Z-ai model
GLM 4.5V API cost calculator
GLM 4.5V costs $0.60 per 1M input tokens and $1.80 per 1M output tokens on the Z-ai API, with a 66K-token context window. A typical request (2K input, 500 output tokens) costs $0.0021 — about $63.00/month at 1,000 requests per day. Use the calculator below to model your exact workload.
Find me a cheaper modelWhat real workloads cost on GLM 4.5V
| Workload | Tokens (in / out) | Per request | Per 1K requests |
|---|---|---|---|
| Chatbot message | 500 / 300 | $0.0008 | $0.84 |
| RAG query with context | 4,000 / 500 | $0.0033 | $3.30 |
| Document summarization | 20,000 / 1,000 | $0.01 | $13.80 |
| Agent coding session | 100,000 / 5,000 | $0.07 | $69.00 |
GLM 4.5V vs other Z-ai models
| Model | Input /1M | Output /1M | Context |
|---|---|---|---|
| GLM 4.5V | $0.60 | $1.80 | 66K |
| GLM 5.3 | $1.40 | $4.40 | 1.0M |
| GLM 5.2 | $0.97 | $3.04 | 1.0M |
| GLM 5.1 | $0.97 | $3.04 | 205K |
| GLM 5V Turbo | $1.20 | $4 | 203K |
Frequently asked questions
How much does GLM 4.5V cost per 1M tokens?
According to current pricing data, GLM 4.5V costs $0.60 per 1M input tokens and $1.80 per 1M output tokens. Processing 1M tokens each way costs $2.40.
What does a typical API request to GLM 4.5V cost?
A typical request with 2,000 input tokens and 500 output tokens costs $0.0021. At 1,000 requests per day that is $2.10 daily, or about $63.00 per month.
What is GLM 4.5V's context window?
GLM 4.5V supports a 66K-token context window (65,536 tokens).
Does GLM 4.5V support prompt caching?
Yes. Cached input tokens cost $0.11 per 1M — a 82% discount versus the standard input rate, which matters for agents and chat apps that resend the same system prompt.
What is a cheaper alternative to GLM 4.5V?
Ling-2.6-flash from Inclusionai is currently the cheapest comparable option at $0.01 per 1M input tokens versus $0.60 for GLM 4.5V — roughly 60x cheaper on input.
Compare all current prices on the live model pricing dashboard, see GLM 4.5V vs Ling-2.6-flash pricing, or run GLM 4.5V head-to-head against other models in the side-by-side comparison playground.
Pricing data via the OpenRouter models API.