GLM 4.7 Flash
Z.ai · Text · Context 198K · max output 131K tokens
glm-4.7-flash
Try
Pricing
| MarkasAI | Vendor list price | |
|---|---|---|
| Input | Rp 1.072 | Rp 1.253 |
| Output | Rp 6.116 | Rp 7.156 |
| Cache | Rp 1.072 | |
| Cache write | Rp 1.072 |
MarkasAI sale prices in Rupiah, read from the same catalog as GET /v1/models. Prices can change and apply to later requests.
Specifications
- Model ID
glm-4.7-flash- Provider
- Z.ai
- Type
- Text
- Endpoint
POST /v1/chat/completions- Context window
- 198,000 tokens
- Output limit per request
- 131,000 tokens
About this model
As a 30B-class SOTA model, GLM-4.7-Flash offers a new option that balances performance and efficiency. It is further optimized for agentic coding use cases, strengthening coding capabilities, long-horizon task planning,...
Quoted from the provider's public catalog, in English.
Call example
curl https://api.markas.ai.id/v1/chat/completions \
-H "Authorization: Bearer $MARKASAI_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"model": "glm-4.7-flash",
"messages": [{"role": "user", "content": "What is an API?"}],
"max_tokens": 300
}'import os
from openai import OpenAI
client = OpenAI(base_url="https://api.markas.ai.id/v1", api_key=os.environ["MARKASAI_API_KEY"])
resp = client.chat.completions.create(
model="glm-4.7-flash",
messages=[{"role": "user", "content": "What is an API?"}],
max_tokens=300,
)
print(resp.choices[0].message.content)import OpenAI from "openai";
const client = new OpenAI({ baseURL: "https://api.markas.ai.id/v1", apiKey: process.env.MARKASAI_API_KEY });
const resp = await client.chat.completions.create({
model: "glm-4.7-flash",
messages: [{ role: "user", content: "What is an API?" }],
max_tokens: 300,
});
console.log(resp.choices[0].message.content);Keep your API key in the MARKASAI_API_KEY environment variable. Read the endpoint docs