Context Window
131,072
Tokens
Model Cost Profile
Z.ai: GLM 4.5
Developer: z-ai
Pricing updated Mar 11, 2026
Input rank: #214Output rank: #231
Z.ai: GLM 4.5 offers an extensive context window of 131,000 tokens, making it ideal for applications requiring deep contextual understanding, such as legal document analysis and long-form content generation. With an input price of $0.55 per 1 million tokens and an output price of $2.00 per 1 million tokens, teams can effectively manage costs based on their specific usage patterns. This pricing structure allows organizations to scale their projects efficiently while leveraging the model's capabilities for complex tasks across various industries.
🔧 Tool Calling📋 Structured Output🧠 Reasoning
Input Price / 1M
$0.6000
Prompt tokens
Output Price / 1M
$2.20
Completion tokens
Intelligence (MMLU)
Benchmark Pending
Massive Multitask Language Understanding
Side-by-Side Pricing Table
| Usage Type | Price / 1M Tokens |
|---|---|
| Input (Prompt) | $0.6000 |
| Output (Completion) | $2.20 |
Price History
Z.ai: GLM 4.5 Pricing Trend
Input / 1M tokens0.0%Output / 1M tokens0.0%
Mar 7 — Mar 11
Current Input / 1M
$0.6000
Current Output / 1M
$2.20
Cost Calculator
Estimate monthly spend for Z.ai: GLM 4.5 based on your workload.
01.0B
0500M
Estimated Monthly Cost
$41
25M input + 12M output tokens
Cheaper Alternatives to Compare
Quick links for cost-down decisions before production rollout.
FAQ
Common pricing and benchmark questions for Z.ai: GLM 4.5.
How much does Z.ai: GLM 4.5 cost per 1M input tokens?
Z.ai: GLM 4.5 input pricing is $0.6000 per 1M tokens based on the latest synced provider data.
How much does Z.ai: GLM 4.5 cost per 1M output tokens?
Z.ai: GLM 4.5 output pricing is $2.20 per 1M tokens based on the latest synced provider data.
What context window does Z.ai: GLM 4.5 support?
Z.ai: GLM 4.5 supports a context window of 131,072 tokens.
How can I compare Z.ai: GLM 4.5 with cheaper alternatives?
Use the comparison links on this page to open direct model-vs-model pricing and benchmark pages, then evaluate monthly spend projections for your workload.