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DeepSeek · 发布于 2026-04-24

DeepSeek V4 Pro (75% off) LLM 75% OFF

上下文 1M 最大输出 384K 类型 LLM 渠道 DeepSeek
deepseek/deepseek-v4-pro

DeepSeek V4 Pro is DeepSeek's flagship Mixture-of-Experts (MoE) model, featuring 1.6 trillion total parameters, 49 billion activated parameters, and a 1 million-token context window. It delivers exceptional performance in reasoning, coding, mathematics, and software engineering, making it ideal for demanding AI workloads. Built on the same architecture as DeepSeek V4 Flash, it adds a hybrid attention system for more efficient long-context processing. It supports High and XHigh reasoning modes (with XHigh corresponding to maximum reasoning), making it well suited for complex tasks such as full codebase analysis, multi-step agent workflows, large-scale information synthesis, and enterprise-grade automation.

定价

USD · 实时汇率
定价 USD / M
输入 $0.43
输出 $0.86
命中缓存 $0.0036
图片输入

供应商

同一模型,多渠道实时比价 · 最优值绿色高亮
供应商 上下文 最大输出 输入 /M 输出 /M 缓存 /M 延迟 吞吐
Tokenpony 1M 384K $1.71 $3.43 $0.01 762ms 19 t/s
Ali 1M 384K $1.71 $3.43 $0.14 2592ms 70 t/s
DeepSeek 1M 384K $0.43 $0.86 $0.0036 324ms 37 t/s

接入示例

Model Center 会在不同服务提供商之间规范化处理请求和响应,为你统一接口。

提供兼容 OpenAI 的 Completion API:既可直接调用,也可通过 OpenAI SDK 调用,一把 key 调用全部模型。

获取 API Key 获取 API Key
from openai import OpenAI

client = OpenAI(
    base_url="https://router-integration.test.cogfoundry.ai/api/v1",
    api_key="$MODEL_CENTER_API_KEY",
)

completion = client.chat.completions.create(
    model="deepseek/deepseek-v4-pro",
    messages=[{"role": "user", "content": "9.11 和 9.8 哪个大?"}],
    stream=True,
)

for chunk in completion:
    if chunk.choices and chunk.choices[0].delta.content is not None:
        print(chunk.choices[0].delta.content, end="", flush=True)

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