per 1M tokens
GLM 4.6V
novita/zai-org/glm-4.6v
GLM-4.6V represents a significant multimodal advancement in the GLM series, featuring a 128k-token training context window and achieving state-of-the-art visual understanding accuracy for models of its parameter scale. Notably, it's the first visual model to natively integrate Function Call capabilities directly into its architecture, creating a seamless pathway from visual perception to executable actions. This breakthrough establishes a unified technical foundation for deploying multimodal agents in real-world business applications.
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.
$1.20 at list price for this workload
Cache
per 1M tokens
Every rate
| Unit | Input | Output | Flat | Confidence |
|---|---|---|---|---|
| token | $0.3/1M | $0.9/1M | Not published— | official |
Price history
input or flat output
Daily snapshots
| UTC date | Unit | Input | Output | Flat |
|---|---|---|---|---|
| 2026-10-08 | token | $0.3 | $0.9 | Not published— |
| 2026-10-09 | token | $0.3 | $0.9 | Not published— |
| 2026-10-10 | token | $0.3 | $0.9 | Not published— |
| 2026-10-11 | token | $0.3 | $0.9 | Not published— |
| 2026-10-12 | token | $0.3 | $0.9 | Not published— |
| 2026-10-13 | token | $0.3 | $0.9 | Not published— |
| 2026-10-14 | token | $0.3 | $0.9 | Not published— |
| 2026-10-15 | token | $0.3 | $0.9 | Not published— |
| 2026-10-16 | token | $0.3 | $0.9 | Not published— |
| 2026-10-17 | token | $0.3 | $0.9 | Not published— |
| 2026-10-18 | token | $0.3 | $0.9 | Not published— |
| 2026-10-19 | token | $0.3 | $0.9 | Not published— |
| 2026-10-20 | token | $0.3 | $0.9 | Not published— |
| 2026-10-21 | token | $0.3 | $0.9 | Not published— |
| 2026-10-22 | token | $0.3 | $0.9 | Not published— |
| 2026-10-23 | token | $0.3 | $0.9 | Not published— |
| 2026-10-24 | token | $0.3 | $0.9 | Not published— |
| 2026-10-25 | token | $0.3 | $0.9 | Not published— |
| 2026-10-26 | token | $0.3 | $0.9 | Not published— |
| 2026-10-27 | token | $0.3 | $0.9 | Not published— |
| 2026-10-28 | token | $0.3 | $0.9 | Not published— |
| 2026-10-29 | token | $0.3 | $0.9 | Not published— |
| 2026-10-30 | token | $0.3 | $0.9 | Not published— |
Alternatives
- @cf/deepseek-ai/deepseek-v4.1-flash-1017$0.3/1M · Compare
- @cf/moondream/moondream3.1-9B-A2B$0.3/1M · Compare
- Amazon: Nova 2 Lite$0.3/1M · Compare
- Cohere: Command A+$0.3/1M · Compare
- DeepSeek V4.1 Flash$0.3/1M · Compare
- DeepSeek V4.1 Flash$0.3/1M · Compare
Call this model
OpenRouter id novita/zai-org/glm-4.6v. 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-4.6v","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-4.6v",
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-4.6v", "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())