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Logits Token：更快、更稳、更有保障的 AI API 服务 Logits Token 致力于为开发者和企业提供高性能、稳定可靠的 AI 模型调用服务，支持 GPT、Gemini、Claude 等主流模型，提供统一的 API 接入方式，让应用开发更加简单高效。 我们持续优化请求链路与模型路由，降低响应延迟，提升高并发场景下的稳定性，帮助用户获得更快速、更流畅的调用体验。 针对 GPT 流式请求，我们还提供独特的“首字超时赔付机制”：当请求首个 Token 响应超过平台设定阈值时，系统将依据赔付规则自动返还部分或全部费用，降低调用延迟带来的使用风险。 选择 Logits Token，享受快速、稳定、透明，并且更有保障的 AI API 服务。
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Fable 5
2 public records are listed; open the full page to review details as needed.
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Opus 4.8
2 public records are listed; open the full page to review details as needed.
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Opus 4.7
2 public records are listed; open the full page to review details as needed.
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Sonnet 5
2 public records are listed; open the full page to review details as needed.
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GPT 5.6 Sol
1 public records are listed; open the full page to review details as needed.
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GPT 5.6 Terra
1 public records are listed; open the full page to review details as needed.
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GPT 5.5
1 public records are listed; open the full page to review details as needed.
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GPT Image 2
1 public records are listed; open the full page to review details as needed.
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Opus 4.6
2 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 |
|---|---|---|---|---|---|---|
| CC Max满血号池(官方客户端) | claude-fable-5 | 输入 ¥13 / 输出 ¥65 / 缓存 ¥1.3 / 写入 ¥16.25 | 0% | — | — | — |
| CC Max满血号池(不限客户端) | claude-fable-5 | 输入 ¥15 / 输出 ¥75 / 缓存 ¥1.5 / 写入 ¥18.75 | 0% | — | — | — |
| Channel | Provider model | Current price | Price trend | Uptime | Fake % | Latency |
|---|---|---|---|---|---|---|
| CC Max满血号池(官方客户端) | claude-opus-4-8 | 输入 ¥6.5 / 输出 ¥32.5 / 缓存 ¥0.65 / 写入 ¥8.13 | 0% | — | — | — |
| CC Max满血号池(不限客户端) | claude-opus-4-8 | 输入 ¥7.5 / 输出 ¥37.5 / 缓存 ¥0.75 / 写入 ¥9.38 | 0% | — | — | — |
| Channel | Provider model | Current price | Price trend | Uptime | Fake % | Latency |
|---|---|---|---|---|---|---|
| CC Max满血号池(官方客户端) | claude-opus-4-7 | 输入 ¥6.5 / 输出 ¥32.5 / 缓存 ¥0.65 / 写入 ¥8.13 | 0% | — | — | — |
| CC Max满血号池(不限客户端) | claude-opus-4-7 | 输入 ¥7.5 / 输出 ¥37.5 / 缓存 ¥0.75 / 写入 ¥9.38 | 0% | — | — | — |
| Channel | Provider model | Current price | Price trend | Uptime | Fake % | Latency |
|---|---|---|---|---|---|---|
| CC Max满血号池(官方客户端) | claude-sonnet-5 | 输入 ¥2.6 / 输出 ¥13 / 缓存 ¥0.26 / 写入 ¥3.25 | 0% | — | — | — |
| CC Max满血号池(不限客户端) | claude-sonnet-5 | 输入 ¥3 / 输出 ¥15 / 缓存 ¥0.3 / 写入 ¥3.75 | 0% | — | — | — |
| Channel | Provider model | Current price | Price trend | Uptime | Fake % | Latency |
|---|---|---|---|---|---|---|
| GPT慢必赔 | gpt-5.6-sol | 输入 ¥2 / 输出 ¥12 / 缓存 ¥0.2 / 写入 ¥2.5 | 0% | — | — | — |
| Channel | Provider model | Current price | Price trend | Uptime | Fake % | Latency |
|---|---|---|---|---|---|---|
| GPT慢必赔 | gpt-5.6-terra | 输入 ¥0.8 / 输出 ¥4.8 / 缓存 ¥0.08 / 写入 ¥1 | 0% | — | — | — |
| Channel | Provider model | Current price | Price trend | Uptime | Fake % | Latency |
|---|---|---|---|---|---|---|
| GPT慢必赔 | gpt-5.5 | 输入 ¥2 / 输出 ¥12 / 缓存 ¥0.2 / 写入 ¥0 | 0% | — | — | — |
| Channel | Provider model | Current price | Price trend | Uptime | Fake % | Latency |
|---|---|---|---|---|---|---|
| 生图 | gpt-image-2 | ¥0.2 / 次 | - | — | — | — |
| Channel | Provider model | Current price | Price trend | Uptime | Fake % | Latency |
|---|---|---|---|---|---|---|
| CC Max满血号池(官方客户端) | claude-opus-4-6 | 输入 ¥6.5 / 输出 ¥32.5 / 缓存 ¥0.65 / 写入 ¥8.13 | 0% | — | — | — |
| CC Max满血号池(不限客户端) | claude-opus-4-6 | 输入 ¥7.5 / 输出 ¥37.5 / 缓存 ¥0.75 / 写入 ¥9.38 | 0% | — | — | — |
平台定价说明 1. 汇率换算 本平台采用 1 美元 = 1 元人民币 的统一换算标准。 模型费用以官方美元定价为基础，平台会将价格单位直接换算为平台余额，具体扣费不再按照实时汇率折算。 2. 分组费率倍率 平台会根据不同分组设置相应的费率倍率。例如： 0.33x 表示平台费率为模型官方价格的 0.33 倍； 当模型按照官方定价消耗 1 美元 时，平台将扣除 0.33 元平台余额 ； 按照 1 美元 ≈ 6.8 元人民币 的汇率粗略换算，0.33 元约相当于官方价格的 4.85% ，即约 0.4 折 。 3. 实际扣费计算 实际扣费公式如下： text 实际扣费 = 模型官方价格（美元） × 分组费率倍率 例如，某次对话按照模型官方定价产生 1 美元 的费用，若当前分组费率为 0.33x ，则平台实际扣除： text 1 × 0.33 = 0.33 元平台余额 注：平台余额单位为人民币元，以上价格说明仅用于平台计费换算，实际费用以平台最终扣费记录为准。
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.