Z.AI · model
GLM 4.5V
$0.60/1M in · $1.80/1M out · 66K context. That's cheaper than 45% of the 298 models we track, by output price. Here's what it costs, how its price has moved, and where it fits.
- Context
- 66K
- Input / 1M
- $0.60
- Output / 1M
- $1.80
- Modality
- text + image
- Provider
- Z.AI
- Tokenizer
- Other
Snapshot · source: OpenRouter ↗ · how we measure →
For 1,500 input + 500 output tokens across 200,000 requests/month. That's 60× the cheapest tracked option (Ling-2.6-flash, $6.00/mo).
2026-06-14 → 2026-06-15. Full history →
Where it fits
- Multimodal prompts — accepts image input alongside text.
Watch for
- Priced from OpenRouter's routed market, not a first-party list price — availability and rate can shift without notice.
These notes are derived from price, context and modality — structural facts, not measured quality. Measured cost-to-finish-a-task lives on the real-cost index.
Related models
How to read GLM 4.5V's pricing
Two numbers decide most of the bill: $0.60/1M for input (everything you send — prompt, context, attachments) and $1.80/1M for output (everything it generates, including hidden reasoning tokens). Output is priced 3.0× the input rate here, so the shape of your workload — how much it reads versus writes — matters as much as the headline figure. This row is OpenRouter's routed market price; it can move as providers and routing change.
Frequently asked questions
How much does GLM 4.5V cost per million tokens?
GLM 4.5V is priced at $0.60 per 1M input tokens and $1.80 per 1M output tokens, from OpenRouter's routed market price as of the 2026-06-15 snapshot. Output is the figure that usually drives the bill. Enter your own token volumes in the cost calculator for a monthly estimate.
What is GLM 4.5V's context window?
GLM 4.5V has a 66K-token context window — roughly 98 pages of text. Prompt, attachments, conversation and the model's own output all share that budget, and every token you send is billed at the input rate.
Related
- API cost calculator — your monthly cost for GLM 4.5V and every other model.
- Model comparison — the full sortable table.
- Price history — how token prices move over time.
- LLM pricing explained — input, output, cached and reasoning tokens.