GLM-4.7 Slashes Claude Code Costs by 90%: Here's How

Switching to z.ai's GLM-4.7 platform can cut your Claude Code token consumption by up to 90%, making it 10 times cheaper with comparable coding performance.

The Quick Answer

If you're burning through tokens with Claude Code and the bills are adding up, z.ai's GLM-4.7 offers a legit alternative. Based on the docs and benchmarks, it gives you 3x more usage than Claude Max, costs about 1% per prompt of standard APIs, and holds its own in coding tasks against Claude Opus 4.5. Honestly, it's a game-changer for devs on a budget.

FAQ

Frequently Asked Questions

Q: Is GLM-4.7 really as good as Claude for coding? A: Surprisingly, yes. Benchmarks like SWE-bench and LiveCodeBench V6 show GLM-4.7 matching Claude Opus 4.5 in coding abilities. It's not perfect—Claude might edge it out in creativity but for most tasks, you won't notice the difference.

Q: How much can I actually save by switching to z.ai? A: A ton. If you're using Claude Code heavily, z.ai's pricing means you could pay just 10% of what you do now. The GLM Pro Plan lets you run about 600 prompts in 5 hours, compared to Claude's limits, and each prompt costs pennies instead of dollars.

Q: What's the catch with the extended capabilities? A: Here's the deal: Vision Understanding, Web Search, and Web Reader MCP servers are locked behind subscriptions. If you need those, factor in the extra cost. But for pure coding, the base plan is more than enough.

Why This Matters

Let's be real Claude Code's token consumption sucks. You're paying for every single token, and it adds up fast, especially if you're iterating on code or debugging. I've seen bills skyrocket for no good reason. So why does this matter? Because z.ai with GLM-4.7 gives you a way out without sacrificing quality.

After digging into the docs at z.ai/devpack, I found that this isn't just hype. The cost savings are backed by real numbers, and the performance is there. If you're an advanced developer burning cash on AI coding assistants, this is worth your attention.

How It Actually Works

Setting up z.ai with GLM-4.7 isn't rocket science, but it does require a bit of tinkering. Here's a breakdown based on what I've learned.

Step 1: Sign Up and Configure

First, head to z.ai and grab the GLM Pro Plan. Confusing? Let me break it down you'll need to create an account and set up your API keys. The docs mention that integration is straightforward, but I lost an hour figuring out the rate limits.

# Example: Setting up a basic prompt with z.ai GLM-4.7
import requests

api_key = "your_glm_api_key_here"
url = "https://api.z.ai/v1/chat/completions"

headers = {
    "Authorization": f"Bearer {api_key}",
    "Content-Type": "application/json"
}

payload = {
    "model": "glm-4.7",
    "messages": [
        {"role": "user", "content": "Write a Python function to reverse a string."}
    ],
    "max_tokens": 500
}

response = requests.post(url, json=payload, headers=headers)
print(response.json())

Gotcha: The API endpoints might differ from Claude's, so check the z.ai docs carefully. I messed this up at first and wasted tokens on failed calls.

Step 2: Optimize Your Prompts

GLM-4.7 is efficient, but you still need to write good prompts. Each prompt can handle 15-20 model calls in the background, which means you can batch tasks. For instance, instead of sending separate requests for code review and debugging, combine them.

Long story short, think in terms of multi-turn conversations within a single prompt. The docs highlight this as a key feature for cost savings.

The Stuff Nobody Tells You

Here's what I learned the hard way: the setup isn't as seamless as Claude's interface. z.ai's platform is powerful, but it's geared more towards developers who don't mind getting their hands dirty with API calls. The docs are decent, but they assume you know your way around.

Also, while GLM-4.7 competes with Claude on benchmarks, in real-world use, I've noticed it can be a bit slower on complex reasoning tasks. Not a deal-breaker, but something to keep in mind if you're under tight deadlines.

And about pricing yes, it's cheaper, but monitor your usage. The "per prompt" model means costs can creep up if you're not careful, though it's still a fraction of Claude's rates.

When to Use This (And When Not To)

Good for:

• Heavy coding sessions where token costs with Claude are prohibitive.
• Teams on a budget needing reliable AI assistance for development.
• Projects that require batch processing or multi-turn conversations.

Avoid when:

• You need the absolute best in creative code generation Claude might still have an edge.
• Your workflow depends heavily on integrated tools that only work with Claude.
• You're not comfortable with API integrations and prefer a plug-and-play solution.

Alternatives Worth Considering

If z.ai isn't your thing, look at other cost-effective models like CodeLlama or GPT-4 mini. But honestly, for the balance of cost and performance, GLM-4.7 is hard to beat right now. Claude's great, but you're paying for the brand name.

The Verdict

Switch to z.ai with GLM-4.7 if you're serious about cutting costs without losing coding prowess. It's not perfect no tool is but the savings are real, and the performance holds up. Give it a shot for a month; you might just kiss those high token bills goodbye.

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Last updated: 2025 • Based on current information as of 2025 from z.ai docs