GLM-5

更低单价的 GLM 路线，适合生产推理、智能体与长上下文工作流。

公开模型详情MoE Transformer

参数规模

744B / 40B active

上下文

198K

最大输出

64K

许可证

Apache 2.0

TTFT

520ms

吞吐

42 tok/s

为什么选它

面向推理智能体的高性价比
与 GLM-5.1 同属 Z.ai 旗舰家族

价格与差价

层级标准缓存SiliconFlow节省

在线调用$0.35 / $0.90$0.122$0.95 / $2.5563%

批处理$0.17 / $0.45$0.122$0.95 / $2.5563%

快速开始

OpenAI 兼容接口，切换 base_url 即可。

在 Playground 中试用查看价格页

Python

from openai import OpenAI

client = OpenAI(
    base_url="https://api.luminapath.tech/v1",
    api_key="BATCHIN_API_KEY"
)

resp = client.chat.completions.create(
    model="glm-5",
    messages=[{"role": "user", "content": "Summarize why this model is a fit for my workload."}]
)

print(resp.choices[0].message.content)

JavaScript

import OpenAI from "openai";

const client = new OpenAI({
  baseURL: "https://api.luminapath.tech/v1",
  apiKey: process.env.BATCHIN_API_KEY,
});

const resp = await client.chat.completions.create({
  model: "glm-5",
  messages: [{ role: "user", content: "Summarize why this model is a fit for my workload." }],
});

console.log(resp.choices[0]?.message?.content);

cURL

curl https://api.luminapath.tech/v1/chat/completions \
  -H "Authorization: Bearer $BATCHIN_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "glm-5",
    "messages": [{"role":"user","content":"Summarize why this model is a fit for my workload."}]
  }'

规格与行为

架构

MoE Transformer

厂商家族

Z.ai

上下文

198K

最大输出

64K

适用场景

reasoning

workflow