Large Language Models (LLMs) have revolutionized AI, business applications, professions, and many other disciplines but there is a new guy in the town, General Language Models (GLM 4.5), which is taking it even further by consolidating reasoning, coding, and agentic capabilities into a single framework, which is quite amazing.
What Is a GLM Model? (Foundation Model, Hybrid Reasoning, Agentic AI)
GLM 4.5 is developed by Zhipu AI, a leading Chinese AI startup backed by big companies like Alibaba and Tencent, the GLM series has rapidly evolved into a formidable competitor against western models like OpenAI’s GPT and Anthropic’s Claude, which means they are changing the dynamics of AI model landscape, AI adoption and Agentic AI applications.
With the recent launch of GLM-4.5, Zhipu AI has set a new benchmark for open-source, Agentic AI, combining hybrid reasoning, cost efficiency, and enterprise-grade performance. As an entrepreneur, product leader and AI researcher, I see this as a game-changer, here’s why.
Also read: Open AI GPT-5: Expected Features, Ethics, Benchmarks and Limitations
What is GLM-4.5? The Next Evolution of AI Agents
GLM-4.5 is Zhipu AI’s latest flagship model, designed for AI agent applications, AI systems that autonomously break down tasks, reason, and execute actions. Here are some of the key Specifications:
- 355B parameters, but only 32B active per inference (Mixture-of-Experts architecture, also known as MoE)
- 128K context window, enabling long-form reasoning and complex workflows
- Hybrid reasoning modes:
- Thinking Mode (deep analysis, multi-step problem-solving)
- Non-Thinking Mode (instant responses for low-latency tasks, which can be a real performance booster)
- Open-source (MIT licensed), allowing commercial use and customization
The thing is, unlike traditional LLMs, GLM-4.5 is agent-native, meaning it’s optimized for autonomous task execution, tool integration, and real-world problem-solving, making it ideal for business automation and AI-driven workflows. The possibilities are endless.
Also read: AI Strategy for Product Leaders to Build Intelligent Products
GLM-4.5 Benchmarks
How does GLM-4.5 stack up against leading proprietary models? Let’s dive into the performance benchmarks:
Ref: https://huggingface.co/zai-org/GLM-4.5
GLM-4.5 vs. GPT 4.1 vs. Claude 4 Sonnet Benchmark
GLM-4.5 is mainly a foundation model which is optimized for AI agentic tasks. The model has equally great performance as compared to Claude 4 Sonnet.
- GLM-4.5 outperformed OpenAI’s GPT-4.1 in function calling and web browsing as well as performed very closely as compared to Claude 4 Sonnet in some of the automation tasks.
- GLM 4.5 claims to have reached 90.6% tool-calling success rate (vs. Claude’s 89.5%), making it the most reliable for agentic workflows
- Excels in math (AIME24) and coding (SWE-bench) , surpassing GPT-4.1 and competing closely with Claude.
- 53.9% win rate against Kimi K2 in coding tasks, proving its full-stack development capabilities
Also read: Applying Design Thinking to build innovative Cloud based AI Products
GLM 4.5 for Business Applications: How Entrepreneurs and Product Leaders can leverage
1. GLM 4.5 for AI-Powered Automation
- Customer Support: GLM 4.5 can be used for customer support systems. Deploy autonomous chatbots with web-search capabilities.
GLM-4.5’s 90.6% tool-calling success rate ensures reliable interactions, while its hybrid modes enable quick responses for FAQs and deep reasoning for complex queries. It can also be used to integrate with CRM systems for personalized support workflows. - E-Commerce: GLM 4.5 can be used for E-commerce to automate inventory management, dynamic pricing, and personalized recommendations.
2. GLM 4.5 for Application Development
- Generate entire web apps using GLM 4.5 (HTML, CSS, backend) from natural language prompts.
GLM-4.5’s 64.2% SWE-bench score and frontend design capabilities (e.g., SVG graphics, responsive layouts) enable rapid prototyping, reducing development cycles from weeks to hours.
3. GLM 4.5 for Data Analysis & Decision Intelligence
- Autonomous market research agents (web scraping + report generation).
With 26.4% BrowseComp accuracy, GLM-4.5 outperforms Claude 4 Opus in extracting actionable insights from web data, ideal for competitive analysis and trend forecasting. This is one of my personal favourites!
GLM 4.5 Pricing
We are using official pricing from Zhipu AI’s Open Platform (open.bigmodel.cn/pricing), converted into USD using the 2025‑08‑01 mid‑market rate of 1 CNY = 0.1387 USD
| Model Version | Input (¥/1M tok) | Output (¥/1M tok) | Input (USD ≈) | Output (USD ≈) |
|---|---|---|---|---|
| GLM‑4.5 | 0.8 CNY | 2 CNY | ≈ $0.11 | ≈ $0.28 |
| GLM‑4.5‑Air | 0.8 CNY | 2 CNY | same | same |
Breakdown of the Conversion:
- Input tokens (prompt you send): ¥0.8 / 1M → 0.8 × 0.1387 ≈ $0.111
- Output tokens (model’s response): ¥2 / 1M → 2 × 0.1387 ≈ $0.277
- Rounding: merchandise to $0.11 input / $0.28 output per million tokens.
Example Scenarios
Scenario A: Low‑interaction bot (e.g. FAQ/helpdesk)
- Prompt: 450 tokens, Response: 300 tokens, 500 calls/day, 30 days/month
- Input cost: 450 × 500 × 30 ÷ 1e6 × 0.111 = ≈ $0.75/month
- Output cost: 300 × 500 × 30 ÷ 1e6 × 0.277 = ≈ $1.25/month
- Total ≈ $2.00/month
Scenario B: Content‑generation (e.g. long article drafts)
- Prompt: 300 tokens → draft feeding; Response: 1,125 tokens, 50 calls/day, 30 days/month
- Input cost: 0.3 × 50 × 30 ÷ 1e6 × 0.111 = ≈ $0.0005/month
- Output cost: 1.125 × 50 × 30 ÷ 1e6 × 0.277 = ≈ $0.47/month
- Total ≈ $0.47/month
Also read: Designing High-Performance Product Strategy: A Leader’s Perspective
Conclusion
GLM-4.5 is an Open Souce model which isn’t just another LLM, it’s a paradigm shift toward open, agentic AI that businesses and products can own and customize. With top-tier reasoning, coding, and automation benchmarks, plus unmatched cost efficiency, it’s poised to disrupt industries of SaaS applications for various industries such as FinTech, Telecom, MedTech, Manufacturing, Automotive, Digital Media and many others.
For entrepreneurs and product leaders, the message is clear: The future of AI-driven business cannot be taken without GLM-4.5. Whether you’re building autonomous agents, optimizing workflows, or developing next-gen AI apps, this model delivers performance, flexibility, and scalability, without the exorbitant costs of closed AI ecosystems.
