z-ai/glm-4.7-flash
202,752 context · $0.06/M input tokens · $0.40/M output tokens
As a 30B-class SOTA model, GLM-4.7-Flash offers a new option that balances performance and efficiency. It is further optimized for agentic coding use cases, strengthening coding capabilities, long-horizon task planning, and tool collaboration, and has achieved leading performance among open-source models of the same size on several current public benchmark leaderboards.
Pay-per-Use
Keine Vorabkosten, zahlen Sie nur, was Sie nutzen
Verwenden Sie die folgenden Codebeispiele zur Integration mit unserer API:
from openai import OpenAI
client = OpenAI(
api_key="YOUR_API_KEY",
base_url="https://llm.wavespeed.ai/v1"
)
response = client.chat.completions.create(
model="z-ai/glm-4.7-flash",
messages=[
{"role": "user", "content": "Hello!"}
]
)
print(response.choices[0].message.content)As a 30B-class SOTA model, GLM-4
As a 30B-class SOTA model, GLM-4.7-Flash offers a new option that balances performance and efficiency. It is further optimized for agentic coding use cases, strengthening coding capabilities, long-horizon task planning, and tool collaboration, and has achieved leading performance among open-source models of the same size on several current public benchmark leaderboards.
| Specification | Value |
|---|---|
| Provider | Z-Ai |
| Model Type | Large Language Model (LLM) |
| Architecture | N/A |
| Context Window | 202752 tokens |
| Max Output | tokens |
| Input | Text |
| Output | Text |
| Vision | Supported |
| Function Calling | Supported |
| Token Type | Cost per Million Tokens |
|---|---|
| Input | $0.1 |
| Output | $0.4 |
Base URL: https://llm.wavespeed.ai/v1 API Endpoint: chat/completions Model ID: z-ai/glm-4.7-flash
from openai import OpenAI
client = OpenAI(
api_key="YOUR_API_KEY",
base_url="https://llm.wavespeed.ai/v1"
)
response = client.chat.completions.create(
model="z-ai/glm-4.7-flash",
messages=[
{"role": "user", "content": "Hello!"}
]
)
print(response.choices[0].message.content)
curl https://llm.wavespeed.ai/v1/chat/completions \
-H "Content-Type: application/json" \
-H "Authorization: Bearer YOUR_API_KEY" \
-d '{
"model": "z-ai/glm-4.7-flash",
"messages": [{"role": "user", "content": "Hello!"}]
}'
z-ai/glm-4.7-flash
As a 30B-class SOTA model, GLM-4.7-Flash offers a new option that balances performance and efficiency. It is further optimized for agentic coding use cases, strengthening coding capabilities, long-horizon task planning, and tool collaboration, and has achieved leading performance among open-source models of the same size on several current public benchmark leaderboards.
Eingabe
$0.06 /M
Ausgabe
$0.4 /M
Kontext
203K
Tool-Nutzung
Unterstützt
Zugriff auf GLM 4.7 Flash über unsere einheitliche API — OpenAI-kompatibel, keine Kaltstarts, transparente Preise.
Preise auf WaveSpeedAI: $0.06 pro Million Input-Tokens und $0.40 pro Million Output-Tokens. Prompt-Caching und Batch-Verarbeitung werden separat berechnet und reduzieren die effektiven Kosten bei langen, sich wiederholenden Workloads.
GLM 4.7 Flash unterstützt bis zu 203K Kontext-Tokens und bis zu — Output-Tokens pro Anfrage.
Ja. WaveSpeedAI stellt GLM 4.7 Flash über einen OpenAI-kompatiblen Endpunkt unter https://llm.wavespeed.ai/v1 bereit. Richten Sie das offizielle OpenAI SDK mit Ihrem WaveSpeedAI-API-Schlüssel auf diese Base-URL — keine weiteren Codeänderungen erforderlich.
Bei WaveSpeedAI anmelden, in Access Keys einen API-Schlüssel erstellen und eine Anfrage an https://llm.wavespeed.ai/v1/chat/completions mit der oben angezeigten Model-ID senden. Neue Konten erhalten kostenlose Credits, um GLM 4.7 Flash zu testen.