为什么选它
- 支持 8 小时自主编码回路
- 相较 SiliconFlow 至少便宜 50%
Z.ai
glm-5.1
GLM-5.1
面向长时自主编码与深度推理的开源旗舰模型。
SWE-Bench Pro #1公开模型详情MoE Transformer
参数规模
754B MoE
上下文
198K
最大输出
128K
许可证
MIT
TTFT
520ms
吞吐
42 tok/s
价格与差价
层级标准缓存SiliconFlow节省
在线调用$0.50 / $1.50$0.175$1.40 / $4.4064%
批处理$0.25 / $0.75$0.175$1.40 / $4.4064%
快速开始
OpenAI 兼容接口，切换 base_url 即可。
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-5.1",
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-5.1",
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-5.1",
"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
128K
适用场景
reasoning
coding
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