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ePhone AI 介绍 ePhone AI 是一家专注于 AI 大模型 API 中转服务的专业平台，支持 ChatGPT、Claude、Gemini 等主流顶尖 AI 模型的稳定接入，支持几乎所有的图片、视频模型，致力于为开发者、企业和创作者提供低成本、高效率的 AIGC 应用构建解决方案。 自 2024 年 3 月 正式上线运营以来，ePhone AI 凭借完整的技术团队架构与扎实的基础设施建设，持续为全球用户提供稳定、纯净、高性价比的 API 服务，是运营时间较早、体系较为完善的 API 中转服务商之一。 核心优势 🏗️ 自建基础设施 平台拥有自建机房，并接入 Cloudflare 企业版 网络加速，从底层保障连接稳定性与请求速度，彻底告别中转不稳、延迟高的痛点。 ⚡ 企业级高速渠道 100% 采用企业高速专用渠道，非共享低价线路，确保高并发场景下依然保持优秀的响应速度与可用性。 🔒 隐私安全承诺 平台承诺不保留任何聊天数据，无广告、无套路，100% 保障用户隐私与数据安全，适合有合规需求的企业客户。 🌐 无障碍全球直连 无需科学上网，全球直连访问，无封号风险，兼容 OpenAI 接口协议，开箱即用，接入成本极低。 💰 极致性价比 价格远低于官方定价，API Key 支持自定义使用时间与余额限制，灵活管理使用成本，适配个人开发者到大型企业的多样化需求。 ePhone AI 始终坚持以技术驱动服务，以稳定赢得信任，是您构建智能应用、实现自动化升级的可靠 AI 基础设施伙伴。
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GPT 5.6 Sol
5 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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Opus 5
4 public records are listed; open the full page to review details as needed.
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Claude Fable 5
5 public records are listed; open the full page to review details as needed.
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GPT Image 2
4 public records are listed; open the full page to review details as needed.
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Claude Opus 4.8
5 public records are listed; open the full page to review details as needed.
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GPT 5.6 Terra
5 public records are listed; open the full page to review details as needed.
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DeepSeek V4 Flash
1 public records are listed; open the full page to review details as needed.
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Kimi K3
1 public records are listed; open the full page to review details as needed.
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Grok 4.5
2 public records are listed; open the full page to review details as needed.
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GLM 5.2
2 public records are listed; open the full page to review details as needed.
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Claude Opus 4.6
5 public records are listed; open the full page to review details as needed.
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Claude Sonnet 5
5 public records are listed; open the full page to review details as needed.
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Claude Opus 4.7
5 public records are listed; open the full page to review details as needed.
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Claude Sonnet 4.6
5 public records are listed; open the full page to review details as needed.
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DeepSeek V3.2
2 public records are listed; open the full page to review details as needed.
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DeepSeek V4 Pro
1 public records are listed; open the full page to review details as needed.
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Gemini 3 Flash Preview
4 public records are listed; open the full page to review details as needed.
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Gemini 3.1 Pro
4 public records are listed; open the full page to review details as needed.
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Gemini 3.5 Flash
4 public records are listed; open the full page to review details as needed.
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Gemini 3.6 Flash
3 public records are listed; open the full page to review details as needed.
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GLM 5.1
2 public records are listed; open the full page to review details as needed.
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GLM-4.7
1 public records are listed; open the full page to review details as needed.
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GLM-5
1 public records are listed; open the full page to review details as needed.
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GPT 5.4
5 public records are listed; open the full page to review details as needed.
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GPT-5 mini
5 public records are listed; open the full page to review details as needed.
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GPT-5.2 Codex
5 public records are listed; open the full page to review details as needed.
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GPT-5.3 Codex
5 public records are listed; open the full page to review details as needed.
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GPT-5.4 Mini
5 public records are listed; open the full page to review details as needed.
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GPT-5.6 Luna
5 public records are listed; open the full page to review details as needed.
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Kimi 2.6
1 public records are listed; open the full page to review details as needed.
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Kimi K2.5
1 public records are listed; open the full page to review details as needed.
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mimo-v2.5
2 public records are listed; open the full page to review details as needed.
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mimo-v2.5-pro
2 public records are listed; open the full page to review details as needed.
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MiniMax M2.5
1 public records are listed; open the full page to review details as needed.
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MiniMax M2.7
1 public records are listed; open the full page to review details as needed.
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Qwen3.6 plus
1 public records are listed; open the full page to review details as needed.
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Step 3.5 Flash
1 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 |
|---|---|---|---|---|---|---|
| default | gpt-5.6-sol | 输入 ¥5.25 / 输出 ¥31.5 / 缓存 ¥0.525 / 写入 ¥0 | 0% | — | — | — |
| Official | gpt-5.6-sol | 输入 ¥18.55 / 输出 ¥111.3 / 缓存 ¥1.85 / 写入 ¥0 | 0% | — | — | — |
| azure | gpt-5.6-sol | 输入 ¥35 / 输出 ¥210 / 缓存 ¥3.5 / 写入 ¥0 | 0% | — | — | — |
| Channel | Provider model | Current price | Price trend | Uptime | Fake % | Latency |
|---|---|---|---|---|---|---|
| default | gpt-5.5 | 输入 ¥5.25 / 输出 ¥31.5 / 缓存 ¥0.525 / 写入 ¥0 | 0% | — | — | — |
| Official | gpt-5.5 | 输入 ¥18.55 / 输出 ¥111.3 / 缓存 ¥1.85 / 写入 ¥0 | 0% | — | — | — |
| azure | gpt-5.5 | 输入 ¥35 / 输出 ¥210 / 缓存 ¥3.5 / 写入 ¥0 | 0% | — | — | — |
| Channel | Provider model | Current price | Price trend | Uptime | Fake % | Latency |
|---|---|---|---|---|---|---|
| default | claude-opus-5 | 输入 ¥5.25 / 输出 ¥26.25 / 缓存 ¥0.525 / 写入 ¥10.5 | 0% | — | — | — |
| Official | claude-opus-5 | 输入 ¥18.55 / 输出 ¥92.75 / 缓存 ¥1.85 / 写入 ¥37.1 | 0% | — | — | — |
| amazon-bedrock | claude-opus-5 | 输入 ¥35 / 输出 ¥175 / 缓存 ¥3.5 / 写入 ¥70 | 0% | — | — | — |
| Channel | Provider model | Current price | Price trend | Uptime | Fake % | Latency |
|---|---|---|---|---|---|---|
| default | claude-fable-5 | 输入 ¥10.5 / 输出 ¥52.5 / 缓存 ¥1.05 / 写入 ¥21 | 0% | — | — | — |
| Official | claude-fable-5 | 输入 ¥37.1 / 输出 ¥185.5 / 缓存 ¥3.71 / 写入 ¥74.2 | 0% | — | — | — |
| amazon-bedrock | claude-fable-5 | 输入 ¥70 / 输出 ¥350 / 缓存 ¥7 / 写入 ¥140 | 0% | — | — | — |
| Channel | Provider model | Current price | Price trend | Uptime | Fake % | Latency |
|---|---|---|---|---|---|---|
| Official | gpt-image-2 | 输入 ¥18.55 / 输出 ¥111.3 / 缓存 ¥4.64 / 写入 ¥0 | 0% | — | — | — |
| azure | gpt-image-2 | 输入 ¥35 / 输出 ¥210 / 缓存 ¥8.75 / 写入 ¥0 | 0% | — | — | — |
| Enterprise | gpt-image-2 | 输入 ¥35 / 输出 ¥210 / 缓存 ¥8.75 / 写入 ¥0 | 0% | — | — | — |
| Channel | Provider model | Current price | Price trend | Uptime | Fake % | Latency |
|---|---|---|---|---|---|---|
| default | claude-opus-4-8 | 输入 ¥5.25 / 输出 ¥26.25 / 缓存 ¥0.525 / 写入 ¥10.5 | 0% | — | — | — |
| Official | claude-opus-4-8 | 输入 ¥18.55 / 输出 ¥92.75 / 缓存 ¥1.85 / 写入 ¥37.1 | 0% | — | — | — |
| amazon-bedrock | claude-opus-4-8 | 输入 ¥35 / 输出 ¥175 / 缓存 ¥3.5 / 写入 ¥70 | 0% | — | — | — |
| Channel | Provider model | Current price | Price trend | Uptime | Fake % | Latency |
|---|---|---|---|---|---|---|
| default | gpt-5.6-terra | 输入 ¥5.25 / 输出 ¥31.5 / 缓存 ¥0.525 / 写入 ¥0 | 0% | — | — | — |
| Official | gpt-5.6-terra | 输入 ¥18.55 / 输出 ¥111.3 / 缓存 ¥1.85 / 写入 ¥0 | 0% | — | — | — |
| azure | gpt-5.6-terra | 输入 ¥35 / 输出 ¥210 / 缓存 ¥3.5 / 写入 ¥0 | 0% | — | — | — |
| Channel | Provider model | Current price | Price trend | Uptime | Fake % | Latency |
|---|---|---|---|---|---|---|
| deepseek | deepseek-v4-flash | 输入 ¥0.8 / 输出 ¥1.6 / 缓存 ¥0.016 / 写入 ¥0 | 0% | — | — | — |
| Channel | Provider model | Current price | Price trend | Uptime | Fake % | Latency |
|---|---|---|---|---|---|---|
| moonshot | kimi-k3 | 输入 ¥16 / 输出 ¥80 / 缓存 ¥1.6 / 写入 ¥0 | 0% | — | — | — |
| Channel | Provider model | Current price | Price trend | Uptime | Fake % | Latency |
|---|---|---|---|---|---|---|
| Official | grok-4.5 | 输入 ¥4.64 / 输出 ¥9.28 / 缓存 ¥0.742 / 写入 ¥0 | 0% | — | — | — |
| xai | grok-4.5 | 输入 ¥8.75 / 输出 ¥17.5 / 缓存 ¥1.4 / 写入 ¥0 | 0% | — | — | — |
| Channel | Provider model | Current price | Price trend | Uptime | Fake % | Latency |
|---|---|---|---|---|---|---|
| Official | glm-5.2 | 输入 ¥5.19 / 输出 ¥16.32 / 缓存 ¥0.9646 / 写入 ¥0 | 0% | — | — | — |
| zhipu | glm-5.2 | 输入 ¥8.82 / 输出 ¥27.72 / 缓存 ¥1.64 / 写入 ¥0 | 0% | — | — | — |
| Channel | Provider model | Current price | Price trend | Uptime | Fake % | Latency |
|---|---|---|---|---|---|---|
| default | claude-opus-4-6 | 输入 ¥5.25 / 输出 ¥26.25 / 缓存 ¥0.525 / 写入 ¥10.5 | 0% | — | — | — |
| Official | claude-opus-4-6 | 输入 ¥18.55 / 输出 ¥92.75 / 缓存 ¥1.85 / 写入 ¥37.1 | 0% | — | — | — |
| amazon-bedrock | claude-opus-4-6 | 输入 ¥35 / 输出 ¥175 / 缓存 ¥3.5 / 写入 ¥70 | 0% | — | — | — |
| Channel | Provider model | Current price | Price trend | Uptime | Fake % | Latency |
|---|---|---|---|---|---|---|
| default | claude-sonnet-5 | 输入 ¥2.1 / 输出 ¥10.5 / 缓存 ¥0.21 / 写入 ¥4.2 | 0% | — | — | — |
| Official | claude-sonnet-5 | 输入 ¥7.42 / 输出 ¥37.1 / 缓存 ¥0.742 / 写入 ¥14.84 | 0% | — | — | — |
| amazon-bedrock | claude-sonnet-5 | 输入 ¥14 / 输出 ¥70 / 缓存 ¥1.4 / 写入 ¥28 | 0% | — | — | — |
| Channel | Provider model | Current price | Price trend | Uptime | Fake % | Latency |
|---|---|---|---|---|---|---|
| default | claude-opus-4-7 | 输入 ¥5.25 / 输出 ¥26.25 / 缓存 ¥0.525 / 写入 ¥10.5 | 0% | — | — | — |
| Official | claude-opus-4-7 | 输入 ¥18.55 / 输出 ¥92.75 / 缓存 ¥1.85 / 写入 ¥37.1 | 0% | — | — | — |
| amazon-bedrock | claude-opus-4-7 | 输入 ¥35 / 输出 ¥175 / 缓存 ¥3.5 / 写入 ¥70 | 0% | — | — | — |
| Channel | Provider model | Current price | Price trend | Uptime | Fake % | Latency |
|---|---|---|---|---|---|---|
| default | claude-sonnet-4-6 | 输入 ¥3.15 / 输出 ¥15.75 / 缓存 ¥0.315 / 写入 ¥6.3 | 0% | — | — | — |
| Official | claude-sonnet-4-6 | 输入 ¥11.13 / 输出 ¥55.65 / 缓存 ¥1.11 / 写入 ¥22.26 | 0% | — | — | — |
| amazon-bedrock | claude-sonnet-4-6 | 输入 ¥21 / 输出 ¥105 / 缓存 ¥2.1 / 写入 ¥42 | 0% | — | — | — |
| Channel | Provider model | Current price | Price trend | Uptime | Fake % | Latency |
|---|---|---|---|---|---|---|
| Official | deepseek-v3.2 | 输入 ¥1.06 / 输出 ¥1.59 / 缓存 ¥0 / 写入 ¥0 | 0% | — | — | — |
| deepseek | deepseek-v3.2 | 输入 ¥1.6 / 输出 ¥2.4 / 缓存 ¥0 / 写入 ¥0 | 0% | — | — | — |
| Channel | Provider model | Current price | Price trend | Uptime | Fake % | Latency |
|---|---|---|---|---|---|---|
| deepseek | deepseek-v4-pro | 输入 ¥2.4 / 输出 ¥4.8 / 缓存 ¥0.02 / 写入 ¥0 | 0% | — | — | — |
| Channel | Provider model | Current price | Price trend | Uptime | Fake % | Latency |
|---|---|---|---|---|---|---|
| Official | gemini-3-flash-preview | 输入 ¥1.85 / 输出 ¥11.13 / 缓存 ¥0.1855 / 写入 ¥0 | 0% | — | — | — |
| Enterprise | gemini-3-flash-preview | 输入 ¥3.5 / 输出 ¥21 / 缓存 ¥0.35 / 写入 ¥0 | 0% | — | — | — |
| google-ai-studio | gemini-3-flash-preview | 输入 ¥3.5 / 输出 ¥21 / 缓存 ¥0.35 / 写入 ¥0 | 0% | — | — | — |
| Channel | Provider model | Current price | Price trend | Uptime | Fake % | Latency |
|---|---|---|---|---|---|---|
| Official | gemini-3.1-pro-preview-customtools | 输入 ¥7.42 / 输出 ¥44.52 / 缓存 ¥0.742 / 写入 ¥0 | 0% | — | — | — |
| Enterprise | gemini-3.1-pro-preview-customtools | 输入 ¥14 / 输出 ¥84 / 缓存 ¥1.4 / 写入 ¥0 | 0% | — | — | — |
| google-ai-studio | gemini-3.1-pro-preview-customtools | 输入 ¥14 / 输出 ¥84 / 缓存 ¥1.4 / 写入 ¥0 | 0% | — | — | — |
| Channel | Provider model | Current price | Price trend | Uptime | Fake % | Latency |
|---|---|---|---|---|---|---|
| Official | gemini-3.5-flash | 输入 ¥5.57 / 输出 ¥33.39 / 缓存 ¥0.5565 / 写入 ¥0 | 0% | — | — | — |
| Enterprise | gemini-3.5-flash | 输入 ¥10.5 / 输出 ¥63 / 缓存 ¥1.05 / 写入 ¥0 | 0% | — | — | — |
| google-ai-studio | gemini-3.5-flash | 输入 ¥10.5 / 输出 ¥63 / 缓存 ¥1.05 / 写入 ¥0 | 0% | — | — | — |
| Channel | Provider model | Current price | Price trend | Uptime | Fake % | Latency |
|---|---|---|---|---|---|---|
| Official | gemini-3.6-flash | 输入 ¥5.57 / 输出 ¥27.82 / 缓存 ¥0.5565 / 写入 ¥0 | 0% | — | — | — |
| Enterprise | gemini-3.6-flash | 输入 ¥10.5 / 输出 ¥52.5 / 缓存 ¥1.05 / 写入 ¥0 | 0% | — | — | — |
| google-ai-studio | gemini-3.6-flash | 输入 ¥10.5 / 输出 ¥52.5 / 缓存 ¥1.05 / 写入 ¥0 | 0% | — | — | — |
| Channel | Provider model | Current price | Price trend | Uptime | Fake % | Latency |
|---|---|---|---|---|---|---|
| Official | glm-5.1 | 输入 ¥3.18 / 输出 ¥12.72 / 缓存 ¥0.689 / 写入 ¥0 | 0% | — | — | — |
| zhipu | glm-5.1 | 输入 ¥5.4 / 输出 ¥21.6 / 缓存 ¥1.17 / 写入 ¥0 | 0% | — | — | — |
| Channel | Provider model | Current price | Price trend | Uptime | Fake % | Latency |
|---|---|---|---|---|---|---|
| zhipu | glm-4.7 | 输入 ¥3.6 / 输出 ¥14.4 / 缓存 ¥0 / 写入 ¥0 | 0% | — | — | — |
| Channel | Provider model | Current price | Price trend | Uptime | Fake % | Latency |
|---|---|---|---|---|---|---|
| zhipu | glm-5 | 输入 ¥3.6 / 输出 ¥16.2 / 缓存 ¥0 / 写入 ¥0 | 0% | — | — | — |
| Channel | Provider model | Current price | Price trend | Uptime | Fake % | Latency |
|---|---|---|---|---|---|---|
| default | gpt-5.4 | 输入 ¥2.63 / 输出 ¥15.75 / 缓存 ¥0 / 写入 ¥0 | 0% | — | — | — |
| Official | gpt-5.4 | 输入 ¥9.28 / 输出 ¥55.65 / 缓存 ¥0 / 写入 ¥0 | 0% | — | — | — |
| azure | gpt-5.4 | 输入 ¥17.5 / 输出 ¥105 / 缓存 ¥0 / 写入 ¥0 | 0% | — | — | — |
| Channel | Provider model | Current price | Price trend | Uptime | Fake % | Latency |
|---|---|---|---|---|---|---|
| default | gpt-5-mini | 输入 ¥0.2625 / 输出 ¥2.1 / 缓存 ¥0.0262 / 写入 ¥0 | 0% | — | — | — |
| Official | gpt-5-mini | 输入 ¥0.9275 / 输出 ¥7.42 / 缓存 ¥0.0927 / 写入 ¥0 | 0% | — | — | — |
| azure | gpt-5-mini | 输入 ¥1.75 / 输出 ¥14 / 缓存 ¥0.175 / 写入 ¥0 | 0% | — | — | — |
| Channel | Provider model | Current price | Price trend | Uptime | Fake % | Latency |
|---|---|---|---|---|---|---|
| default | gpt-5.2-codex | 输入 ¥1.84 / 输出 ¥14.7 / 缓存 ¥0 / 写入 ¥0 | 0% | — | — | — |
| Official | gpt-5.2-codex | 输入 ¥6.49 / 输出 ¥51.94 / 缓存 ¥0 / 写入 ¥0 | 0% | — | — | — |
| azure | gpt-5.2-codex | 输入 ¥12.25 / 输出 ¥98 / 缓存 ¥0 / 写入 ¥0 | 0% | — | — | — |
| Channel | Provider model | Current price | Price trend | Uptime | Fake % | Latency |
|---|---|---|---|---|---|---|
| default | gpt-5.3-codex | 输入 ¥1.84 / 输出 ¥14.7 / 缓存 ¥0.1837 / 写入 ¥0 | 0% | — | — | — |
| Official | gpt-5.3-codex | 输入 ¥6.49 / 输出 ¥51.94 / 缓存 ¥0.6492 / 写入 ¥0 | 0% | — | — | — |
| azure | gpt-5.3-codex | 输入 ¥12.25 / 输出 ¥98 / 缓存 ¥1.23 / 写入 ¥0 | 0% | — | — | — |
| Channel | Provider model | Current price | Price trend | Uptime | Fake % | Latency |
|---|---|---|---|---|---|---|
| default | gpt-5.4-mini | 输入 ¥0.7875 / 输出 ¥4.72 / 缓存 ¥0.0788 / 写入 ¥0 | 0% | — | — | — |
| Official | gpt-5.4-mini | 输入 ¥2.78 / 输出 ¥16.7 / 缓存 ¥0.2782 / 写入 ¥0 | 0% | — | — | — |
| azure | gpt-5.4-mini | 输入 ¥5.25 / 输出 ¥31.5 / 缓存 ¥0.525 / 写入 ¥0 | 0% | — | — | — |
| Channel | Provider model | Current price | Price trend | Uptime | Fake % | Latency |
|---|---|---|---|---|---|---|
| default | gpt-5.6-luna | 输入 ¥5.25 / 输出 ¥31.5 / 缓存 ¥0.525 / 写入 ¥0 | 0% | — | — | — |
| Official | gpt-5.6-luna | 输入 ¥18.55 / 输出 ¥111.3 / 缓存 ¥1.85 / 写入 ¥0 | 0% | — | — | — |
| azure | gpt-5.6-luna | 输入 ¥35 / 输出 ¥210 / 缓存 ¥3.5 / 写入 ¥0 | 0% | — | — | — |
| Channel | Provider model | Current price | Price trend | Uptime | Fake % | Latency |
|---|---|---|---|---|---|---|
| moonshot | kimi-k2.6 | 输入 ¥5.2 / 输出 ¥21.6 / 缓存 ¥0.88 / 写入 ¥0 | 0% | — | — | — |
| Channel | Provider model | Current price | Price trend | Uptime | Fake % | Latency |
|---|---|---|---|---|---|---|
| moonshot | kimi-k2.5 | 输入 ¥3.2 / 输出 ¥16.8 / 缓存 ¥0 / 写入 ¥0 | 0% | — | — | — |
| Channel | Provider model | Current price | Price trend | Uptime | Fake % | Latency |
|---|---|---|---|---|---|---|
| Official | mimo-v2.5 | 输入 ¥0.53 / 输出 ¥1.06 / 缓存 ¥0.0106 / 写入 ¥0 | 0% | — | — | — |
| xiaomi | mimo-v2.5 | 输入 ¥0.8 / 输出 ¥1.6 / 缓存 ¥0.016 / 写入 ¥0 | 0% | — | — | — |
| Channel | Provider model | Current price | Price trend | Uptime | Fake % | Latency |
|---|---|---|---|---|---|---|
| Official | mimo-v2.5-pro | 输入 ¥1.59 / 输出 ¥3.18 / 缓存 ¥0.0132 / 写入 ¥0 | 0% | — | — | — |
| xiaomi | mimo-v2.5-pro | 输入 ¥2.4 / 输出 ¥4.8 / 缓存 ¥0.02 / 写入 ¥0 | 0% | — | — | — |
| Channel | Provider model | Current price | Price trend | Uptime | Fake % | Latency |
|---|---|---|---|---|---|---|
| minimax | MiniMax-M2.5 | 输入 ¥1.68 / 输出 ¥6.72 / 缓存 ¥0.168 / 写入 ¥2.1 | 0% | — | — | — |
| Channel | Provider model | Current price | Price trend | Uptime | Fake % | Latency |
|---|---|---|---|---|---|---|
| minimax | MiniMax-M2.7 | 输入 ¥1.68 / 输出 ¥6.72 / 缓存 ¥0.336 / 写入 ¥2.1 | 0% | — | — | — |
| Channel | Provider model | Current price | Price trend | Uptime | Fake % | Latency |
|---|---|---|---|---|---|---|
| alibaba | qwen3.6-plus | 输入 ¥1.6 / 输出 ¥9.6 / 缓存 ¥0.16 / 写入 ¥2 | 0% | — | — | — |
| Channel | Provider model | Current price | Price trend | Uptime | Fake % | Latency |
|---|---|---|---|---|---|---|
| stepfun | step-3.5-flash | 输入 ¥0.7 / 输出 ¥2.1 / 缓存 ¥0 / 写入 ¥0 | 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.