bigmodel

GLM-4.7

bigmodel/glm-4.7
/v1/chat/completions/v1/messages/v1/responses/v1beta/models/*/v1/models/*

最新旗舰模型:通用对话、推理与智能体能力上实现全面升级。回复更简洁自然,写作更具沉浸感,且在工具调用时指令遵循更强,Artifacts 与 Agentic Coding 的前端美感和长程任务完成效率进一步提升

Input / output modalities
文本 to 文本
Reference input / output price
Input¥2Output¥8per 1M tokens
Context window
200K
Added to catalog
Dec 23, 2025

Providers and pricing

ProviderInput lengthInput /MOutput /MCached /MContextMax outputDetails
智谱≤ 32K¥2——200K128K
> 32K¥4——
≤ 2K—¥8—
≥ 2K—¥14—
≥ 0—¥16¥0.4
Ali≤ 32K¥3¥14¥0.6198K16K
≥ 32K¥4¥16¥0.8
Other-A≤ 32K¥2——200K16K
≥ 32K¥4——
≤ 2K—¥8—
≥ 2K—¥14—
≥ 0—¥16¥0.4

智谱

Latency
5.32s
Throughput
9 tokens/s
Context
200K

Pricing

Input
¥2/M tokens
Output
¥8/M tokens
Cached
¥0.4/M tokens

Tiered pricing

Pricing varies by input token range.

0–32K Token

Input tier
¥2/M tokens
Input tier
¥3/M tokens

32K–∞ Token

Input tier
¥4/M tokens

0–2K Token

Output tier
¥8/M tokens

2K–∞ Token

Output tier
¥14/M tokens

0–∞ Token

Output tier
¥16/M tokens
Cached tier
¥0.4/M tokens
Cached tier
¥0.6/M tokens
Cached tier
¥0.8/M tokens

Specifications

Context
200K
Max output
128K
Supported APIs
/v1/chat/completions/v1/messages/v1/responses/v1beta/models/*/v1/models/*

Ali

Latency
2.52s
Throughput
9431 tokens/s
Context
198K

Pricing

Input
¥3/M tokens
Output
¥14/M tokens
Cached
¥0/M tokens

Tiered pricing

Pricing varies by input token range.

0–32K Token

Input tier
¥3/M tokens
Output tier
¥14/M tokens
Cached tier
¥0.6/M tokens

32K–∞ Token

Input tier
¥4/M tokens
Output tier
¥16/M tokens
Cached tier
¥0.8/M tokens

Specifications

Context
198K
Max output
16K
Supported APIs
/v1/chat/completions/v1/messages/v1/responses/v1beta/models/*/v1/models/*

Other-A

Latency
1.29s
Throughput
92 tokens/s
Context
200K

Pricing

Input
¥2/M tokens
Output
¥8/M tokens
Cached
¥0.4/M tokens

Tiered pricing

Pricing varies by input token range.

0–32K Token

Input tier
¥2/M tokens
Input tier
¥3/M tokens

32K–∞ Token

Input tier
¥4/M tokens

0–2K Token

Output tier
¥8/M tokens

2K–∞ Token

Output tier
¥14/M tokens

0–∞ Token

Output tier
¥16/M tokens
Cached tier
¥0.4/M tokens
Cached tier
¥0.6/M tokens
Cached tier
¥0.8/M tokens

Specifications

Context
200K
Max output
16K
Supported APIs
/v1/chat/completions/v1/messages/v1/responses/v1beta/models/*/v1/models/*

GLM-4.7 code examples and API guide

Modelmesh normalizes requests and responses across service providers behind one consistent API.

Modelmesh provides an OpenAI-compatible Completion API for more than 300 models and service providers. Call it directly, through the OpenAI SDK, or with supported third-party SDKs.

Modelmesh-specific request headers in these examples are optional. When supplied, your application can appear on the Modelmesh rankings.

Supported endpointsSelect an endpoint to switch the example below.
/v1/chat/completions
from openai import OpenAI API_KEY = "$SSY_API_KEY" client = OpenAI( base_url="https://router.shengsuanyun.com/api/v1", api_key=API_KEY, ) try: completion = client.chat.completions.create( model="bigmodel/glm-4.7", messages=[{"role": "user", "content": "Which number is larger, 9.11 or 9.8?"}], temperature=0.6, top_p=0.7, stream=True, ) response_text = "" for chunk in completion: if chunk.choices and chunk.choices[0].delta.content is not None: content = chunk.choices[0].delta.content print(content, end="", flush=True) response_text += content except Exception as error: print(f"Request failed: {error}")
                
              

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