GLM 5.3 Flash
Z.ai's first natively multimodal GLM-5 model — 320B parameters with 18B active, 1M context, MIT-licensed, and built for coding and agentic workflows at flash cost.
Overview
What is GLM 5.3 Flash
GLM 5.3 Flash is Z.ai's first natively multimodal large language model in the GLM-5 series, released on August 26, 2026. With 320B total parameters and 18B active, it delivers frontier-level intelligence at a fraction of the cost, supports vision, video, and code-optimized reasoning, and features a 1M-token context window.
Running it privately on Venice
On Venice, GLM 5.3 Flash runs with full privacy — your prompts are never stored or profiled, and zero retention is enforced. You get uncensored access to a model designed for agentic coding and multimodal tasks, with end-to-end sovereignty over your data. This is open, performant AI without Big Tech surveillance.
Assessment
Strengths and limitations
- Natively multimodal with strong vision and video input handling built into the architecture.
- Extremely cost-efficient: delivers near-flagship intelligence at one-tenth the price of GLM 5.3.
- Open weights under MIT license enable self-hosting, auditing, and customization.
- Excels in coding, tool use, and agentic workflows with autonomous goal decomposition and tool invocation.
- Supports web search and structured output (JSON schema), making it ideal for research and automation.
- Slightly lower overall intelligence index (57) compared to GLM 5.3 (60), especially in complex reasoning tasks.
- Output speed (~49 tokens/sec) is slower than GLM 5.3 (~86 tokens/sec).
- Not end-to-end encrypted or running in a TEE, so not suitable for highly sensitive data isolation.
Capabilities
What it supports
- Vision (image input)
- Video input
- Tool use / function calling
- Reasoning
- Web search
- Code-optimized
- Structured output (JSON schema)
- Multiple image inputs
- Random seed on all plan tiers
- End-to-end encryption
- Runs in TEE
Specifications
Datasheet
- Maker
- Z.ai
- Open weights
- Yes — MIT license
- License
- MIT
- Modes
- Low, high, max reasoning effort via reasoning_effort parameter
- Context window
- 1,048.576K tokens
- Prompt length
- Up to 1M tokens input
- Input images
- Supported — multiple formats, native resolution up to 4K
- Released
- August 26, 2026
- Architecture
- 320B total / 18B active MoE, hybrid sparse + linear attention
- Parameters
- 320B total, 18B active
- Max output
- 131.072K tokens
- Capabilities
- Vision, Function calling, Reasoning, Web search, Code-optimized
- Privacy on Venice
- Private — zero retention
- Available on Venice since
- Aug 2026
API
Call it from your code
Venice exposes an OpenAI-compatible API. Point your base URL at Venice and pass the model id.
curl https://api.venice.ai/api/v1/chat/completions \
-H "Authorization: Bearer $VENICE_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"model": "z-ai-glm-5-3-flash",
"messages": [{ "role": "user", "content": "Explain quantum tunneling simply." }]
}'Pricing
What it costs on Venice
Billed per token on Venice: $0.15 per 1M input tokens and $0.50 per 1M output tokens.
New Venice accounts include a free daily allowance and 500 welcome credits — no credit card required.
Alternatives
How it compares
| Model | Best for | Context | Open weights | Price (Venice) |
|---|---|---|---|---|
| GLM 5.3 Flash | Multimodal coding & agents | 1M tokens | Yes | $0.15 in · $0.50 out / 1M |
| DeepSeek V4 Flash 0731 | Fast general reasoning | 1M tokens | Yes | $0.17 in · $0.35 out / 1M |
| Claude Opus 5 | Complex reasoning & accuracy | 1M tokens | No | $6 in · $30 out / 1M |
| GLM 5.1 | Privacy-focused workflows | 200K tokens | Yes | $1.10 in · $4.15 out / 1M |
GLM 5.3 Flash is the right pick when you need open, multimodal intelligence for coding and agentic tasks at the lowest possible cost — especially if you value self-hosting and auditability.
Use cases
What it is good for
- 01Automated coding workflows with visual feedback and browser interaction.
- 02Multimodal document analysis combining text, images, and charts.
- 03Agentic research tasks requiring web search, tool use, and structured output.
- 04Financial and office automation generating PPTX, PDF, XLSX from natural language.
- 05Low-cost, high-context AI for startups and developers needing open, auditable models.
Prompting
Getting better results
Use the reasoning_effort parameter to control thinking budget: set to 'low' for fast responses, 'max' for complex reasoning.
Pass clear_thinking=true in chat templates to improve coherence in conversational scenarios.
Include video or image inputs directly in the prompt for visual coding tasks.
Break down complex goals into steps — the model autonomously invokes tools and reviews outputs.
Use JSON schema in your request to get structured, parseable responses.
Reference rendered UIs or browser states in coding tasks — the model observes and iterates.
Version history
Predecessor model, less efficient and not natively multimodal.
Current — natively multimodal, MIT-licensed, flash cost.
FAQ
Frequently asked questions
GLM 5.3 Flash is Z.ai's first natively multimodal model in the GLM-5 series, released on August 26, 2026. It features 320B total parameters with 18B active, a 1M-token context window, and native support for vision, video, and code-optimized reasoning.
On Venice, GLM 5.3 Flash costs $0.15 per 1M input tokens and $0.50 per 1M output tokens, with cached input at $0.03 per 1M. A 50% promotional discount is available until September 9, 2026.
GLM 5.3 Flash is not free, but it is open source — the weights are released under the MIT license and available on Hugging Face, allowing self-hosting and modification.
Yes, GLM 5.3 Flash natively supports image and video input, making it ideal for visual coding, UI analysis, and multimodal workflows.
GLM 5.3 Flash has a context window of 1,048,576 tokens — among the largest available — enabling extremely long conversations and document processing.
Yes, GLM 5.3 Flash supports tool use and function calling, allowing it to autonomously interact with code, browsers, and APIs as part of agentic workflows.
GLM 5.3 Flash is far more cost-effective and open, ideal for coding and agentic tasks. Claude Opus 5 offers slightly stronger reasoning but at 60× the price and without open weights.
On Venice, GLM 5.3 Flash runs with zero retention — your prompts are never stored or profiled. You get full privacy and sovereignty while using a powerful, open model.
Run GLM 5.3 Flash privately
No prompt logging. No data used for training.