About
Compared with GLM-4.5, this generation brings several key improvements: Longer context window: The context window has been expanded from 128K to 200K tokens, enabling the model to handle more complex...
Pricing
| Input | $0.70 | per 1M prompt tokens |
|---|---|---|
| Output | $2.80 | per 1M generated tokens, reasoning included |
| Cached input | $0.14 | per 1M tokens read back from the prompt cache |
What a request costs
| Typical request | Each | Per 1,000 |
|---|---|---|
| Short chat reply1,500 in · 400 out | $0.0022 | $2.17 |
| Question over a long document40,000 in · 800 out | $0.030 | $30.24 |
| Agent tool step20,000 in · 1,200 out | $0.017 | $17.36 |
At the developer-API rate, before any provider promotion or prompt-cache saving. In the app, the model picker shows what a message costs on your plan before you send it.
Benchmarks
Head-to-head rankings
- #17Godot gamesAgent arenaElo 118053% wins
- #29Android appsAgent arenaElo 109953% wins
- #36Mobile appsAgent arenaElo 109447% wins
- #38Full stackAgent arenaElo 102942% wins
- #58SVGModel arenaElo 110852% wins
- #70Game devModel arenaElo 115455% wins
- #74Data vizModel arenaElo 116253% wins
- #763DModel arenaElo 112954% wins
- #76CodeModel arenaElo 116754% wins
- #76WebsitesModel arenaElo 117654% wins
Scores from Artificial Analysis; bars are scaled to the best model on our list. Rankings from Design Arena head-to-head votes. Published by OpenRouter alongside its catalogue.
Call it from code
OpenAI-compatible: point any OpenAI SDK at https://api.privateer.pro/v1 and set
model. Keys are created in the app under Settings.
cURL
curl https://api.privateer.pro/v1/chat/completions \
-H "Authorization: Bearer $PRIVATEER_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"model": "z-ai/glm-4.6",
"messages": [{ "role": "user", "content": "Hello" }]
}'Python
import os
from openai import OpenAI
client = OpenAI(
base_url="https://api.privateer.pro/v1",
api_key=os.environ["PRIVATEER_API_KEY"],
)
reply = client.chat.completions.create(
model="z-ai/glm-4.6",
messages=[{"role": "user", "content": "Hello"}],
)
print(reply.choices[0].message.content)JavaScript
import OpenAI from "openai";
const client = new OpenAI({
baseURL: "https://api.privateer.pro/v1",
apiKey: process.env.PRIVATEER_API_KEY,
});
const reply = await client.chat.completions.create({
model: "z-ai/glm-4.6",
messages: [{ role: "user", content: "Hello" }],
});
console.log(reply.choices[0].message.content);Parameters this model accepts
frequency_penaltyinclude_reasoninglogit_biasmax_tokensmin_ppresence_penaltyreasoningrepetition_penaltyresponse_formatseedstopstructured_outputstemperaturetool_choicetoolstop_ktop_p