The Open-Source AI That’s Actually Open

Everyone’s fighting over ChatGPT vs Claude, meanwhile China just dropped a 355B parameter model that’s completely free. Yes, really.

GLM-4.5 isn’t just another “GPT-4 competitor” – it’s the first truly open model that doesn’t make me roll my eyes at the benchmarks. After three weeks of hammering this thing with real work, I’m genuinely shocked more people aren’t talking about it. Here’s what you need to know.

What is GLM-4.5?

GLM-4.5 is Zhipu AI’s latest foundation model, released in July 2025. It’s a 355-billion-parameter beast (32B active) that uses a Mixture of Experts architecture to compete directly with GPT-4, Claude, and Gemini. The kicker? It’s actually open-source with an MIT license. No asterisks, no “open but not really” – you can download it, modify it, sell it, whatever.

The model comes from a Tsinghua University spin-off backed by Alibaba and Tencent. If you’re thinking “Chinese model = censored garbage,” you’re in for a surprise. This thing is legitimately good.

Key Features That Matter

Hybrid Reasoning That Works

GLM-4.5 has two modes:

Thinking mode: For complex problems – it actually shows its work
Non-thinking mode: For quick responses – blazing fast

This isn’t marketing fluff. The thinking mode genuinely improves output quality for hard problems.

Agent-Native Design

While other models bolt on tool use as an afterthought, GLM-4.5 was built for it. Web browsing, code execution, and function calling are baked into the architecture. It doesn’t just call tools – it understands when and why to use them.

Insane Speed

With speculative decoding, I’m seeing 100-200 tokens/second. That’s 2.5-8x faster than most models. For production use, this is game-changing.

Actually Affordable

Input: $0.11 per million tokens
Output: $0.28 per million tokens

That’s not a typo. It’s literally 100x cheaper than GPT-4.

Real-World Testing Results

I put GLM-4.5 through everything I throw at Claude and GPT-4:

Writing Tests

Technical documentation: Clear, well-structured, minimal hallucination
Blog posts: Good flow, but occasionally shows its Chinese training
Creative writing: Decent but not exceptional – cultural nuances sometimes off
Code comments: Excellent – explains complex logic clearly

Coding Tests

Full-stack development: Built a working task manager with React + FastAPI
Algorithm challenges: Solved every LeetCode hard I threw at it
Code review: Caught bugs and suggested legitimate optimizations
System design: Proposed sensible architectures with proper trade-offs

Agent Tasks

Web research: 26.4% accuracy on BrowseComp (beats Claude-4-Opus at 18.8%)
Multi-step planning: Breaks down complex tasks intelligently
Tool coordination: Smoothly chains multiple tools without confusion
Autonomous execution: Can work for hours without hand-holding

Pricing Breakdown

Let’s talk money because this is where it gets ridiculous:

GLM-4.5 API (via Z.ai):

Input: $0.11/million tokens
Output: $0.28/million tokens

Compare to:

GPT-4: $30/million tokens (270x more expensive)
Claude 3.5: $15/million tokens (135x more expensive)
Gemini 1.5 Pro: $7/million tokens (63x more expensive)

But here’s the real kicker – it’s MIT licensed. You can run it yourself for just the cost of electricity.

GLM-4.5 vs. The Competition

GLM-4.5 vs. GPT-4

General tasks: GPT-4 slightly better but not 270x better
Coding: Dead heat
Speed: GLM-4.5 much faster
Agent tasks: GLM-4.5 actually better
Price: Not even close

GLM-4.5 vs. Claude 3.5 Sonnet

Writing quality: Claude better for English creative work
Instruction following: Both excellent
Reasoning: GLM-4.5 thinking mode impressive
Availability: GLM-4.5 (no rate limits if self-hosted)

GLM-4.5 vs. Open Models (Llama, Mistral)

Performance: GLM-4.5 consistently better
True openness: GLM-4.5 (MIT license vs restrictive licenses)
Agent capabilities: GLM-4.5 by a mile
Deployment: GLM-4.5-Air (12B active) easier for edge

Who Should Use GLM-4.5?

Perfect For:

Startups that need to process millions of tokens daily
Developers building agent-based applications
Companies wanting true data sovereignty
Researchers who need to modify models
Anyone sick of API rate limits and bills

Skip If:

You need perfect English creative writing
You want hand-holding and extensive documentation
You’re not technical enough to debug issues
You need 24/7 enterprise support

Tips for Best Results

Use thinking mode for complex tasks – The quality difference is real
Leverage the agent capabilities – It’s better at tool use than most models
Try GLM-4.5-Air first – 12B active params, same architecture, runs on consumer hardware
Join the Discord – The community is surprisingly helpful
Read the Chinese documentation – Google Translate works fine, more detailed than English

Common Complaints (And Reality)

“It’s Chinese so it must be censored” – Surprisingly uncensored. Less restricted than Claude on many topics.

“Documentation is mostly in Chinese” – True, but the code is clear and community fills gaps.

“Benchmarks are cherry-picked” – I’ve verified performance myself. It’s legit.

“No enterprise support” – Fair point. This is for teams that can self-support.

The Hidden Gem: GLM-4.5-Air

Everyone’s focused on the big model, but GLM-4.5-Air (106B total, 12B active) is the real breakthrough. Same capabilities, runs on a single A100, perfect for edge deployment. This is what I’m actually using in production.

The Bottom Line

GLM-4.5 is the most important open model release of 2025. Not because it beats GPT-4 (it doesn’t quite), but because it’s genuinely open, genuinely good, and genuinely usable.

At 1/100th the cost of GPT-4 with 90% of the performance, the math is obvious. The agent capabilities are best-in-class. The speed is unmatched. And you actually own it.

Yes, there are rough edges. Yes, the documentation needs work. Yes, you’ll occasionally hit weird cultural assumptions in the training. But for the price (free), complaining feels petty.

This is what open-source AI should be. Download it before someone decides it’s too good to be free.

Frequently Asked Questions

Q: Is it really MIT licensed? A: Yes. Check the Hugging Face repo. No tricks, no commercial restrictions.

Q: Can I actually run this locally? A: The full model needs serious hardware. Start with GLM-4.5-Air or use the API.

Q: How’s the English performance? A: 95% as good as native English models. Occasional odd phrasing but totally usable.

Q: Will it help me make weapons/malware/etc? A: Less restricted than Western models but still has some guardrails. Don’t be evil.

Q: Should I switch from Claude/GPT-4? A: Try it for a week. The cost savings alone make it worth testing.

Ready to try GLM-4.5? Download from Hugging Face or use the API at z.ai. Your AWS bill will thank you.

Zhipu AI's GLM-4.5 Review