Z.ai's flagship coding and security specialist — open weights, 1M context, and emergent cyber capabilities via post-training.
curl https://api.venice.ai/api/v1/chat/completions \
-H "Authorization: Bearer $VENICE_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"model": "e2ee-glm-5-3-p",
"messages": [{ "role": "user", "content": "Build without permission." }]
}'Overview
GLM 5.3 is Z.ai's flagship large language model, released on August 14, 2026. It uses the same 744B-parameter base as GLM-5.2, with all improvements from scaled post-training. It excels in coding, agent tasks, and cybersecurity, offering a 1M-token context window and open weights under a permissive license.
On Venice, GLM 5.3 runs with full privacy: zero retention, end-to-end encryption, and execution in a Trusted Execution Environment (TEE). You get uncensored access to its full capabilities — including tool use, web search, and code reasoning — without your prompts being stored or profiled. This is sovereign AI: open, private, and permissionless.
Agent quickstart
The API is OpenAI-compatible: change the base URL and the model id and existing client code works unchanged.
curl https://api.venice.ai/api/v1/chat/completions \
-H "Authorization: Bearer $VENICE_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"model": "e2ee-glm-5-3-p",
"stream": true,
"messages": [{ "role": "user", "content": "Draft the release note." }]
}'curl https://api.venice.ai/api/v1/chat/completions \
-H "Authorization: Bearer $VENICE_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"model": "e2ee-glm-5-3-p",
"messages": [{ "role": "user", "content": "Find the rate limits." }],
"tools": [{
"type": "function",
"function": {
"name": "search_docs",
"description": "Search the API documentation.",
"parameters": {
"type": "object",
"properties": { "query": { "type": "string" } },
"required": ["query"]
}
}
}],
"tool_choice": "auto"
}'import os
from openai import OpenAI
client = OpenAI(
api_key=os.environ["VENICE_API_KEY"],
base_url="https://api.venice.ai/api/v1",
)
resp = client.chat.completions.create(
model="e2ee-glm-5-3-p",
messages=[{"role": "user", "content": "Build without permission."}],
)
print(resp.choices[0].message.content)Specifications
Assessment
Use cases
Prompting
Use explicit JSON formatting in prompts when expecting structured output.
Leverage web search mode for up-to-date code documentation or API references.
Break down complex coding tasks into step-by-step reasoning chains.
Use function calling syntax to integrate external tools or databases.
For long inputs, ensure critical context is near the beginning to mitigate attention decay.
Enable reasoning mode for multi-step problem solving and debugging.
Alternatives
| Model | Best for | Context | Open weights | Price (Venice) |
|---|---|---|---|---|
| GLM 5.3 | Coding & security | 1M tokens | Yes | $1.75 in · $5.50 out / 1M |
| Claude Fable 5.1 | Hard coding & reasoning | 1M tokens | No | $12 in · $60 out / 1M |
| DeepSeek V4 Flash 0731 | Speed & cost | 1M tokens | Yes | $0.17 in · $0.35 out / 1M |
| Gemini 3.8 Flash | Low-latency tasks | 1M tokens | No | $0.94 in · $4.69 out / 1M |
GLM 5.3 is the right pick for developers and security researchers who need open, private, and high-performance coding AI — especially when long context and tool integration are critical.
Pricing
Billed per token on Venice: $1.75 per 1M input tokens and $5.50 per 1M output tokens.
New Venice accounts include a free daily allowance and 500 welcome credits — no credit card required.
Getting a key
Create a key in API settings. Nothing else is required to start.
Export it as VENICE_API_KEY so the snippets above run unedited.
Point an existing OpenAI client at https://api.venice.ai/api/v1. The scheme is part of the value: an OpenAI client given a bare host does not resolve it.
Pass e2ee-glm-5-3-p as the model and send the request.
FAQ
GLM 5.3 is Z.ai's flagship large language model, released on August 14, 2026. It uses the same base as GLM-5.2 but gains all improvements from post-training, excelling in coding, agent tasks, and cybersecurity with a 1M-token context and open weights.
On Venice, GLM 5.3 costs $1.75 per 1M input tokens and $5.50 per 1M output tokens. Cached input is $0.33 per 1M tokens. Pricing is transparent and per-token, with no subscription required.
GLM 5.3 is not free but is open weights under the permissive GLM-5.3 License. You can use, modify, distribute, and fine-tune the model, though commercial Model-as-a-Service over $10B revenue requires a security review.
Yes, GLM 5.3 supports tool use and function calling, enabling integration with external tools, databases, and APIs for agent workflows and automation.
GLM 5.3 has a 1,000K-token context window, allowing it to process extremely long documents, codebases, or conversation histories in a single session.
No, GLM 5.3 is text-only and does not support image or multimodal input. For vision tasks, consider Kimi K3 or other multimodal models on Venice.
GLM 5.3 is better for private, cost-effective coding and security work with open weights. Claude Fable 5.1 leads in independent coding benchmarks but is closed, more expensive, and not yet on Venice.
One key, free to start, no credit card.