> ## Documentation Index
> Fetch the complete documentation index at: https://docs.apiyi.com/llms.txt
> Use this file to discover all available pages before exploring further.
# GLM-5.2 Launch: Zhipu's 1M-Context Flagship Coding Model
> Zhipu Z.AI's new flagship GLM-5.2 is live on APIYI via Alibaba Cloud's official authorized channel. 1M context, 744B MoE architecture, 81.0 on Terminal-Bench 2.1 and 62.1 on SWE-bench Pro, top open-weight score on the Artificial Analysis Intelligence Index. $1.142 input / $3.997 output per million tokens — stack recharge bonuses for ~85% of official pricing.
## Key Takeaways
* **1M context window**: Up from GLM-5.1's 200K to 1,000,000 tokens — large enough to hold project-level engineering context
* **Top open-weight intelligence score**: 51 on the Artificial Analysis Intelligence Index, the highest open-weight score
* **New coding high**: 81.0 on Terminal-Bench 2.1 and 62.1 on SWE-bench Pro, leading on long-horizon coding benchmarks
* **744B MoE architecture**: Continues the mixture-of-experts + dynamic sparse attention design with \~40B active parameters
* **Alibaba Cloud official authorized channel**: Live on APIYI via Alibaba Cloud's official relay partnership, pricing aligned to official rates — \$1.142 input / \$3.997 output per million tokens
## Background
In mid-June 2026, Zhipu Z.AI released its new flagship **GLM-5.2**, a major GLM-5 upgrade built for the era of long-horizon tasks. Released under the MIT license, it scores 51 on the Artificial Analysis Intelligence Index — currently the highest-scoring open-weight model.
The headline upgrade is the context window jump from GLM-5.1's \~200K to **1M tokens**. Zhipu stresses this is engineering-validated, stably sustaining long, messy coding-agent trajectories. In real-world tests, GLM-5.2 completed root-cause analysis across 740,000 server log lines and identified clause conflicts across four contract documents in a single session.
APIYI now offers `glm-5.2` via **Alibaba Cloud's official authorized channel (official relay partnership)**, callable in OpenAI-compatible mode, with pricing aligned to Alibaba Cloud's official rates.
## Deep Dive
### Core Features
1,000,000-token context window — load an entire repo, long logs, or multiple long documents at once
51 on the Artificial Analysis Intelligence Index, the highest open-weight score
81.0 on Terminal-Bench 2.1, 62.1 on SWE-bench Pro — leading open-weight long-horizon coding
744B MoE open-weight, commercial use permitted, deploy on-prem with full data control
### Performance Highlights
| Benchmark | GLM-5.2 | Notes |
| ------------------------------------------ | ----------- | ----------------------------------------------------------- |
| **Artificial Analysis Intelligence Index** | **51** | Highest open-weight score |
| **Terminal-Bench 2.1** | **81.0** | Leading open-weight terminal / coding-agent capability |
| **SWE-bench Pro** | **62.1** | Real repo-level coding tasks |
| **Long-horizon coding** | **Leading** | #1 open-weight on FrontierSWE, PostTrainBench, SWE-Marathon |
| **Context window** | **1M** | 5× larger than GLM-5.1's 200K |
Sources: Zhipu Z.AI official docs (`docs.bigmodel.cn`, `docs.z.ai`), Artificial Analysis (`artificialanalysis.ai`), VentureBeat. GLM-5.2 released mid-June 2026. Data retrieved June 18, 2026.
### Specifications
| Spec | GLM-5.2 |
| ------------------------ | --------------------------------------------------- |
| **Architecture** | MoE (mixture of experts) + dynamic sparse attention |
| **Total parameters** | \~744B |
| **Active parameters** | \~40B |
| **Context window** | 1,000,000 tokens |
| **Training data cutoff** | November 2025 |
| **License** | MIT License |
| **Model name** | `glm-5.2` |
## Use Cases
### Recommended Scenarios
1M context loads an entire codebase at once — ideal for large refactors and cross-file feature work
Leading open-weight long-horizon coding — a strong open alternative to Claude Code and Cursor
Spot clause conflicts across long documents, run root-cause analysis on massive logs in one pass
MIT-licensed open weights — download and self-host with full data control
### Code Examples
```python theme={null}
from openai import OpenAI
client = OpenAI(
api_key="your-api-key",
base_url="https://api.apiyi.com/v1"
)
response = client.chat.completions.create(
model="glm-5.2",
messages=[
{"role": "system", "content": "You are a senior software engineer skilled at project-level long-horizon coding."},
{"role": "user", "content": "Refactor this project's auth module using the full repository context."}
],
max_tokens=16384
)
print(response.choices[0].message.content)
```
```javascript theme={null}
import OpenAI from "openai";
const client = new OpenAI({
apiKey: "your-api-key",
baseURL: "https://api.apiyi.com/v1",
});
const response = await client.chat.completions.create({
model: "glm-5.2",
messages: [
{ role: "user", content: "Analyze these 700k server log lines and find the root cause." }
],
max_tokens: 16384,
});
console.log(response.choices[0].message.content);
```
### Best Practices
GLM-5.2 is built for long-horizon tasks. When handling very long context or long-running tasks, set a generous timeout (e.g. 600+ seconds) to fully use its 1M context.
* **Project-level coding**: Feed the full repo as context and let GLM-5.2 plan and execute the refactor
* **Long-document analysis**: Feed massive logs and multiple long documents at once for root-cause analysis and clause-conflict detection
* **On-prem deployment**: The MIT license lets enterprises self-host the weights with vLLM or SGLang for efficient inference
## Pricing & Availability
### Pricing
APIYI offers GLM-5.2 via **Alibaba Cloud's official authorized channel (official relay partnership)**, with pricing aligned to Alibaba Cloud's official rates (8 RMB / 28 RMB per million input / output tokens), converted to USD at our fixed 1:7 rate:
| Item | Price |
| ---------- | ------------------------ |
| **Input** | \$1.142 / million tokens |
| **Output** | \$3.997 / million tokens |
Billing type: pay-as-you-go (Chat). Input aligns to Alibaba Cloud's official 8 RMB and output 28 RMB per million tokens, converted to USD at our fixed 1:7 rate.
### Stack Recharge Bonuses
Our recharge bonus campaign is ongoing — stacking the recharge bonus easily brings you to **around 85% of Alibaba Cloud's official pricing**. The more you recharge, the bigger the bonus. See [Recharge Promotions](/en/faq/recharge-promotions) for details.
## Summary & Recommendations
GLM-5.2 is one of the strongest open-weight flagship models available today. Its 1M context plus 744B MoE architecture delivers excellent long-horizon coding and long-document handling, and it tops the open-weight field on the Artificial Analysis Intelligence Index. Live via Alibaba Cloud's official authorized channel with pricing aligned to official rates, it offers standout value once recharge bonuses are stacked.
**Recommended for**:
* Developers and teams needing 1M context for project-level coding and long-document analysis
* Users seeking a cost-effective open alternative to Claude Code / GPT-5.5
* Teams building long-horizon coding agents and autonomous workflows
* Enterprises needing on-prem deployment with full data control
Sources: Zhipu Z.AI official docs (`docs.bigmodel.cn`, `docs.z.ai`), Artificial Analysis (`artificialanalysis.ai`), VentureBeat. Data retrieved June 18, 2026. GLM-5.2 is released under the MIT license.