GLM 5.3
Flagship GLM model for long-horizon coding, agents, and complex project delivery
- Released
- Aug 14 2026
- Modality
- Text
- Context
- 1M tokens
- Price in / cached input / out
- $1.35 / $0.26 / $4.25per 1M tokens
Quickstart
OpenAI-compatible: change the base URL, and the setup is complete.
from openai import OpenAI
import os
client = OpenAI(
base_url="https://api.you.com/v1",
api_key=os.environ["YOU_API_KEY"],
)
response = client.chat.completions.create(
model="glm-5.3",
messages=[{"role": "user", "content": "Summarize this support ticket in two sentences."}],
)
print(response.choices[0].message.content)Specifications
Technical details, capabilities, pricing, and data handling.
Model info
- Input Modality
- Text
- Output Modality
- Text
- Context Window
- 1M
- License
- GLM-5.3 License
Capabilities
- Reasoning
- Supported
- Function calling
- Supported
- Structured outputs
- Supported
- Web search grounding
- Not supported
Pricing
- Input
- $1.35
- Cached input
- $0.26
- Output
- $4.25
Data handling
- Zero data retention
- Supported
- No training on customer data
- Supported
- Regions
- US
Providers
Access models through multiple providers with automatic routing and built-in failover.
| Provider | ZDR | No training | Region |
|---|---|---|---|
| You Inference | Yes | Yes | US |
| Parasail | Yes | Yes | US |
| Wafer | Yes | Yes | US |
When to use GLM 5.3
Guidance based on the specifications and benchmarks on this page.
Best for
- Complex, long-horizon agentic codingZ.ai calls GLM-5.3 its most capable open-weights coding model, 50% better than GLM-5.2 on its in-house Code Bench.
- Security research and vulnerability discoveryZ.ai reports state-of-the-art results on CyberGym (84.5%) and more than double GLM-5.2 on exploitation benchmarks.
- Tool-driven automation workflowsScores 73.0% on Toolathlon Verified and 62.5% on Humanity's Last Exam with tools.
Consider alternatives for
- You need image understandingGLM-5.3 is text-only; Z.ai's GLM-5.3 Flash is its first natively multimodal GLM-5 model.
- You need a lighter modelGLM-5.3 Flash is Z.ai's smaller sibling, with 320B total / 18B active parameters.
- You need top repository-generation scoresOn NL2Repo, Z.ai's own table shows Opus 4.8 well ahead (69.7% vs 58.0%).
Benchmarks
GLM 5.3 results alongside comparable models
| Benchmark | GLM 5.3Z.ai | DeepSeek V4.1 FlashDeepSeek | Qwen3.8 MaxAlibaba | Kimi K3Moonshot AI | Muse Spark 1.3Meta | DeepSeek V4 ProDeepSeek |
|---|---|---|---|---|---|---|
| Humanity's Last Exam (with tools) | 62.5% | 63.9% | 56.2% | 56% | Not evaluated | 48.2% |
Scores are self-reported by each model’s developer, so settings may vary between models. Sources: GLM 5.3 (Hugging Face), DeepSeek V4.1 Flash (Hugging Face), Qwen3.8 Max (Hugging Face), Qwen3.8 Max (release post), Kimi K3 (Hugging Face), Muse Spark 1.3 (release post), DeepSeek V4 Pro (Hugging Face).
Give GLM 5.3 access to the live web
Ground responses with fresh web information and cited sources using You.com Search, without changing models or adding another integration.
What error do I get installing psycopg2 on Python 3.13?
LLM + You.com Web Search
psycopg2 on Python 3.13
Short answer:
psycopg2 installs fine today. 2.9.10 added 3.13 support in Oct 2024. 12
The error you hit is almost certainly missing build step:
pg_config executable not found
Fix:
pip install -U psycopg2-binary
LLM (LLM only)
When trying to install psycopg2 on Python 3.13, you will most likely hit one of these errors:
1. No pre-built wheel available
pip cannot find a binary wheel because the psycopg2 project hasn’t yet published wheels for Python 3.13.
What you should do
Downgrade Python — use Python 3.12 or earlier until psycopg2 officially supports 3.13.
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