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Sidrune AI是一个面向企业用户与个人开发者的多模型 AI 接入与管理平台。用户通过一个账户和统一 API，可以使用 GPT、Claude、Grok、DeepSeek、GLM、Kimi 等当前开放的模型，不必为每种模型分别管理账户、密钥和账单。 平台提供自营号池及多种非官方 API 线路，用户可以根据预算和使用场景，在价格优先与稳定性优先的线路之间选择。Sidrune AI 兼容常用的 OpenAI、Anthropic 接口，可接入 AI 编程工具、支持自定义接口的客户端，也可通过 SDK 用于应用、脚本和自动化工作流。多线路调度旨在降低单一线路波动的影响，但具体可用性仍以实际线路状态为准。 模型广场公开展示当前模型、线路与价格；工作台提供调用用量和费用记录，方便用户核对支出。平台支持按量余额和订阅套餐，并提供人民币结算、中文指南与支持。模型、价格和可用线路以官网模型广场的实时信息为准。
Price listing
Fable 5
10 public records are listed; open the full page to review details as needed.
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Opus 4.8
13 public records are listed; open the full page to review details as needed.
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Opus 4.7
13 public records are listed; open the full page to review details as needed.
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Sonnet 5
13 public records are listed; open the full page to review details as needed.
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GPT 5.6 Sol
6 public records are listed; open the full page to review details as needed.
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GPT 5.6 Terra
6 public records are listed; open the full page to review details as needed.
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GPT 5.5
5 public records are listed; open the full page to review details as needed.
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GLM 5.2
1 public records are listed; open the full page to review details as needed.
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GPT Image 2
6 public records are listed; open the full page to review details as needed.
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Opus 4.6
13 public records are listed; open the full page to review details as needed.
Current public prices are shown by model and channel. Token prices use CNY per 1M tokens unless another billing unit is shown.
| Channel | Provider model | Current price | Price trend | Uptime | Fake % | Latency |
|---|---|---|---|---|---|---|
| Claude-AWSQ | claude-fable-5 | 输入 ¥4 / 输出 ¥20 / 缓存 ¥0.4 / 写入 ¥8 | 0% | — | — | — |
| Claude-AWSB逆 | claude-fable-5 | 输入 ¥8 / 输出 ¥40 / 缓存 ¥0.8 / 写入 ¥16 | 0% | — | — | — |
| Claude-Max-cc | claude-fable-5 | 输入 ¥10 / 输出 ¥50 / 缓存 ¥1 / 写入 ¥12.5 | -17% | — | — | — |
| Channel | Provider model | Current price | Price trend | Uptime | Fake % | Latency |
|---|---|---|---|---|---|---|
| Claude-Kiro | claude-opus-4-8 | 输入 ¥1.25 / 输出 ¥6.25 / 缓存 ¥0.125 / 写入 ¥2.5 | 0% | — | — | — |
| Claude-AWSQ | claude-opus-4-8 | 输入 ¥2 / 输出 ¥10 / 缓存 ¥0.2 / 写入 ¥4 | 0% | — | — | — |
| Claude-Vertex逆 | claude-opus-4-8 | 输入 ¥3 / 输出 ¥15 / 缓存 ¥0.3 / 写入 ¥6 | 0% | — | — | — |
| Channel | Provider model | Current price | Price trend | Uptime | Fake % | Latency |
|---|---|---|---|---|---|---|
| Claude-Kiro | claude-opus-4-7 | 输入 ¥1.25 / 输出 ¥6.25 / 缓存 ¥0.125 / 写入 ¥2.5 | 0% | — | — | — |
| Claude-AWSQ | claude-opus-4-7 | 输入 ¥2 / 输出 ¥10 / 缓存 ¥0.2 / 写入 ¥4 | 0% | — | — | — |
| Claude-Vertex逆 | claude-opus-4-7 | 输入 ¥3 / 输出 ¥15 / 缓存 ¥0.3 / 写入 ¥6 | 0% | — | — | — |
| Channel | Provider model | Current price | Price trend | Uptime | Fake % | Latency |
|---|---|---|---|---|---|---|
| Claude-Kiro | claude-sonnet-5 | 输入 ¥0.5 / 输出 ¥2.5 / 缓存 ¥0.05 / 写入 ¥1 | 0% | — | — | — |
| Claude-AWSQ | claude-sonnet-5 | 输入 ¥0.8 / 输出 ¥4 / 缓存 ¥0.08 / 写入 ¥1.6 | 0% | — | — | — |
| Claude-Vertex逆 | claude-sonnet-5 | 输入 ¥1.2 / 输出 ¥6 / 缓存 ¥0.12 / 写入 ¥2.4 | 0% | — | — | — |
| Channel | Provider model | Current price | Price trend | Uptime | Fake % | Latency |
|---|---|---|---|---|---|---|
| GPT-Pro | gpt-5.6-sol | 输入 ¥1 / 输出 ¥6 / 缓存 ¥0.1 / 写入 ¥1.25 | 0% | — | — | — |
| GPT-Pro优选 | gpt-5.6-sol | 输入 ¥1.5 / 输出 ¥9 / 缓存 ¥0.15 / 写入 ¥1.88 | 0% | — | — | — |
| GPT-OpenAI官逆 | gpt-5.6-sol | 输入 ¥2.5 / 输出 ¥15 / 缓存 ¥0.25 / 写入 ¥3.13 | 0% | — | — | — |
| Channel | Provider model | Current price | Price trend | Uptime | Fake % | Latency |
|---|---|---|---|---|---|---|
| GPT-Pro | gpt-5.6-terra | 输入 ¥0.4 / 输出 ¥2.4 / 缓存 ¥0.04 / 写入 ¥0.5 | 0% | — | — | — |
| GPT-Pro优选 | gpt-5.6-terra | 输入 ¥0.6 / 输出 ¥3.6 / 缓存 ¥0.06 / 写入 ¥0.75 | 0% | — | — | — |
| GPT-OpenAI官逆 | gpt-5.6-terra | 输入 ¥1 / 输出 ¥6 / 缓存 ¥0.1 / 写入 ¥1.25 | 0% | — | — | — |
| Channel | Provider model | Current price | Price trend | Uptime | Fake % | Latency |
|---|---|---|---|---|---|---|
| GPT-Pro | gpt-5.5 | 输入 ¥1 / 输出 ¥6 / 缓存 ¥0.1 / 写入 ¥0 | 0% | — | — | — |
| GPT-Pro优选 | gpt-5.5 | 输入 ¥1.5 / 输出 ¥9 / 缓存 ¥0.15 / 写入 ¥0 | 0% | — | — | — |
| GPT-OpenAI官逆 | gpt-5.5 | 输入 ¥2.5 / 输出 ¥15 / 缓存 ¥0.25 / 写入 ¥0 | 0% | — | — | — |
| Channel | Provider model | Current price | Price trend | Uptime | Fake % | Latency |
|---|---|---|---|---|---|---|
| GLM | glm-5.2 | 输入 ¥4.8 / 输出 ¥16.8 / 缓存 ¥1.2 / 写入 ¥4.8 | 0% | — | — | — |
| Channel | Provider model | Current price | Price trend | Uptime | Fake % | Latency |
|---|---|---|---|---|---|---|
| GPT-Pro | gpt-image-2 | ¥0.03 / 次 | - | — | — | — |
| GPT-Pro优选 | gpt-image-2 | ¥0.045 / 次 | - | — | — | — |
| GPT-OpenAI官逆 | gpt-image-2 | ¥0.075 / 次 | - | — | — | — |
| Channel | Provider model | Current price | Price trend | Uptime | Fake % | Latency |
|---|---|---|---|---|---|---|
| Claude-Kiro | claude-opus-4-6 | 输入 ¥1.25 / 输出 ¥6.25 / 缓存 ¥0.125 / 写入 ¥2.5 | 0% | — | — | — |
| Claude-AWSQ | claude-opus-4-6 | 输入 ¥2 / 输出 ¥10 / 缓存 ¥0.2 / 写入 ¥4 | 0% | — | — | — |
| Claude-Vertex逆 | claude-opus-4-6 | 输入 ¥3 / 输出 ¥15 / 缓存 ¥0.3 / 写入 ¥6 | 0% | — | — | — |
Uptime is the share of recent probes where the service was available; a higher value generally indicates better stability.
Model consistency uses model pass results to show whether the endpoint behaves like the target model.
Pricing and latency come from public monitoring data and are intended for side-by-side gateway comparison.
Data is provided for reference. Third-party gateways may experience outages or balance loss, so test first and add only a small balance when needed.