Chat Models

AI models for chat, Q&A, reasoning, and text generation

7 models15 makersData through Sep 16, 2026

Chat · Zhipu AI

Type

All7 Chat7

Model maker

Capabilities

All7Tool use7Prompt Cache7JSON mode4Vision2Code1Reasoning1

Model count

glm-5.3

Available

CodeJSON modePrompt CacheReasoningTool useCached input 75% less

TokenLab price/ Official price: Input$1.18
Output$4.12
/1M

glm-5.3-flash

Available

JSON modePrompt CacheTool useVisionCached input 80% less

TokenLab price/ Official price: Input$0.15
Output$0.50
/1M

glm-5v-turbo

Available

JSON modePrompt CacheTool useVisionCached input 80% less

TokenLab price/ Official price: Input$1.20
Output$4.00
/1M

glm-5

Available

Prompt CacheTool useCached input 80% less

TokenLab price/ Official price: Input$1.00
Output$3.20
/1M

glm-5-turbo

Available

Prompt CacheTool useCached input 80% less

TokenLab price/ Official price: Input$1.20
Output$4.00
/1M

glm-5.1

Available

Prompt CacheTool useCached input 81% less

TokenLab price/ Official price: Input$1.40
Output$4.40
/1M

glm-5.2

Available

JSON modePrompt CacheTool useCached input 75% less

TokenLab price: Input$1.18
Output$4.12
/1M
Official price: Input$1.18
Output$4.12
/1M

Model	Context	Max output	Official price	TokenLab price	Discount
glm-5.3CodeJSON modePrompt CacheReasoningTool use	1M	128K	Input$1.18 Output$4.12 /1M	Input$1.18 Output$4.12 /1M	-
glm-5.3-flashJSON modePrompt CacheTool useVision	1M	128K	Input$0.15 Output$0.50 /1M	Input$0.15 Output$0.50 /1M	-
glm-5v-turboJSON modePrompt CacheTool useVision	205K	128K	Input$1.20 Output$4.00 /1M	Input$1.20 Output$4.00 /1M	-
glm-5Prompt CacheTool use	200K	128K	Input$1.00 Output$3.20 /1M	Input$1.00 Output$3.20 /1M	-
glm-5-turboPrompt CacheTool use	200K	128K	Input$1.20 Output$4.00 /1M	Input$1.20 Output$4.00 /1M	-
glm-5.1Prompt CacheTool use	200K	128K	Input$1.40 Output$4.40 /1M	Input$1.40 Output$4.40 /1M	-
glm-5.2JSON modePrompt CacheTool use	1M	128K	Input$1.18 Output$4.12 /1M	Input$1.18 Output$4.12 /1M	-

All model series

1 series

GLM

Zhipu AI

ChatVisionCode+1

7 modelsOpen series

Choosing the right chat model

The right model balances task fit, output quality, latency, and price.

Selection signals

Match the model to the input and output you actually need.
Compare models that use the same pricing unit.
A small test reveals quality and latency differences that a catalog cannot.

FAQ

What makes a good chat model?

A strong fit matches the task, quality bar, latency target, and budget. A small evaluation set makes quality and reliability differences easier to see.

Can I switch models later?

Yes. Keep the public model ID and request format explicit, and compare alternatives on the same tasks.

Model rankings Compare models

Model count

All model series

GLM

Choosing the right chat model

Selection signals

FAQ

What makes a good chat model?

Can I switch models later?

Related pages