China's Low-Priced Z.ai Model Is Exposing Costly Coder Habits
Zain Hasan, an AI engineer at Together AI, has taught himself to use AI coding assistants while still keeping an eye on cost. He directs difficult problems to a frontier model, meaning one near the current state of the art in reasoning and capability, such as Anthropic's Fable. But if the task that Hasan is outsourcing is more straightforward, he directs it to a less capable-and less expensive-language model.
Key Takeaways
- Right now, the cheaper model, for him, tends to be GLM 5.
2 is an open-weights model , meaning any organization with sufficient hardware can download and host the model for free.
- "The easiest thing is to pick the most powerful model.
" That price-be-damned habit, reinforced by loose token budgets in software companies today, may now be the widest moat protecting the U.
- 2 scores well in cybersecurity benchmarks , a capability that spurred comparisons to Anthropic's Mythos .
- Any organization worried about where their data is being sent can instead host the model on their own hardware.
This stands in contrast to most frontier-level models, which are gated behind an API with no self-hosting option.
- 2 completed just 13 percent of tasks in SWE-Marathon , a difficult long-duration agentic coding benchmark.
Stats & Key Facts
- #2 is an AI large language model (LLM) with 753 billion parameters, though it has only 40 billion parameters active at once-an optimization that improves the speed at which a model can respond.
- #According to Stanford's AI Index (an annual, 300-plus-page survey of AI trends) Chinese companies produced just over half as many "notable" AI models in 2025 as their U.
- #2 completed just 13 percent of tasks in SWE-Marathon , a difficult long-duration agentic coding benchmark.
ai for GLM access still can save money, because the company's API costs $4. That's less than a fifth of the comparable price for access to Anthropic's Opus 4. 8 model, and a tenth the price of Anthropic's Fable coding model.
An output token is the basic unit of text a model generates in response to a prompt. Yet many software engineers around the world, Hasan said, aren't yet fully mindful of the net AI pricetag for a given coding project. "A lot of companies right now, they're still trying to figure this technology out, and so there isn't really a token budget," said Hasan.
And when someone else is paying, the rational move for many software engineers is to skip tabulating costs entirely. "The easiest thing is to pick the most powerful model. " That price-be-damned habit, reinforced by loose token budgets in software companies today, may now be the widest moat protecting the U.
For more details please read the original article at IEEE Spectrum AI.
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