Speed
Output tokens / second
GLM-4.5 Air overview
GLM-4.5 Air by Zhipu AI
By delivering nearly flagship-level performance with significantly reduced active parameter counts and memory requirements.
GLM-4.5 Air specs
- Model ID
zhipu/glm-4.5-air- Developer
- Zhipu AI
- Context window
- 128,000 tokens
- Max output
- 98,000 tokens
- Input
- Text
- Output
- Text
- API
- OpenAI-compatible, base URL
https://api.aimlapi.com/v1
Zhipu AI’s GLM-4.5-Air is a highly efficient, cost-effective large language model built with 106 billion total parameters (12 billion active) using a Mixture-of-Experts (MoE) design. Tailored for a broad spectrum of text-to-text applications, it matches the full GLM-4.5’s 128,000-token context window, enabling comprehension and generation of very long-form text while dramatically reducing computational overhead.
Performance Benchmarks
- Context Window: 128,000 tokens
- Ranked 6th overall on 12 industry benchmarks, with a 59.8 average score
- Reasoning: MMLU-Pro 81.4%, AIME24 89.4%, Math 98.1%; solid coding
Performance Metrics
GLM-4.5-Air is engineered for agentic applications, offering a 128,000-token context window and built-in function execution capabilities. On agentic benchmarks such as τ-bench and BFCL-v3, it attains results nearly equivalent to Claude 4 Sonnet. In specialized tests for web browsing (BrowseComp), which assess complex multi-step reasoning and tool use, GLM-4.5-Air achieves a 26.4% accuracy rate, outperforming Claude-4-Opus (18.8%) and approaching the leading o4-mini-high at 28.3%. These results underscore GLM-4.5-Air’s balanced performance in real-world, tool-driven tasks and agent scenarios.
Key Capabilities
- Advanced Text Generation: Fluent, contextually precise outputs for long-form and multi-turn dialogue.
- Efficient Agentic Reasoning: Maintains strong coding, reasoning, and tool-use ability in both “thinking” (complex) and “non-thinking” (instant response) modes.
- Resource Efficiency: Requires far less GPU memory (deployable on 16GB GPUs), making it excellent for real-world, hardware-constrained environments.
- Competitive on practical development and agent tasks, with rapid code suggestion and document analysis.
Comparison with Other Models
Vs. Claude 4 Sonnet: GLM-4.5-Air offers a competitive balance of efficiency and performance but is slightly behind Claude 4 Sonnet in coding and agentic reasoning tasks. Claude 4 Sonnet supports a larger context window (200k tokens vs. 128k) and includes image input capabilities, making it more suitable for multimodal applications. However, GLM-4.5-Air is open-source, more cost-effective, and provides strong reliability across function calling and multi-turn reasoning.
Vs. GLM-4.5: GLM-4.5-Air achieves about 80-98% of the flagship GLM-4.5’s performance, with significantly fewer active parameters (12B vs. 32B) and reduced resource requirements. While it slightly trails in raw task accuracy, it maintains solid reasoning, coding, and agentic capabilities, making it better suited for deployment in hardware-constrained environments.
Vs. Qwen3-Coder: GLM-4.5-Air competes well with Qwen3-Coder in coding and tool use, delivering fast and accurate code generation for complex programming tasks. GLM-4.5-Air demonstrates dominant success rates and reliable tool calling mechanisms over Qwen3-Coder.
Vs. Gemini 2.5 Pro: GLM-4.5-Air holds close on practical reasoning and coding benchmarks against Gemini 2.5 Pro. While Gemini may excel slightly in some coding and reasoning tests, GLM-4.5-Air offers a favorable balance of large context window and agentic tooling optimized for efficient real-world deployments.
Limitations
- Slightly reduced overall performance and number of active parameters compared to GLM-4.5 flagship
- Some complex tasks show minor drops, but core text and code abilities remain robust
- Not ideal for organizations needing absolute state-of-the-art accuracy above all else
- “Full” context and tool-support requires new infrastructure for best efficiency
Use cases
- Cost-Effective Conversational AI: Supports high-volume, low-latency chatbots and virtual assistants.
- Lightweight Coding Assistance: Real-time code completion, debugging, and documentation generation.
- Complex Document Analysis: Legal, scientific, and business text at scale.
- Mobile & Edge Deployments: Effective for environments with limited hardware resources.
- Agentic Tools: Tool-using agents, web browsing, and batch content transformation.
Capabilities
- Function calling
- Streaming
- Structured outputs
- Reasoning
- Web search
GLM-4.5 Air benchmarks by 
Artificial Analysis
See how GLM-4.5 Air compares in generation speed and latency. Data retrieved Nov 3, 2026.
Benchmark results
Compare 13 models available on AI/ML API across 5 independent benchmarks.
Humanity's Last Exam
Expert-written questions across academic subjects.
GPQA Diamond
Graduate-level science questions written to resist web search.
AA-LCR
Reasoning across long documents of about 100k tokens.
IFBench
Following precise instructions about the shape of the answer.
τ²-Bench Telecom
Customer support agent tasks with tool calls.
GLM-4.5 Air API pricing
| Usage | Price | Unit |
|---|---|---|
| Input | $0.2 | 1M tokens |
| Output | $1.1 | 1M tokens |
| Cached input | $0.03 | 1M tokens |
Prices from the AI/ML API price list, checked on Nov 4, 2026.
GLM-4.5 Air vs other models: token prices
AI/ML API input and output rates for 5 models, per million tokens.
| Model | Input | Output |
|---|---|---|
 GLM-4.5 Air | $0.2 | $1.1 |
| GLM-5.3-Flash | $0.15 | $0.5 |
| GLM 5.3 FlashX | $0.37 | $1.25 |
| GLM-5.3 | $1.4 | $4.4 |
| GLM 5.2 Fast Preview | $3.5 | $11 |
How to use the GLM-4.5 Air API
View docs
Build with your agent
Give your agent the model details, code and documentation.
Paste it into your coding agent to build the integration.
1Get your API key
Create API keyexport AIMLAPI_KEY="8f2b4c7d9a1e6b3f…"2Make your first request
curl 'https://api.aimlapi.com/v1/chat/completions' \
-H "Authorization: Bearer $AIMLAPI_KEY" \
-H 'Content-Type: application/json' \
-d '{
"model": "zhipu/glm-4.5-air",
"messages": [
{
"role": "user",
"content": "Write a haiku about the ocean."
}
]
}'import os
import requests
headers = {
"Authorization": f"Bearer {os.environ['AIMLAPI_KEY']}",
"Content-Type": "application/json",
}
payload = {
"model": "zhipu/glm-4.5-air",
"messages": [
{
"role": "user",
"content": "Write a haiku about the ocean."
}
]
}
response = requests.post("https://api.aimlapi.com/v1/chat/completions", headers=headers, json=payload, timeout=120)
response.raise_for_status()
print(response.json())const response = await fetch("https://api.aimlapi.com/v1/chat/completions", {
method: "POST",
headers: {
Authorization: `Bearer ${process.env.AIMLAPI_KEY}`,
"Content-Type": "application/json",
},
body: JSON.stringify({
"model": "zhipu/glm-4.5-air",
"messages": [
{
"role": "user",
"content": "Write a haiku about the ocean."
}
]
}),
});
if (!response.ok) throw new Error(`HTTP ${response.status}`);
console.log(await response.json());Models similar to GLM-4.5 Air
Related articles
GLM-4.5 Air FAQ
What is the context window of GLM-4.5 Air?
GLM-4.5 Air has a 128,000 tokens context window and can return up to 98,000 tokens.
What inputs and outputs does GLM-4.5 Air support?
GLM-4.5 Air takes text as input and returns text.
What is the model ID for GLM-4.5 Air?
Use zhipu/glm-4.5-air as the model id. Requests go to https://api.aimlapi.com/v1/chat/completions.
When was GLM-4.5 Air released?
GLM-4.5 Air became available on September 9, 2025.
How much does GLM-4.5 Air cost?
GLM-4.5 Air costs $0.2 input and $1.1 output per 1M tokens on AI/ML API, billed as you go with no subscription.
Does GLM-4.5 Air support streaming?
Yes, GLM-4.5 Air can stream responses as they are generated.
Who created GLM-4.5 Air?
GLM-4.5 Air was built by Zhipu AI.
Can GLM-4.5 Air call external tools or functions?
Yes, it supports function calling, parallel tool calls, and structured output as part of its tool use capabilities.