Publish time
-Model Series
Input type
Output type
Context Window
128,000Max Output Length
8,192Input Price
¥2 / 1M tokensOutput Price
¥3 / 1M tokensDeepSeek-V3.2 的目标是平衡推理能力与输出长度，适合日常使用，例如问答场景和通用 Agent 任务场景。在公开的推理类 Benchmark 测试中，DeepSeek-V3.2 达到了 GPT-5 的水平，仅略低于 Gemini-3.0-Pro；相比 Kimi-K2-Thinking，V3.2 的输出长度大幅降低，显著减少了计算开销与用户等待时间。
Zhinao API routes requests to the best-fit provider and automatically fails over to the one with highest availability.
TTFT
No data
Throughput
No data
Uptime
No data
Provider Model
paratera/deepseek-v3.2
Supported Parameters
Recent Uptime
Reasoning
-
Supported Response Formats
Request Log Collection
-
Distillable
-
Total Context
4,096
Max Output
2,048
Input Price
¥2 / 1M tokens
Output Price
¥3 / 1M tokens
TTFT
21.37s
Throughput
8.47tps
Uptime
74.00%
Provider Model
sophnet/deepseek-v3.2
Supported Parameters
Recent Uptime
Reasoning
-
Supported Response Formats
Request Log Collection
-
Distillable
-
Total Context
4,096
Max Output
2,048
Input Price
¥2 / 1M tokens
Output Price
¥3 / 1M tokens
Compare different providers across Zhinao API
16.84 tok/s
No data
Uptime for deepseek-v3.2 across all providers
Zhinao API normalizes requests and responses across providers for you
import OpenAI from "openai";
const client = new OpenAI({
baseURL: "https://api.360.cn/v1",
apiKey: process.env.ZHINAO_API_KEY,
});
const response = await client.chat.completions.create({
model: "deepseek-v3.2",
messages: [
{ role: "user", content: "Hello, how are you?" }
],
temperature: 0.7,
max_tokens: 1000,
});
console.log(response.choices[0].message.content);