Z.ai · Open weights
GLM 4.5 Air
GLM-4.5-Air is a 106B total / 12B active parameter model designed to unify frontier reasoning, coding, and agentic capabilities. On the SWE-bench Verified benchmark, it delivers the best performance at its scale with a competitive performance-to-cost ratio.
- Tools
- Structured output
- Input
- Text
- Output
- Text
- Discovery tier
- Open weights
Pricing
USD per 1M tokens- Input
- $0.13
- Output
- $0.85
- Cache read
- $0.025
Reference prices as published by the model provider. API example
Specifications
- Context window
- 128K
- Max output
- 98.3K
- Average output (7 days)
- 59 tokens
- Longer than 5% of 465 models
Side by side
GLM 4.5 Air compared
Specifications, prices, speed and benchmark scores next to each other. Benchmarks below show every compared model too.
| GLM 4.5 AirZ.aiThis model | Qwen3 Next 80B A3B (Thinking)QwenRemove | |
|---|---|---|
| Provider | Z.ai | Qwen |
| Discovery tier | Open weights | Open weights |
| Added | Apr 15, 2025 | Jan 1, 2024 |
| Limits | ||
| Context window | 128K | 256KBest |
| Max output | 98.3KBest | 32.77K |
| Average output | 59 tokens | — |
| Pricing, USD per 1M tokens | ||
| Input | $0.13Best | $0.15 |
| Output | $0.85 | $0.65Best |
| Cache read | $0.025 | — |
| Performance | ||
| Throughput | 89.9 tok/s | — |
| Time to first token | 1.6 s | — |
| Request success (24h) | 100.0% | — |
| Benchmark indexes | ||
| Intelligence Index | 11.1 | 11.2Best |
| Coding Index | — | 17.4 |
| Math Index | 80.7 | 84.3Best |
| Capabilities | ||
| Tools | Yes | No |
| Structured output | Yes | No |
| Reasoning effort | — | — |
Public evaluations
Benchmarks
Independent evaluation results, with how each score ranks among the models in the Noumen catalog.
- GLM 4.5 Air
- Qwen3 Next 80B A3B (Thinking)
Intelligence Index
- GLM 4.5 Air11.1
- Qwen3 Next 80B A3B (Thinking)11.2
GLM 4.5 Air: Better than 23% of 326 scored models
Indexes
Coding Index
Composite of the coding evaluations
- GLM 4.5 Air: —
- Qwen3 Next 80B A3B (Thinking): 17.4
Math Index
Composite of the math evaluations
- GLM 4.5 Air: 80.7
- Qwen3 Next 80B A3B (Thinking): 84.3Top
Agentic work
GDPval-AAv2.1
Economically valuable occupational tasks, rated head to head
- GLM 4.5 Air: —
- Qwen3 Next 80B A3B (Thinking): 128 Elo
Document reasoning
AA-LCRv1.1
Reasoning across long documents
- GLM 4.5 Air: 46.7%
- Qwen3 Next 80B A3B (Thinking): 63.7%Top
Reasoning and knowledge
Humanity’s Last Exam
Expert-level questions across academic fields
- GLM 4.5 Air: 7.0%
- Qwen3 Next 80B A3B (Thinking): 12.6%Top
GPQA Diamond
Graduate-level science questions
- GLM 4.5 Air: 73.3%
- Qwen3 Next 80B A3B (Thinking): 75.9%Top
MMLU-Pro
Multi-subject knowledge and reasoning
- GLM 4.5 Air: 81.5%
- Qwen3 Next 80B A3B (Thinking): 82.4%Top
IFBench
Following precise output instructions
- GLM 4.5 Air: 37.6%
- Qwen3 Next 80B A3B (Thinking): 60.7%Top
Coding
LiveCodeBench
Recent competitive programming problems
- GLM 4.5 Air: 68.4%
- Qwen3 Next 80B A3B (Thinking): 78.4%Top
Math
AIME 2025
Competition mathematics, 2025 problems
- GLM 4.5 Air: 80.7%
- Qwen3 Next 80B A3B (Thinking): 84.3%Top
AIME
Competition mathematics
- GLM 4.5 Air: 67.3%
- Qwen3 Next 80B A3B (Thinking): —
MATH-500
Competition math problems
- GLM 4.5 Air: 96.5%
- Qwen3 Next 80B A3B (Thinking): —
Legacy evaluations
Terminal-Bench Hard
Earlier terminal task suite
- GLM 4.5 Air: 20.5%Top
- Qwen3 Next 80B A3B (Thinking): 9.8%
τ²-Bench Telecom
Tool use in a customer-support simulation
- GLM 4.5 Air: 46.5%Top
- Qwen3 Next 80B A3B (Thinking): 41.5%
AA-LCR (unversioned)
Long-context reasoning, earlier grading
- GLM 4.5 Air: 46.7%
- Qwen3 Next 80B A3B (Thinking): 63.7%Top
Scores from Artificial Analysis, updated Oct 26, 2026. Artificial Analysis
Live routing data
Performance and reliability
Recent averages across requests routed for this model. Your own speed depends on prompt length, reasoning effort and load.
- Throughput
- 89.9 tok/s
- Faster than 57% of 251 models
- Time to first token
- 1.6 s
- Quicker than 85% of 251 models
- Prompt cache hits
- 40.6%
- About $0.0873 per 1M input tokens with caching
- Request success (24h)
- 100.0%
- Reliable
Cache hits are the share of input tokens recently served from a prompt cache across all requests. They are not a forecast of your own hit rate.
- Healthy (98% or more)
- Degraded (90–98%)
- Down (under 90%)
- No requests
Developers
Use it through the API
Noumen’s API is OpenAI-compatible: any Chat Completions client works with a base URL and a key.
curl https://www.noumen.xyz/api/v1/chat/completions \
-H "Authorization: Bearer $NOUMEN_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"model": "z-ai/GLM-4.5-Air",
"messages": [{ "role": "user", "content": "Explain this stack trace." }]
}'import os
from openai import OpenAI
client = OpenAI(base_url="https://www.noumen.xyz/api/v1", api_key=os.environ["NOUMEN_API_KEY"])
reply = client.chat.completions.create(
model="z-ai/GLM-4.5-Air",
messages=[{"role": "user", "content": "Explain this stack trace."}],
)
print(reply.choices[0].message.content)Z.ai
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