Z.ai · Open weights
GLM 5.2
GLM-5.2 is Z.AI's flagship model for long-horizon autonomous coding and engineering workflows. It is built to plan, execute, iterate, and optimize complex development tasks over extended runs. This variant keeps thinking disabled for faster direct responses.
- Reasoning
- Tools
- Structured output
- Input
- Text
- Output
- Text
- Reasoning effort
- none · high · max
- Discovery tier
- Open weights
Pricing
USD per 1M tokens- Input
- $0.42
- Output
- $1.32
- Cache read
- $0.078
Reference prices as published by the model provider. API example
Specifications
- Context window
- 1M
- Max output
- 131.1K
- Average output (7 days)
- 839 tokens
- Longer than 66% of 468 models
Side by side
GLM 5.2 compared
Specifications, prices, speed and benchmark scores next to each other. Benchmarks below show every compared model too.
| GLM 5.2Z.aiThis model | GLM 5.2 Thinking TEEZ.aiRemove | |
|---|---|---|
| Provider | Z.ai | Z.ai |
| Discovery tier | Open weights | Open weights |
| Added | Jun 15, 2026 | Jun 16, 2026 |
| Limits | ||
| Context window | 1.05M | 1.05M |
| Max output | 131.07K | 131.07K |
| Average output | 839 tokens | 2K tokens |
| Pricing, USD per 1M tokens | ||
| Input | $0.42Best | $1.40 |
| Output | $1.32Best | $4.40 |
| Cache read | $0.078Best | $0.70 |
| Performance | ||
| Throughput | 96.8 tok/s | — |
| Time to first token | 1.6 s | — |
| Request success (24h) | 99.6%Best | 87.5% |
| Benchmark indexes | ||
| Intelligence Index | 22.4 | 33.7Best |
| Coding Index | 46.5 | 68.8Best |
| Capabilities | ||
| Reasoning | Yes | Yes |
| Tools | Yes | Yes |
| Structured output | Yes | Yes |
| Reasoning effort | none, high, max | low, medium, high, xhigh, max |
Public evaluations
Benchmarks
Independent evaluation results, with how each score ranks among the models in the Noumen catalog.
- GLM 5.2
- GLM 5.2 Thinking TEE
Intelligence Index
- GLM 5.222.4
- GLM 5.2 Thinking TEE33.7
GLM 5.2: Better than 54% of 326 scored models
Indexes
Coding Index
Composite of the coding evaluations
- GLM 5.2: 46.5
- GLM 5.2 Thinking TEE: 68.8Top
Agentic work
AutomationBench-AA
Workflow automation, penalized for guardrail violations
- GLM 5.2: —
- GLM 5.2 Thinking TEE: 28.4%
AutomationBench-AA tasks completed
Workflows finished end to end without a guardrail violation
- GLM 5.2: —
- GLM 5.2 Thinking TEE: 6.2%
AA-Briefcasev1.1
Agentic knowledge work, rated head to head
- GLM 5.2: —
- GLM 5.2 Thinking TEE: 1,227 Elo
GDPval-AAv2.1
Economically valuable occupational tasks, rated head to head
- GLM 5.2: 1,244 Elo
- GLM 5.2 Thinking TEE: 1,373 EloTop
Document reasoning
GDP.pdf
Professional reasoning over PDF documents, all-pass rate
- GLM 5.2: —
- GLM 5.2 Thinking TEE: 10.4%
AA-LCRv1.1
Reasoning across long documents
- GLM 5.2: 42.3%
- GLM 5.2 Thinking TEE: 78.3%Top
MLCR-AA
Long-context reasoning over medical records
- GLM 5.2: —
- GLM 5.2 Thinking TEE: 12.8%
Reasoning and knowledge
Humanity’s Last Exam
Expert-level questions across academic fields
- GLM 5.2: 9.8%
- GLM 5.2 Thinking TEE: 41.1%Top
GPQA Diamond
Graduate-level science questions
- GLM 5.2: 68.6%
- GLM 5.2 Thinking TEE: 89.5%Top
IFBench
Following precise output instructions
- GLM 5.2: —
- GLM 5.2 Thinking TEE: 73.3%
Coding
Terminal-Benchv4.0
Practical software engineering in a terminal
- GLM 5.2: —
- GLM 5.2 Thinking TEE: 1.0%
SciCode
Scientific computing in Python
- GLM 5.2: —
- GLM 5.2 Thinking TEE: 51.2%
Legacy evaluations
Terminal-Bench Hard
Earlier terminal task suite
- GLM 5.2: —
- GLM 5.2 Thinking TEE: 50.8%
τ²-Bench Telecom
Tool use in a customer-support simulation
- GLM 5.2: —
- GLM 5.2 Thinking TEE: 99.1%
AA-LCR (unversioned)
Long-context reasoning, earlier grading
- GLM 5.2: 42.3%
- GLM 5.2 Thinking TEE: 78.3%Top
Scores from Artificial Analysis, updated Oct 26, 2026. Artificial Analysis
- GLM 5.2
- GLM 5.2 Thinking TEE
| Leaderboard | GLM 5.2 | GLM 5.2 Thinking TEE |
|---|---|---|
| EQ-Bench 4 | #17 · 1211 | Not in top 20 |
| EQ-Bench 3 | #6 · 1563 | Not in top 20 |
Ranks among Noumen catalog models on EQ-Bench leaderboards. Only top-20 placements are listed.EQ-Bench
- GLM 5.2
- GLM 5.2 Thinking TEE
| Leaderboard | GLM 5.2 | GLM 5.2 Thinking TEE |
|---|---|---|
| UI Component | #20 · 1291 | Not in top 20 |
| Data Visualization | #19 · 1285 | Not in top 20 |
| Agentic Game Dev | #8 · 1170 | Not in top 20 |
| Web Apps | #15 · 1223 | Not in top 20 |
| Full Stack | #11 · 1241 | Not in top 20 |
| Native Apps | #14 · 1181 | Not in top 20 |
Ranks among Noumen catalog models on Design Arena leaderboards. Only top-20 placements are listed.Design Arena
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
- 96.8 tok/s
- Faster than 62% of 253 models
- Time to first token
- 1.6 s
- Quicker than 87% of 253 models
- Prompt cache hits
- 66.4%
- About $0.19 per 1M input tokens with caching
- Request success (24h)
- 99.6%
- 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-5.2",
"reasoning_effort": "none",
"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-5.2",
messages=[{"role": "user", "content": "Explain this stack trace."}],
)
print(reply.choices[0].message.content)Z.ai
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