per 1M tokens
GLM 4.5V
novita/zai-org/glm-4.5v
Z.ai's GLM-4.5V sets a new standard in visual reasoning, achieving SOTA performance across 42 benchmarks among open-source models. Beyond benchmarks, it excels in real-world applications through hybrid training, enabling comprehensive visual understanding—from image/video analysis and GUI interaction to complex document processing and precise visual grounding. In China's GeoGuessr challenge, GLM-4.5V surpassed 99% of 21,000 human players within 16 hours, reaching 66th place in a week. Built on the GLM-4.5-Air foundation and inheriting GLM-4.1V-Thinking's approach, it leverages a 106B-parameter MoE architecture for scalable, efficient performance. This model bridges advanced AI research with practical deployment, delivering unmatched visual intelligence
Price
per 1M tokens
Providers
Each row is one seller. Prices are the published rate from that source. A dash means that source did not publish the amount. Sorted by a 3:1 blend of input and output.
No provider prices yet.
Monthly bill
Token models use the token counts. Image, video, and audio models use units times the flat rate.
$2.40 at list price for this workload
Cache
per 1M tokens
Every rate
| Unit | Input | Output | Flat | Confidence |
|---|---|---|---|---|
| token | $0.6/1M | $1.8/1M | Not published— | official |
Price history
input or flat output
Daily snapshots
| UTC date | Unit | Input | Output | Flat |
|---|---|---|---|---|
| 2026-10-08 | token | $0.6 | $1.8 | Not published— |
| 2026-10-09 | token | $0.6 | $1.8 | Not published— |
| 2026-10-10 | token | $0.6 | $1.8 | Not published— |
| 2026-10-11 | token | $0.6 | $1.8 | Not published— |
| 2026-10-12 | token | $0.6 | $1.8 | Not published— |
| 2026-10-13 | token | $0.6 | $1.8 | Not published— |
| 2026-10-14 | token | $0.6 | $1.8 | Not published— |
| 2026-10-15 | token | $0.6 | $1.8 | Not published— |
| 2026-10-16 | token | $0.6 | $1.8 | Not published— |
| 2026-10-17 | token | $0.6 | $1.8 | Not published— |
| 2026-10-18 | token | $0.6 | $1.8 | Not published— |
| 2026-10-19 | token | $0.6 | $1.8 | Not published— |
| 2026-10-20 | token | $0.6 | $1.8 | Not published— |
| 2026-10-21 | token | $0.6 | $1.8 | Not published— |
| 2026-10-22 | token | $0.6 | $1.8 | Not published— |
| 2026-10-23 | token | $0.6 | $1.8 | Not published— |
| 2026-10-24 | token | $0.6 | $1.8 | Not published— |
| 2026-10-25 | token | $0.6 | $1.8 | Not published— |
| 2026-10-26 | token | $0.6 | $1.8 | Not published— |
| 2026-10-27 | token | $0.6 | $1.8 | Not published— |
| 2026-10-28 | token | $0.6 | $1.8 | Not published— |
| 2026-10-29 | token | $0.6 | $1.8 | Not published— |
| 2026-10-30 | token | $0.6 | $1.8 | Not published— |
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Call this model
OpenRouter id novita/zai-org/glm-4.5v. InferenceList does not send the request.
curl
curl https://openrouter.ai/api/v1/chat/completions \
-H "Authorization: Bearer $OPENROUTER_API_KEY" \
-H "Content-Type: application/json" \
-d '{"model":"novita/zai-org/glm-4.5v","messages":[{"role":"user","content":"Hello"}]}'
JavaScript
await fetch("https://openrouter.ai/api/v1/chat/completions", {
method: "POST",
headers: {
Authorization: "Bearer " + process.env.OPENROUTER_API_KEY,
"Content-Type": "application/json",
},
body: JSON.stringify({
model: "novita/zai-org/glm-4.5v",
messages: [{ role: "user", content: "Hello" }],
}),
});
Python
import os, json, urllib.request
req = urllib.request.Request(
"https://openrouter.ai/api/v1/chat/completions",
data=json.dumps({"model": "novita/zai-org/glm-4.5v", "messages": [{"role": "user", "content": "Hello"}]}).encode(),
headers={"Authorization": "Bearer " + os.environ["OPENROUTER_API_KEY"], "Content-Type": "application/json"},
)
print(urllib.request.urlopen(req).read().decode())