GLM 5.1 AI: The $3 Coding Model That Nearly Beats Claude

01What Is GLM 5.1 AI and How It Works

GLM 5.1 AI is a new language model from Chinese company Z.AI (also called Jerpu AI). It scores 45.3 on coding benchmarks, which is 94.6% of Claude Opus 4.6’s score of 47.9. The model is designed to handle complex coding tasks and is available for just $3 a month.

The model uses a mixture-of-experts architecture with 744 billion total parameters, but only 40 billion are active per request. This keeps it fast and cheap to run. It supports a 200,000 token context window and can output up to 131,000 tokens in a single response.

That’s like writing an entire book in one shot.

Z.AI trained GLM 5.1 entirely on 100,000 Huawei Ascend 910B chips, which are made in China. This is important because the company is on the US entity list and cannot buy NVIDIA chips. Despite this, the model performs at a near-frontier level.

02Key Features and What's New in GLM 5.1

GLM 5.1 brings several key improvements over its predecessor, GLM 5. The coding score jumped from 35.4 to 45.3, a 28% improvement in just 6 weeks. It also outperforms many open-source models on advanced math and science benchmarks.

• Mixture-of-Experts: Only 40 billion of 744 billion parameters are active per request, keeping costs low.
• 200K token context window: Handles long documents and complex conversations.
• 131K token output: Can generate book-length content in one response.
• Open-source ready: GLM 5 was released under the MIT license, and GLM 5.1 is expected to follow.
• Fast iteration: Z.AI has released a major model nearly every month since July 2025.

This speed of release is unmatched by any other AI company, including OpenAI, Google DeepMind, and Anthropic.

03How to Set Up GLM 5.1 for Coding

Getting started with GLM 5.1 is straightforward, especially if you already use tools like Claude Code or Cursor. The model plugs directly into these tools, so the setup is minimal.

1. Sign up for a GLM 5.1 coding plan on the Z.AI platform ($3/month promo for 120 prompts).
2. Open your AI tool (e.g., Claude Code, Cursor, or OpenCode).
3. Go to the config file or settings.
4. Change the model name to “GLM 5.1” in the model field.
5. Save the config and restart the tool.
6. Start using GLM 5.1 for your coding tasks.

You don’t need to learn a new interface or change your workflow. Just one line in the config file is enough to switch.

04How to Use GLM 5.1 in Real Projects

In the episode, Julian demonstrated how GLM 5.1 can be used in real business scenarios. For example, if you run an agency, you can use it to build landing pages and write email sequences for clients. The model delivers nearly the same quality as Claude at a fraction of the cost.

One of the biggest advantages is the low switching cost. Since GLM 5.1 works with Claude Code, you can keep your existing workflow. Just swap the model name and you’re running.

No new setup, no relearning.

You can also use GLM 5.1 for complex problem-solving, math, and science tasks. It scored 92.7% on AME 2026 for advanced math and 86% on GPQA Diamond for graduate-level science questions. This makes it a versatile tool for both coding and other technical work.

05Benchmarks and Comparison Results from the Episode

In the episode, Julian shared specific benchmark scores to show how GLM 5.1 stacks up against the competition. The model scored 45.3 on coding benchmarks, compared to Claude Opus 4.6’s 47.9. That’s 94.6% of Claude’s performance.

• SWE Bench Verified (GLM 5): 77.8%, the best open-source score at the time.
• AME 2026 (math): 92.7%.
• GPQA Diamond (science): 86%.
• Agentic benchmarks: Topped all other open-source models on BrowseComp, VendingBench 2, and MCP Atlas.

Importantly, these benchmarks were run using Claude Code as the testing framework, which gives Claude an advantage. Despite that, GLM 5.1 still scored nearly as well. However, these numbers are self-reported and not verified by independent labs.

06Pricing and Cost Comparison

The pricing for GLM 5.1 is dramatically lower than Western models. The coding plan starts at $3 per month for 120 prompts. Standard is $10/month, and Pro is $30/month.

Even the most expensive plan is far cheaper than Claude Max, which costs $100–$200 per month.

On the API side, GLM 5.1 charges $1 per million input tokens and $3.20 per million output tokens. Claude Opus 4.6 charges $5 for input and $25 for output. That makes Claude roughly 5 to 8 times more expensive.

For an agency or freelancer, this difference can drastically improve profit margins. If you use AI to serve clients, you get similar quality for a fraction of the cost. That’s a huge advantage for your business.

07Tips, Limits, and Mistakes to Avoid

While GLM 5.1 is impressive, it has some limitations you should know about. Its context window is 200,000 tokens, compared to Claude’s 1 million. For deep reasoning and complex multi-step analysis, Claude still has the edge.

Also, for multi-modal tasks like image understanding, Claude and GPT are still ahead.

• Beware of self-reported benchmarks: Treat the exact scores with skepticism until independent verification.
• Don’t throw away your existing tools: Use GLM 5.1 as an additional weapon, not a replacement for everything.
• Check the license: GLM 5 was MIT-licensed, but GLM 5.1 hasn’t been released yet (as of the episode).
• Watch for performance variance: Real-world results may be 10–15% lower than claimed.

Despite these limits, GLM 5.1 is a powerful, affordable option for specific tasks like coding and math. Ignoring it could mean paying much more for similar results.

08Who GLM 5.1 Is For and Why It Matters

GLM 5.1 is perfect for developers, freelancers, and agencies that rely on AI for coding and business automation. If you’re looking to cut costs without sacrificing quality, this model is a game-changer. It’s also great for anyone who wants to stay ahead of the AI curve.

The bigger picture is that the gap between open-source and closed-source AI is nearly gone. GLM 5.1 proves that you can build frontier-level AI without American hardware. This matters for every business, because more competition means better tools and lower prices.

The biggest winners won’t be the companies building these models—it’ll be the people who use them before everyone else catches up. The gap between expensive and affordable AI has basically disappeared overnight.