 输入 \$0.1 · 输出 \$0.5 / 1M tokens |
    | 2026-09-24 | [`gpt-6-sol`](#vendor-openai-text) | OpenAI | 文本对话 | 输入 \$2 · 输出 \$10 / 1M tokens |
    | 2026-09-24 | [`grok-4.7`](#vendor-xai-text) | xAI | 文本对话 | 输入 \$2 · 输出 \$6 / 1M tokens |
    | 2026-09-24 | [`doubao-seedance-2-5-260628`](#vendor-字节跳动-video) | 字节跳动 | 视频生成 | 见模型文档 |
    | 2026-09-10 | [`gpt-6-astra`](#vendor-openai-text) | OpenAI | 文本对话 | 输入 \$10 · 输出 \$50 / 1M tokens |
    | 2026-09-10 | [`gpt-image-2.5-web`](#vendor-openai-image) | OpenAI | 图像生成与编辑 | \$0.03 / 次 |
    | 2026-09-09 | [`gpt-image-2.5-flare`](#vendor-openai-image) | OpenAI | 图像生成与编辑 | 输入 \$5 · 输出 \$30 / 1M tokens |
    | 2026-09-09 | [`gpt-image-2.5-flare-2026-09-08`](#vendor-openai-image) | OpenAI | 图像生成与编辑 | 输入 \$5 · 输出 \$30 / 1M tokens |
    | 2026-09-09 | [`gpt-image-2.5-flare-vip`](#vendor-openai-image) | OpenAI | 图像生成与编辑 | \$0.03 / 次 |
    | 2026-09-09 | [`gpt-image-2.5-sunburst`](#vendor-openai-image) | OpenAI | 图像生成与编辑 | 输入 \$5 · 输出 \$30 / 1M tokens |
    | 2026-09-09 | [`gpt-image-2.5-sunburst-2026-09-08`](#vendor-openai-image) | OpenAI | 图像生成与编辑 | 输入 \$5 · 输出 \$30 / 1M tokens |
    | 2026-09-09 | [`gpt-image-2.5-sunburst-vip`](#vendor-openai-image) | OpenAI | 图像生成与编辑 | \$0.03 / 次 |
    | 2026-09-03 | [`gemini-3.8-flash`](#vendor-google-text) | Google | 文本对话 | 输入 \$0.75 · 输出 \$3.75 / 1M tokens |
    | 2026-09-03 | [`grok-imagine-image-2.0`](#vendor-xai-image) | xAI | 图像生成与编辑 | \$0.055 / 次 |
    | 2026-08-26 | [`deepseek-v4-flash-vision-exp`](#vendor-deepseek) | DeepSeek | 文本对话 | 输入 \$0.44 · 输出 \$1.32 / 1M tokens |
    | 2026-08-21 | [`grok-4.6`](#vendor-xai-text) | xAI | 文本对话 | 输入 \$2 · 输出 \$6 / 1M tokens |
    | 2026-08-14 | [`gemini-3.7-flash`](#vendor-google-text) | Google | 文本对话 | 输入 \$0.75 · 输出 \$3.75 / 1M tokens |
    | 2026-08-13 | [`grok-imagine-image`](#vendor-xai-image) | xAI | 图像生成与编辑 | \$0.025 / 次 |
    | 2026-08-13 | [`grok-imagine-image-quality`](#vendor-xai-image) | xAI | 图像生成与编辑 | \$0.045 / 次 |

    <h2 id="model-catalog">按厂商查价格</h2>

    <p>每个厂商下按用途分表，表内按版本从新到旧排列。宽表格在手机上可左右滑动。</p>

    <div className="lp-mobile-jump"><a href="#vendor-openai">OpenAI</a><a href="#vendor-google">Google</a><a href="#vendor-xai">xAI</a><a href="#vendor-deepseek">DeepSeek</a><a href="#vendor-阿里巴巴">阿里巴巴</a><a href="#vendor-字节跳动">字节跳动</a><a href="#vendor-智谱">智谱</a><a href="#vendor-moonshot">Moonshot</a><a href="#vendor-minimax">MiniMax</a><a href="#vendor-black-forest-labs">Black Forest Labs</a><a href="#vendor-阶跃星辰">阶跃星辰</a></div>

    <h2 id="vendor-openai">OpenAI <span className="lp-count">96</span></h2>

    <h3 id="vendor-openai-text">文本对话 <span className="lp-count">68</span></h3>

    <p className="lp-table-note">以下模型的令牌分组：<code>default</code>。</p>

    | 模型 ID | 输入（/1M tokens） | 输出（/1M tokens） | 缓存读（/1M tokens） | 调用接口 |
    | - | -: | -: | -: | - |
    | `gpt-6.1-sol` † | \$2 | \$10 | — | OpenAI 兼容 |
    | `gpt-6-astra` † | \$10 | \$50 | \$1 | OpenAI 兼容 |
    | `gpt-6-luna` † | \$0.1 | \$0.5 | \$0.01 | OpenAI 兼容 |
    | `gpt-6-sol` † | \$2 | \$10 | \$0.2 | OpenAI 兼容 |
    | `gpt-5.6-luna` † | \$0.2 | \$1.2 | \$0.02 | OpenAI 兼容 |
    | `gpt-5.6-sol` † | \$4 | \$20 | \$0.4 | OpenAI 兼容 |
    | `gpt-5.6-terra` † | \$2 | \$12 | \$0.2 | OpenAI 兼容 |
    | `gpt-5.5` † | \$5 | \$30 | \$0.5 | OpenAI 兼容 |
    | `gpt-5.5-pro` † | \$30 | \$180 | — | OpenAI 兼容 |
    | `gpt-5.4` † | \$2.5 | \$15 | \$0.25 | OpenAI 兼容 |
    | `gpt-5.4-mini` | \$0.75 | \$4.5 | \$0.075 | OpenAI 兼容 |
    | `gpt-5.4-nano` | \$0.2 | \$1.25 | \$0.02 | OpenAI 兼容 |
    | `gpt-5.4-pro` † | \$30 | \$180 | — | OpenAI 兼容 |
    | `gpt-5.2` | \$1.75 | \$14 | \$0.175 | OpenAI 兼容 |
    | `gpt-5.2-2025-12-11` | \$1.75 | \$14 | \$0.175 | OpenAI 兼容 |
    | `gpt-5.1` | \$1.25 | \$10 | \$0.125 | OpenAI 兼容 |
    | `gpt-5.1-2025-11-13` | \$1.25 | \$10 | \$0.125 | OpenAI 兼容 |
    | `gpt-5` | \$1.25 | \$10 | \$0.125 | OpenAI 兼容 |
    | `gpt-5-chat` | \$1.25 | \$10 | \$0.125 | OpenAI 兼容 |
    | `gpt-5-mini` | \$0.25 | \$2 | \$0.025 | OpenAI 兼容 |
    | `gpt-5-nano` | \$0.05 | \$0.4 | \$0.005 | OpenAI 兼容 |
    | `gpt-5-pro` | \$15 | \$120 | — | OpenAI 兼容 |
    | `gpt-5-pro-2025-10-06` | \$15 | \$120 | — | OpenAI 兼容 |
    | `gpt-5-2025-08-07` | \$1.25 | \$10 | \$0.125 | OpenAI 兼容 |
    | `gpt-5-mini-2025-08-07` | \$0.25 | \$2 | \$0.025 | OpenAI 兼容 |
    | `gpt-5-nano-2025-08-07` | \$0.05 | \$0.4 | \$0.005 | OpenAI 兼容 |
    | `gpt-4.1` | \$2 | \$8 | \$0.5 | OpenAI 兼容 |
    | `gpt-4.1-mini` | \$0.4 | \$1.6 | \$0.1 | OpenAI 兼容 |
    | `gpt-4.1-nano` | \$0.1 | \$0.4 | \$0.025 | OpenAI 兼容 |
    | `gpt-4.1-2025-04-14` | \$2 | \$8 | \$0.5 | OpenAI 兼容 |
    | `gpt-4.1-mini-2025-04-14` | \$0.4 | \$1.6 | \$0.1 | OpenAI 兼容 |
    | `gpt-4.1-nano-2025-04-14` | \$0.1 | \$0.4 | \$0.025 | OpenAI 兼容 |
    | `gpt-4o` | \$2.5 | \$10 | \$1.25 | OpenAI 兼容 |
    | `gpt-4o-mini` | \$0.15 | \$0.6 | \$0.075 | OpenAI 兼容 |
    | `o4-mini` | \$1.1 | \$4.4 | \$0.275 | OpenAI 兼容 |
    | `o4-mini-2025-04-16` | \$1.1 | \$4.4 | \$0.275 | OpenAI 兼容 |
    | `gpt-4o-2024-11-20` | \$2.5 | \$10 | \$1.25 | OpenAI 兼容 |
    | `gpt-4o-2024-08-06` | \$2.5 | \$10 | \$1.25 | OpenAI 兼容 |
    | `gpt-4o-mini-2024-07-18` | \$0.15 | \$0.6 | \$0.075 | OpenAI 兼容 |
    | `gpt-4o-2024-05-13` | \$5 | \$15 | — | OpenAI 兼容 |
    | `gpt-3.5-turbo` | \$0.5 | \$1.5 | — | OpenAI 兼容 |
    | `gpt-3.5-turbo-0125` | \$0.5 | \$1.5 | — | OpenAI 兼容 |
    | `gpt-3.5-turbo-0613` | \$1.5 | \$1.95 | — | OpenAI 兼容 |
    | `gpt-3.5-turbo-1106` | \$1 | \$2 | — | OpenAI 兼容 |
    | `gpt-3.5-turbo-16k` | \$3 | \$3.9 | — | OpenAI 兼容 |
    | `gpt-3.5-turbo-16k-0613` | \$3 | \$3.9 | — | OpenAI 兼容 |
    | `gpt-3.5-turbo-instruct` | \$1.5 | \$1.95 | — | OpenAI 兼容 |
    | `o3` | \$3 | \$12 | \$0.75 | OpenAI 兼容 |
    | `o3-mini` | \$1.1 | \$4.4 | \$0.55 | OpenAI 兼容 |
    | `o3-mini-low` | \$1.1 | \$4.4 | \$0.55 | OpenAI 兼容 |
    | `o3-mini-medium` | \$1.1 | \$4.4 | \$0.55 | OpenAI 兼容 |
    | `o3-pro` | \$20 | \$80 | — | Responses |
    | `o3-pro-2025-06-10` | \$20 | \$80 | — | Responses |
    | `o3-2025-04-16` | \$3 | \$12 | \$0.75 | OpenAI 兼容 |
    | `o3-mini-2025-01-31` | \$1.1 | \$4.4 | \$0.55 | OpenAI 兼容 |
    | `o3-mini-2025-01-31-high` | \$1.1 | \$4.4 | \$0.55 | OpenAI 兼容 |
    | `o3-mini-2025-01-31-low` | \$1.1 | \$4.4 | \$0.55 | OpenAI 兼容 |
    | `o3-mini-2025-01-31-medium` | \$1.1 | \$4.4 | \$0.55 | OpenAI 兼容 |
    | `o1` | \$15 | \$60 | \$7.5 | OpenAI 兼容 |
    | `o1-mini` | \$1.1 | \$4.4 | \$0.55 | OpenAI 兼容 |
    | `o1-preview` | \$15 | \$60 | \$7.5 | OpenAI 兼容 |
    | `o1-pro` | \$180 | \$720 | — | OpenAI 兼容 |
    | `o1-pro-2025-03-19` | \$180 | \$720 | — | OpenAI 兼容 |
    | `o1-2024-12-17` | \$15 | \$60 | \$7.5 | OpenAI 兼容 |
    | `o1-mini-2024-09-12` | \$1.1 | \$4.4 | \$0.55 | OpenAI 兼容 |
    | `o1-preview-2024-09-12` | \$15 | \$60 | \$7.5 | OpenAI 兼容 |
    | `gpt-oss-120b` | \$0.5 | \$2 | — | OpenAI 兼容 |
    | `gpt-oss-20b` | \$0.1 | \$0.4 | — | OpenAI 兼容 |

    <h3 id="vendor-openai-image">图像生成与编辑 <span className="lp-count">15</span></h3>

    | 模型 ID | 计费 | 输入（/1M tokens） | 输出（/1M tokens） | 缓存读（/1M tokens） | 按次价格 | 令牌分组 | 调用接口 |
    | - | - | -: | -: | -: | -: | - | - |
    | `gpt-image-2.5-flare` | 按量 | \$5 | \$30 | \$1.25 | — | GPTImage2 Sora2 Enterprise（×1.2）, Sora2Official | Images, OpenAI 兼容 |
    | `gpt-image-2.5-flare-vip` | 按次 | — | — | — | \$0.03 / 次 | default, Other image group (see console for name) | Images, OpenAI 兼容 |
    | `gpt-image-2.5-sunburst` | 按量 | \$5 | \$30 | \$1.25 | — | GPTImage2 Sora2 Enterprise（×1.2）, Sora2Official | Images, OpenAI 兼容 |
    | `gpt-image-2.5-sunburst-vip` | 按次 | — | — | — | \$0.03 / 次 | default, Other image group (see console for name) | Images, OpenAI 兼容 |
    | `gpt-image-2.5-web` | 按次 | — | — | — | \$0.03 / 次 | default, Other image group (see console for name) | Images, OpenAI 兼容 |
    | `gpt-image-2.5-flare-2026-09-08` | 按量 | \$5 | \$30 | \$1.25 | — | GPTImage2 Sora2 Enterprise（×1.2）, Sora2Official | Images, OpenAI 兼容 |
    | `gpt-image-2.5-sunburst-2026-09-08` | 按量 | \$5 | \$30 | \$1.25 | — | GPTImage2 Sora2 Enterprise（×1.2）, Sora2Official | Images, OpenAI 兼容 |
    | `gpt-image-2` | 按次 | — | — | — | \$0.03 / 次 | GPTImage2 Sora2 Enterprise（×1.2）, default, Other image group (see console for name), Sora2Official | Images, OpenAI 兼容 |
    | `gpt-image-2-all` | 按次 | — | — | — | \$0.03 / 次 | default, Other image group (see console for name) | Images, OpenAI 兼容 |
    | `gpt-image-2-vip` | 按次 | — | — | — | \$0.03 / 次 | default, Other image group (see console for name) | Images, OpenAI 兼容 |
    | `gpt-image-2-web` | 按次 | — | — | — | \$0.03 / 次 | default, Other image group (see console for name) | Images, OpenAI 兼容 |
    | `gpt-image-1.5` | 按量 | \$5 | \$32 | \$1.25 | — | GPTImage2 Sora2 Enterprise（×1.2）, default, Sora2Official | Images, OpenAI 兼容 |
    | `gpt-image-1.5-2025-12-16` | 按量 | \$5 | \$32 | \$1.25 | — | default | Images, OpenAI 兼容 |
    | `gpt-image-1` | 按量 | \$5 | \$40 | \$1.25 | — | GPTImage2 Sora2 Enterprise（×1.2）, default, Sora2Official | Images, OpenAI 兼容 |
    | `gpt-image-1-mini` | 按量 | \$2 | \$8 | \$0.2 | — | GPTImage2 Sora2 Enterprise（×1.2）, default, Sora2Official | Images, OpenAI 兼容 |

    <h3 id="vendor-openai-embedding">向量嵌入 <span className="lp-count">3</span></h3>

    <p className="lp-table-note">以下模型的令牌分组：<code>default</code>。</p>

    | 模型 ID | 输入（/1M tokens） | 输出（/1M tokens） | 调用接口 |
    | - | -: | -: | - |
    | `text-embedding-3-large` | \$0.13 | \$0.13 | Embeddings, OpenAI 兼容 |
    | `text-embedding-3-small` | \$0.02 | \$0.02 | Embeddings, OpenAI 兼容 |
    | `text-embedding-ada-002` | \$0.1 | \$0.1 | Embeddings, OpenAI 兼容 |

    <h3 id="vendor-openai-audio">语音与音频 <span className="lp-count">8</span></h3>

    <p className="lp-table-note">以下模型的令牌分组：<code>default</code>。</p>

    | 模型 ID | 输入（/1M tokens） | 输出（/1M tokens） | 调用接口 |
    | - | -: | -: | - |
    | `gpt-4o-audio-preview` | \$2.5 | \$10 | OpenAI 兼容 |
    | `gpt-4o-mini-audio-preview` | \$2 | \$8 | OpenAI 兼容 |
    | `gpt-4o-mini-transcribe` | \$1.5 | \$6 | OpenAI 兼容 |
    | `gpt-4o-mini-tts` | \$1.2 | \$18 | OpenAI 兼容 |
    | `gpt-4o-transcribe` | \$8 | \$16 | OpenAI 兼容 |
    | `tts-1` | \$30 | \$30 | OpenAI 兼容 |
    | `tts-1-hd` | \$60 | \$60 | OpenAI 兼容 |
    | `whisper-1` | \$60 | \$0 | OpenAI 兼容 |

    <h3 id="vendor-openai-moderation">内容审核 <span className="lp-count">2</span></h3>

    <p className="lp-table-note">以下模型的令牌分组：<code>default</code>。</p>

    | 模型 ID | 输入（/1M tokens） | 输出（/1M tokens） | 调用接口 |
    | - | -: | -: | - |
    | `omni-moderation-latest` | \$0.2 | \$0.2 | OpenAI 兼容 |
    | `omni-moderation-2024-09-26` | \$0.2 | \$0.2 | OpenAI 兼容 |

    <h2 id="vendor-google">Google <span className="lp-count">20</span></h2>

    <h3 id="vendor-google-text">文本对话 <span className="lp-count">13</span></h3>

    <p className="lp-table-note">以下模型的令牌分组：<code>default</code>。</p>

    | 模型 ID | 输入（/1M tokens） | 输出（/1M tokens） | 缓存读（/1M tokens） | 调用接口 |
    | - | -: | -: | -: | - |
    | `gemini-3.8-flash` | \$0.75 | \$3.75 | \$0.075 | Gemini 原生, OpenAI 兼容 |
    | `gemini-3.7-flash` | \$0.75 | \$3.75 | — | Gemini 原生, OpenAI 兼容 |
    | `gemini-3.6-flash` | \$1.5 | \$7.5 | — | Gemini 原生, OpenAI 兼容 |
    | `gemini-3.5-flash` | \$1.5 | \$9 | \$0.15 | Gemini 原生, OpenAI 兼容 |
    | `gemini-3.5-flash-lite` | \$0.3 | \$2.502 | \$0.03 | Gemini 原生, OpenAI 兼容 |
    | `gemini-3.1-flash-lite` | \$0.25 | \$1.5 | \$0.025 | Gemini 原生, OpenAI 兼容 |
    | `gemini-3.1-flash-lite-preview` | \$0.25 | \$1.5 | \$0.025 | Gemini 原生, OpenAI 兼容 |
    | `gemini-3.1-pro-preview` † | \$2 | \$12 | \$0.2 | Gemini 原生, OpenAI 兼容 |
    | `gemini-3-flash-preview` | \$0.44 | \$2.64 | \$0.044 | Gemini 原生, OpenAI 兼容 |
    | `gemini-2.5-flash` | \$0.3 | \$2.4 | \$0.03 | Gemini 原生, OpenAI 兼容 |
    | `gemini-2.5-flash-lite` | \$0.1 | \$0.4 | \$0.01 | Gemini 原生, OpenAI 兼容 |
    | `gemini-2.5-flash-nothinking` | \$0.3 | \$2.4 | \$0.03 | Gemini 原生, OpenAI 兼容 |
    | `gemini-2.5-pro` † | \$1.25 | \$10 | \$0.125 | Gemini 原生, OpenAI 兼容 |

    <h3 id="vendor-google-image">图像生成与编辑 <span className="lp-count">7</span></h3>

    <p className="lp-table-note">以下模型的令牌分组：<code>default</code>。</p>

    | 模型 ID | 按次价格 | 调用接口 |
    | - | -: | - |
    | `gemini-3.1-flash-image` | \$0.055 / 次 | Gemini 原生, OpenAI 兼容 |
    | `gemini-3.1-flash-image-preview` | \$0.055 / 次 | Gemini 原生, OpenAI 兼容 |
    | `gemini-3.1-flash-lite-image` | \$0.025 / 次 | Gemini 原生, OpenAI 兼容 |
    | `gemini-3-pro-image` | \$0.09 / 次 | Gemini 原生, OpenAI 兼容 |
    | `gemini-3-pro-image-preview` | \$0.09 / 次 | Gemini 原生, OpenAI 兼容 |
    | `gemini-2.5-flash-image` | \$0.02 / 次 | Gemini 原生, OpenAI 兼容 |
    | `gemini-nano-banana-2.1` | \$0.045 / 次 | Gemini 原生, OpenAI 兼容 |

    <h2 id="vendor-xai">xAI <span className="lp-count">13</span></h2>

    <h3 id="vendor-xai-text">文本对话 <span className="lp-count">10</span></h3>

    <p className="lp-table-note">以下模型的令牌分组：<code>default</code>。</p>

    | 模型 ID | 输入（/1M tokens） | 输出（/1M tokens） | 缓存读（/1M tokens） | 调用接口 |
    | - | -: | -: | -: | - |
    | `grok-4.7` † | \$2 | \$6 | — | OpenAI 兼容 |
    | `grok-4.6` † | \$2 | \$6 | — | OpenAI 兼容 |
    | `grok-4.5` | \$2 | \$6 | \$0.5 | OpenAI 兼容 |
    | `grok-4.3` | \$1.25 | \$2.5 | \$0.2 | OpenAI 兼容 |
    | `grok-4-1-fast-non-reasoning` | \$0.2 | \$0.5 | — | OpenAI 兼容 |
    | `grok-4-1-fast-reasoning` | \$0.2 | \$0.5 | — | OpenAI 兼容 |
    | `grok-4-fast-non-reasoning` | \$0.2 | \$0.5 | — | OpenAI 兼容 |
    | `grok-4-fast-reasoning` | \$0.2 | \$0.5 | — | OpenAI 兼容 |
    | `grok-3` | \$3 | \$15 | — | OpenAI 兼容 |
    | `grok-3-mini` | \$0.3 | \$1.8 | — | OpenAI 兼容 |

    <h3 id="vendor-xai-image">图像生成与编辑 <span className="lp-count">3</span></h3>

    <p className="lp-table-note">以下模型的令牌分组：<code>default</code>。</p>

    | 模型 ID | 按次价格 | 调用接口 |
    | - | -: | - |
    | `grok-imagine-image-2.0` | \$0.055 / 次 | OpenAI 兼容 |
    | `grok-imagine-image` | \$0.025 / 次 | OpenAI 兼容 |
    | `grok-imagine-image-quality` | \$0.045 / 次 | OpenAI 兼容 |

    <h2 id="vendor-deepseek">DeepSeek <span className="lp-count">8</span></h2>

    <p className="lp-vendor-type">文本对话</p>

    <p className="lp-table-note">以下模型的令牌分组：<code>default</code>。</p>

    | 模型 ID | 输入（/1M tokens） | 输出（/1M tokens） | 缓存读（/1M tokens） | 调用接口 |
    | - | -: | -: | -: | - |
    | `deepseek-v4-flash` | \$0.44 | \$1.32 | \$0.088 | Anthropic Messages, OpenAI 兼容 |
    | `deepseek-v4-flash-vision-exp` | \$0.44 | \$1.32 | \$0.014667 | Anthropic Messages, OpenAI 兼容 |
    | `deepseek-v4-pro` | \$1.74 | \$3.48 | \$0.145 | Anthropic Messages, OpenAI 兼容 |
    | `deepseek-v3.2` | \$0.28 | \$0.42 | — | OpenAI 兼容 |
    | `deepseek-v3.2-thinking` | \$0.28 | \$0.42 | — | OpenAI 兼容 |
    | `deepseek-v3.1` | \$0.5 | \$1.5 | — | OpenAI 兼容 |
    | `deepseek-v3` | \$0.286 | \$1.144 | \$0.0715 | OpenAI 兼容 |
    | `deepseek-r1` | \$0.57 | \$2.28 | \$0.1425 | OpenAI 兼容 |

    <h2 id="vendor-阿里巴巴">阿里巴巴 <span className="lp-count">58</span></h2>

    <h3 id="vendor-阿里巴巴-text">文本对话 <span className="lp-count">49</span></h3>

    <p className="lp-table-note">以下模型的令牌分组：<code>default</code>。</p>

    | 模型 ID | 输入（/1M tokens） | 输出（/1M tokens） | 调用接口 |
    | - | -: | -: | - |
    | `qwen3.6-plus` † | \$0.273973 | \$1.6438 | OpenAI 兼容 |
    | `qwen3.5-122b-a10b` | \$0.12 | \$0.96 | OpenAI 兼容 |
    | `qwen3.5-27b` | \$0.09 | \$0.72 | OpenAI 兼容 |
    | `qwen3.5-35b-a3b` | \$0.06 | \$0.48 | OpenAI 兼容 |
    | `qwen3.5-397b-a17b` | \$0.18 | \$1.08 | OpenAI 兼容 |
    | `qwen3.5-flash` † | \$0.027397 | \$0.273973 | OpenAI 兼容 |
    | `qwen3.5-plus` † | \$0.109589 | \$0.657534 | OpenAI 兼容 |
    | `qwen3.5-flash-2026-02-23` † | \$0.027397 | \$0.273973 | OpenAI 兼容 |
    | `qwen3.5-plus-2026-02-15` † | \$0.109589 | \$0.657534 | OpenAI 兼容 |
    | `qwen3-235b-a22b` | \$1 | \$10 | OpenAI 兼容 |
    | `qwen3-coder-480b-a35b-instruct` | \$3 | \$15 | OpenAI 兼容 |
    | `qwen3-coder-flash` † | \$0.136986 | \$0.547945 | OpenAI 兼容 |
    | `qwen3-coder-plus` † | \$0.547945 | \$2.1918 | OpenAI 兼容 |
    | `qwen3-max` † | \$0.342466 | \$1.3699 | OpenAI 兼容 |
    | `qwen3-max-preview` † | \$0.821918 | \$3.2877 | OpenAI 兼容 |
    | `qwen3-next-80b-a3b-instruct` | \$0.15 | \$1.2 | OpenAI 兼容 |
    | `qwen3-omni-flash` | \$2 | \$20 | OpenAI 兼容 |
    | `qwen3-vl-235b-a22b-instruct` | \$0.3 | \$3 | OpenAI 兼容 |
    | `qwen3-vl-235b-a22b-thinking` | \$0.3 | \$3 | OpenAI 兼容 |
    | `qwen3-vl-30b-a3b-thinking` | \$0.12 | \$1.2 | OpenAI 兼容 |
    | `qwen3-vl-32b-thinking` | \$0.3 | \$3 | OpenAI 兼容 |
    | `qwen3-vl-flash` | \$0.1 | \$0.8 | OpenAI 兼容 |
    | `qwen3-vl-plus` † | \$0.136986 | \$1.3699 | OpenAI 兼容 |
    | `qwen3-vl-flash-2025-10-15` | \$0.1 | \$0.8 | OpenAI 兼容 |
    | `qwen3-coder-plus-2025-09-23` † | \$0.547945 | \$2.1918 | OpenAI 兼容 |
    | `qwen3-max-2025-09-23` † | \$0.821918 | \$3.2877 | OpenAI 兼容 |
    | `qwen3-vl-plus-2025-09-23` † | \$0.136986 | \$1.3699 | OpenAI 兼容 |
    | `qwen3-omni-flash-2025-09-15` | \$2 | \$20 | OpenAI 兼容 |
    | `qwen3-coder-plus-2025-07-22` † | \$0.547945 | \$2.1918 | OpenAI 兼容 |
    | `qwen3-235b-a22b-instruct-2507` | \$1 | \$10 | OpenAI 兼容 |
    | `qwen3-235b-a22b-thinking-2507` | \$1.6 | \$12.8 | OpenAI 兼容 |
    | `qwen3-30b-a3b-instruct-2507` | \$0.2 | \$0.8 | OpenAI 兼容 |
    | `qwen3-30b-a3b-thinking-2507` | \$0.2 | \$2.4 | OpenAI 兼容 |
    | `qwen-plus-latest` † | \$0.109589 | \$0.273973 | OpenAI 兼容 |
    | `qwen-vl-ocr-latest` | \$0.044 | \$0.07348 | OpenAI 兼容 |
    | `qvq-plus` | \$0.28 | \$0.7 | OpenAI 兼容 |
    | `qwen-long` | \$0.07 | \$0.28 | OpenAI 兼容 |
    | `qwen-max` | \$1.6 | \$6.4 | OpenAI 兼容 |
    | `qwen-max-longcontext` | \$3.2 | \$3.2 | OpenAI 兼容 |
    | `qwen-mt-plus` | \$2 | \$8 | OpenAI 兼容 |
    | `qwen-mt-turbo` | \$0.2 | \$0.5 | OpenAI 兼容 |
    | `qwen-plus` † | \$0.109589 | \$0.273973 | OpenAI 兼容 |
    | `qwen-turbo` | \$0.2 | \$0.6 | OpenAI 兼容 |
    | `qwen-vl-max` | \$0.2 | \$0.8 | OpenAI 兼容 |
    | `qwen-vl-ocr` | \$0.72 | \$0.72 | OpenAI 兼容 |
    | `qwen-vl-plus` | \$0.2 | \$0.6 | OpenAI 兼容 |
    | `qwen-vl-ocr-2025-11-20` | \$0.044 | \$0.07348 | OpenAI 兼容 |
    | `qwen-plus-2025-09-11` † | \$0.109589 | \$0.273973 | OpenAI 兼容 |
    | `qwen-plus-2025-07-14` | \$0.4 | \$4 | OpenAI 兼容 |

    <h3 id="vendor-阿里巴巴-video">视频生成 <span className="lp-count">8</span></h3>

    <p className="lp-table-note">以下模型的令牌分组：<code>Wan（×0.15）</code>。</p>

    | 模型 ID | 计费 | 调用接口 |
    | - | - | - |
    | `wan2.7-i2v` | [见模型文档](/api-capabilities/wan-video-generation) | OpenAI 兼容 |
    | `wan2.7-r2v` | [见模型文档](/api-capabilities/wan-video-generation) | OpenAI 兼容 |
    | `wan2.7-t2v` | [见模型文档](/api-capabilities/wan-video-generation) | OpenAI 兼容 |
    | `wan2.7-videoedit` | [见模型文档](/api-capabilities/wan-video-generation) | OpenAI 兼容 |
    | `wan2.6-i2v` | [见模型文档](/api-capabilities/wan-video-generation) | OpenAI 兼容 |
    | `wan2.6-r2v` | [见模型文档](/api-capabilities/wan-video-generation) | OpenAI 兼容 |
    | `wan2.6-r2v-flash` | [见模型文档](/api-capabilities/wan-video-generation) | OpenAI 兼容 |
    | `wan2.6-t2v` | [见模型文档](/api-capabilities/wan-video-generation) | OpenAI 兼容 |

    <h3 id="vendor-阿里巴巴-embedding">向量嵌入 <span className="lp-count">1</span></h3>

    <p className="lp-table-note">以下模型的令牌分组：<code>default</code>。</p>

    | 模型 ID | 输入（/1M tokens） | 输出（/1M tokens） | 调用接口 |
    | - | -: | -: | - |
    | `text-embedding-v4` | \$0.07 | \$0.07 | Embeddings, OpenAI 兼容 |

    <h2 id="vendor-字节跳动">字节跳动 <span className="lp-count">13</span></h2>

    <h3 id="vendor-字节跳动-text">文本对话 <span className="lp-count">4</span></h3>

    <p className="lp-table-note">以下模型的令牌分组：<code>default</code>。</p>

    | 模型 ID | 输入（/1M tokens） | 输出（/1M tokens） | 调用接口 |
    | - | -: | -: | - |
    | `seed-2-0-lite-260428` | \$0.25 | \$2 | OpenAI 兼容 |
    | `seed-2-0-mini-260428` | \$0.1 | \$0.4 | OpenAI 兼容 |
    | `seed-2-0-code-preview-260328` | \$0.5 | \$3 | OpenAI 兼容 |
    | `seed-2-0-pro-260328` | \$0.5 | \$3 | OpenAI 兼容 |

    <h3 id="vendor-字节跳动-image">图像生成与编辑 <span className="lp-count">5</span></h3>

    <p className="lp-table-note">以下模型的令牌分组：<code>default</code>。</p>

    | 模型 ID | 按次价格 | 调用接口 |
    | - | -: | - |
    | `seedream-5-0-flash-260915` | \$0.018 / 次 | OpenAI 兼容 |
    | `seedream-5-0-pro-260628` | \$0.12 / 次 | OpenAI 兼容 |
    | `seedream-5-0-260128` | \$0.035 / 次 | OpenAI 兼容 |
    | `seedream-4-5-251128` | \$0.045 / 次 | OpenAI 兼容 |
    | `seedream-4-0-250828` | \$0.035 / 次 | OpenAI 兼容 |

    <h3 id="vendor-字节跳动-video">视频生成 <span className="lp-count">4</span></h3>

    <p className="lp-table-note">以下模型的令牌分组：<code>SeeDance2（×0.18）</code>。</p>

    | 模型 ID | 计费 | 调用接口 |
    | - | - | - |
    | `doubao-seedance-2-5-260628` | [见模型文档](/api-capabilities/seedance2-video-generation) | OpenAI 兼容 |
    | `doubao-seedance-2-0-mini-260615` | [见模型文档](/api-capabilities/seedance2-video-generation) | OpenAI 兼容 |
    | `doubao-seedance-2-0-260128` | [见模型文档](/api-capabilities/seedance2-video-generation) | OpenAI 兼容 |
    | `doubao-seedance-2-0-fast-260128` | [见模型文档](/api-capabilities/seedance2-video-generation) | OpenAI 兼容 |

    <h2 id="vendor-智谱">智谱 <span className="lp-count">5</span></h2>

    <p className="lp-vendor-type">文本对话</p>

    | 模型 ID | 输入（/1M tokens） | 输出（/1M tokens） | 令牌分组 | 调用接口 |
    | - | -: | -: | - | - |
    | `glm-5.2` | \$1.142 | \$3.997 | claude\_code, default | Anthropic Messages, OpenAI 兼容 |
    | `glm-5.1` † | \$0.84 | \$3.36 | default | OpenAI 兼容 |
    | `glm-5` | \$0.56 | \$2.52 | default | OpenAI 兼容 |
    | `glm-4.7` | \$0.6 | \$2.16 | default | OpenAI 兼容 |
    | `glm-4.6` | \$0.5 | \$2 | default | OpenAI 兼容 |

    <h2 id="vendor-moonshot">Moonshot <span className="lp-count">1</span></h2>

    <p className="lp-vendor-type">文本对话</p>

    <p className="lp-table-note">以下模型的令牌分组：<code>default</code>。</p>

    | 模型 ID | 输入（/1M tokens） | 输出（/1M tokens） | 缓存读（/1M tokens） | 调用接口 |
    | - | -: | -: | -: | - |
    | `kimi-k2.5` | \$0.6 | \$3.15 | \$0.1 | OpenAI 兼容 |

    <h2 id="vendor-minimax">MiniMax <span className="lp-count">2</span></h2>

    <p className="lp-vendor-type">文本对话</p>

    <p className="lp-table-note">以下模型的令牌分组：<code>default</code>。</p>

    | 模型 ID | 输入（/1M tokens） | 输出（/1M tokens） | 调用接口 |
    | - | -: | -: | - |
    | `MiniMax-M2.5` | \$0.3 | \$1.2 | OpenAI 兼容 |
    | `MiniMax-M2.1` | \$0.3 | \$1.2 | OpenAI 兼容 |

    <h2 id="vendor-black-forest-labs">Black Forest Labs <span className="lp-count">5</span></h2>

    <p className="lp-vendor-type">图像生成与编辑</p>

    <p className="lp-table-note">以下模型的令牌分组：<code>default</code>。</p>

    | 模型 ID | 按次价格 | 调用接口 |
    | - | -: | - |
    | `flux-2-flex` | \$0.06 / 次 | Images, OpenAI 兼容 |
    | `flux-2-max` | \$0.07 / 次 | Images, OpenAI 兼容 |
    | `flux-2-pro` | \$0.03 / 次 | Images, OpenAI 兼容 |
    | `flux-kontext-max` | \$0.07 / 次 | Images, OpenAI 兼容 |
    | `flux-kontext-pro` | \$0.035 / 次 | Images, OpenAI 兼容 |

    <h2 id="vendor-阶跃星辰">阶跃星辰 <span className="lp-count">1</span></h2>

    <p className="lp-vendor-type">文本对话</p>

    <p className="lp-table-note">以下模型的令牌分组：<code>default</code>。</p>

    | 模型 ID | 输入（/1M tokens） | 输出（/1M tokens） | 调用接口 |
    | - | -: | -: | - |
    | `step-3.5-flash` | \$0.1 | \$0.3 | OpenAI 兼容 |

    <h2 id="tiered-pricing">阶梯计价</h2>

    <p>标有 † 的模型按单次请求的 token 数量分档计价，一次请求整体落在一个档位。目录表显示首档价格，各档位如下；实际档位与扣费以调用日志为准。</p>

    | 模型 ID | 单次请求 tokens | 输入（/1M tokens） | 输出（/1M tokens） | 缓存读（/1M tokens） |
    | - | - | -: | -: | -: |
    | `qwen3.6-plus` | 0–256,000 | \$0.273973 | \$1.6438 | — |
    | `qwen3.6-plus` | 256,001 以上 | \$1.0959 | \$6.5753 | — |
    | `qwen3.5-flash` | 0–128,000 | \$0.027397 | \$0.273973 | — |
    | `qwen3.5-flash` | 128,001–256,000 | \$0.109589 | \$1.0959 | — |
    | `qwen3.5-flash` | 256,001 以上 | \$0.164384 | \$1.6438 | — |
    | `qwen3.5-plus` | 0–128,000 | \$0.109589 | \$0.657534 | — |
    | `qwen3.5-plus` | 128,001–256,000 | \$0.273973 | \$1.6438 | — |
    | `qwen3.5-plus` | 256,001 以上 | \$0.547945 | \$3.2877 | — |
    | `qwen3.5-flash-2026-02-23` | 0–128,000 | \$0.027397 | \$0.273973 | — |
    | `qwen3.5-flash-2026-02-23` | 128,001–256,000 | \$0.109589 | \$1.0959 | — |
    | `qwen3.5-flash-2026-02-23` | 256,001 以上 | \$0.164384 | \$1.6438 | — |
    | `qwen3.5-plus-2026-02-15` | 0–128,000 | \$0.109589 | \$0.657534 | — |
    | `qwen3.5-plus-2026-02-15` | 128,001–256,000 | \$0.273973 | \$1.6438 | — |
    | `qwen3.5-plus-2026-02-15` | 256,001 以上 | \$0.547945 | \$3.2877 | — |
    | `qwen3-coder-flash` | 0–32,000 | \$0.136986 | \$0.547945 | — |
    | `qwen3-coder-flash` | 32,001–128,000 | \$0.205479 | \$0.821918 | — |
    | `qwen3-coder-flash` | 128,001–256,000 | \$0.342466 | \$1.3699 | — |
    | `qwen3-coder-flash` | 256,001 以上 | \$0.684932 | \$3.4247 | — |
    | `qwen3-coder-plus` | 0–32,000 | \$0.547945 | \$2.1918 | — |
    | `qwen3-coder-plus` | 32,001–128,000 | \$0.821918 | \$3.2877 | — |
    | `qwen3-coder-plus` | 128,001–256,000 | \$1.3699 | \$5.4795 | — |
    | `qwen3-coder-plus` | 256,001 以上 | \$2.7397 | \$27.3973 | — |
    | `qwen3-max` | 0–32,000 | \$0.342466 | \$1.3699 | — |
    | `qwen3-max` | 32,001–128,000 | \$0.547945 | \$2.1918 | — |
    | `qwen3-max` | 128,001 以上 | \$0.958904 | \$3.8356 | — |
    | `qwen3-max-preview` | 0–32,000 | \$0.821918 | \$3.2877 | — |
    | `qwen3-max-preview` | 32,001–128,000 | \$1.3699 | \$5.4795 | — |
    | `qwen3-max-preview` | 128,001 以上 | \$2.0548 | \$8.2192 | — |
    | `qwen3-vl-plus` | 0–32,000 | \$0.136986 | \$1.3699 | — |
    | `qwen3-vl-plus` | 32,001–128,000 | \$0.205479 | \$2.0548 | — |
    | `qwen3-vl-plus` | 128,001 以上 | \$0.410959 | \$4.1096 | — |
    | `qwen3-coder-plus-2025-09-23` | 0–32,000 | \$0.547945 | \$2.1918 | — |
    | `qwen3-coder-plus-2025-09-23` | 32,001–128,000 | \$0.821918 | \$3.2877 | — |
    | `qwen3-coder-plus-2025-09-23` | 128,001–256,000 | \$1.3699 | \$5.4795 | — |
    | `qwen3-coder-plus-2025-09-23` | 256,001 以上 | \$2.7397 | \$27.3973 | — |
    | `qwen3-max-2025-09-23` | 0–32,000 | \$0.821918 | \$3.2877 | — |
    | `qwen3-max-2025-09-23` | 32,001–128,000 | \$1.3699 | \$5.4795 | — |
    | `qwen3-max-2025-09-23` | 128,001 以上 | \$2.0548 | \$8.2192 | — |
    | `qwen3-vl-plus-2025-09-23` | 0–32,000 | \$0.136986 | \$1.3699 | — |
    | `qwen3-vl-plus-2025-09-23` | 32,001–128,000 | \$0.205479 | \$2.0548 | — |
    | `qwen3-vl-plus-2025-09-23` | 128,001 以上 | \$0.410959 | \$4.1096 | — |
    | `qwen3-coder-plus-2025-07-22` | 0–32,000 | \$0.547945 | \$2.1918 | — |
    | `qwen3-coder-plus-2025-07-22` | 32,001–128,000 | \$0.821918 | \$3.2877 | — |
    | `qwen3-coder-plus-2025-07-22` | 128,001–256,000 | \$1.3699 | \$5.4795 | — |
    | `qwen3-coder-plus-2025-07-22` | 256,001 以上 | \$2.7397 | \$27.3973 | — |
    | `qwen-plus-latest` | 0–128,000 | \$0.109589 | \$0.273973 | — |
    | `qwen-plus-latest` | 128,001–256,000 | \$0.328767 | \$2.7397 | — |
    | `qwen-plus-latest` | 256,001 以上 | \$0.657534 | \$6.5753 | — |
    | `qwen-plus` | 0–128,000 | \$0.109589 | \$0.273973 | — |
    | `qwen-plus` | 128,001–256,000 | \$0.328767 | \$2.7397 | — |
    | `qwen-plus` | 256,001 以上 | \$0.657534 | \$6.5753 | — |
    | `qwen-plus-2025-09-11` | 0–128,000 | \$0.109589 | \$0.273973 | — |
    | `qwen-plus-2025-09-11` | 128,001–256,000 | \$0.328767 | \$2.7397 | — |
    | `qwen-plus-2025-09-11` | 256,001 以上 | \$0.657534 | \$6.5753 | — |
    | `glm-5.1` | 0–32,768 | \$0.84 | \$3.36 | — |
    | `glm-5.1` | 32,769 以上 | \$1.14 | \$3.99 | — |
    | `gemini-3.1-pro-preview` | 0–200,000 | \$2 | \$12 | \$0.2 |
    | `gemini-3.1-pro-preview` | 200,001 以上 | \$4 | \$18 | \$0.4 |
    | `gemini-2.5-pro` | 0–200,000 | \$1.25 | \$10 | \$0.125 |
    | `gemini-2.5-pro` | 200,001 以上 | \$2.5 | \$15 | \$0.25 |
    | `gpt-6.1-sol` | 0–272,000 | \$2 | \$10 | — |
    | `gpt-6.1-sol` | 272,001 以上 | \$4 | \$15 | — |
    | `gpt-6-astra` | 0–272,000 | \$10 | \$50 | \$1 |
    | `gpt-6-astra` | 272,001 以上 | \$20 | \$75 | \$2 |
    | `gpt-6-luna` | 0–272,000 | \$0.1 | \$0.5 | \$0.01 |
    | `gpt-6-luna` | 272,001 以上 | \$0.2 | \$0.75 | \$0.02 |
    | `gpt-6-sol` | 0–272,000 | \$2 | \$10 | \$0.2 |
    | `gpt-6-sol` | 272,001 以上 | \$4 | \$15 | \$0.4 |
    | `gpt-5.6-luna` | 0–272,000 | \$0.2 | \$1.2 | \$0.02 |
    | `gpt-5.6-luna` | 272,001 以上 | \$0.4 | \$1.8 | \$0.04 |
    | `gpt-5.6-sol` | 0–272,000 | \$4 | \$20 | \$0.4 |
    | `gpt-5.6-sol` | 272,001 以上 | \$8 | \$30 | \$0.8 |
    | `gpt-5.6-terra` | 0–272,000 | \$2 | \$12 | \$0.2 |
    | `gpt-5.6-terra` | 272,001 以上 | \$4 | \$18 | \$0.4 |
    | `gpt-5.5` | 0–271,999 | \$5 | \$30 | \$0.5 |
    | `gpt-5.5` | 272,000 以上 | \$10 | \$45 | \$1 |
    | `gpt-5.5-pro` | 0–271,999 | \$30 | \$180 | — |
    | `gpt-5.5-pro` | 272,000 以上 | \$60 | \$270 | — |
    | `gpt-5.4` | 0–271,999 | \$2.5 | \$15 | \$0.25 |
    | `gpt-5.4` | 272,000 以上 | \$5 | \$22.5 | \$0.5 |
    | `gpt-5.4-pro` | 0–271,999 | \$30 | \$180 | — |
    | `gpt-5.4-pro` | 272,000 以上 | \$60 | \$270 | — |
    | `grok-4.7` | 0–200,000 | \$2 | \$6 | — |
    | `grok-4.7` | 200,001 以上 | \$4 | \$12 | — |
    | `grok-4.6` | 0–204,800 | \$2 | \$6 | — |
    | `grok-4.6` | 204,801 以上 | \$4 | \$12 | — |

    <h2 id="pricing-basis">价格与计费说明</h2>

    <ul>
      <li>所有金额以美元计。按量模型的输入、输出和缓存读价格按每 1M tokens 计，按次模型按每次调用计。</li>
      <li>表中是默认标价。账号合同或专属线路可能采用不同价格，以控制台显示为准。</li>
      <li>缓存读价格只在请求命中该模型的提示词缓存时生效；“—”表示当前配置没有列出缓存读价格，未命中缓存时按普通输入价计费。</li>
      <li>令牌分组后的「×倍率」表示在该分组调用时，按列出价格乘以倍率计费。</li>
      <li>视频模型按任务或视频时长计费，价格和计算方式见 <a href="/api-capabilities/wan-video-generation">Wan</a> 与 <a href="/api-capabilities/seedance2-video-generation">Seedance 2</a> 文档。</li>
      <li><code>gpt-image-2</code> 同时有按次和按量线路，令牌应选哪种计费见 <a href="/api-capabilities/gpt-image-2">GPT Image 2 分组说明</a>。</li>
      <li>GPT Image 官转按 token 计费：Sora2Official 分组与 OpenAI 官方同价，GPTImage2 Sora2 Enterprise 分组为官方价加 20%。</li>
      <li>“调用接口”列是价格配置标注的协议入口。“OpenAI 兼容”表示按 OpenAI 格式调用对应端点（文本、图像、音频或审核因模型而异），不代表所有客户端参数都兼容。</li>
    </ul>

    <h2 id="commercial-terms">企业采购与折扣</h2>

    <p>企业采购、批量使用、合同、发票、折扣或特殊付款安排，请联系站长或支持团队确认。文档不公布固定折扣门槛或比例，最终条件以双方确认内容、控制台和调用日志为准。</p>

    <h2 id="faq">常见问题</h2>

    <div className="lp-faq">
      <div className="lp-faq-item">
        <h3>这是实时价格吗？</h3>
        <p>本页按系统价格配置生成，并显示更新时间。模型临时调价、账号分组或专属合同都可能让控制台价格与本页不同，最终以控制台和调用日志为准。</p>
      </div>

      <div className="lp-faq-item">
        <h3>怎样确认我的令牌能调用哪些模型？</h3>
        <p>用该令牌请求 <code>GET [https://api.laozhang.ai/v1/models](https://api.laozhang.ai/v1/models)</code>，返回列表就是这个令牌当前可调用的模型。令牌分组不同，列表也不同。</p>
      </div>

      <div className="lp-faq-item">
        <h3>表里找不到某个模型怎么办？</h3>
        <p>本页只列出公开价格配置中的在线模型。找不到时，说明该模型当前没有对外开放或已下架；上线与下架消息见<a href="/changelog">公告</a>，企业专属线路请联系支持确认。</p>
      </div>

      <div className="lp-faq-item">
        <h3>为什么表里没有 Claude 模型？</h3>
        <p>Claude 模型因资源不足暂时下线，恢复时会在<a href="/changelog">网站公告</a>通知。Anthropic Messages 协议仍可用于表中标注了该接口的模型，例如 <code>glm-5.2</code>。</p>
      </div>

      <div className="lp-faq-item">
        <h3>阶梯计价如何计算？</h3>
        <p>系统按单次请求的 token 数量选择档位，整次请求按该档位的输入、输出和缓存读价格计费。各档位见上方「阶梯计价」表。</p>
      </div>

      <div className="lp-faq-item">
        <h3>找到模型 ID 后怎么调用？</h3>
        <p>先看表中的调用接口和令牌分组，在控制台创建对应分组的令牌。文本模型的 OpenAI 兼容入口是 <code>/v1/chat/completions</code>；图像、视频、音频等模型按「按用途选模型」中的接入文档调用。</p>
      </div>

      <div className="lp-faq-item">
        <h3>企业采购、批量使用或折扣怎么确认？</h3>
        <p>请联系站长或支持团队，说明账户、模型、预计用量、合同和发票需求。文档不承诺固定折扣门槛或比例。</p>
      </div>
    </div>

    <p className="lp-footnote">价格快照生成时间: <code>2026-10-07T09:29:21.919Z</code></p>
  </div>
</div>


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