Zhipu AI’s GLM-5 is what happens when you train a frontier model entirely on Huawei chips to survive US sanctions: it’s scrappy, surprisingly powerful, and aggressively cheap. As of February 2026, the Beijing-based lab (now a public company) has solidified its reputation as the "pragmatic alternative" to OpenAI. While GPT-5 and Claude Opus 4.6 fight for the $20/million high ground, Zhipu is winning the volume war with its free GLM-4-Flash model and the sub-$1/million flagship GLM-5.
For developers processing massive datasets, the math is impossible to ignore. Running a sentiment analysis pipeline on 10 million documents with GPT-4o cost a small fortune; with GLM-4-Flash, it costs literally zero dollars. If you need flagship-grade reasoning, upgrading to GLM-5 costs roughly $1.00 per million input tokens—about 80% cheaper than OpenAI’s equivalent. The 200k context window (and 1M on the Long variant) works reliably for RAG applications, and the new "DeepSeek Sparse Attention" architecture keeps latency competitive, even for Western users routing through the Great Firewall.
However, the elephant in the server room is the US Commerce Department’s Entity List. Since its addition in January 2025, Zhipu AI is effectively off-limits for US enterprise compliance teams requiring strict data residency or IP protection. You are sending data to Beijing, and the company is legally barred from buying US hardware. This makes Zhipu excellent for processing public data, summarizing academic papers, or running non-sensitive extraction tasks, but a hard "no" for handling PII or trade secrets.
The API itself is a seamless OpenAI clone. You can swap base_url and barely touch your code. Tool calling and JSON mode are robust, though the model’s refusal to discuss politically sensitive topics (like Taiwan or Xinjiang) is hard-coded and over-sensitive. If you’re a solo dev or a startup bootstrapping a data-heavy app, Zhipu is a financial lifesaver. If you’re a Fortune 500 CTO, it’s a compliance violation waiting to happen.
Pricing
The pricing strategy is aggressive and bifurcated. The entry-level GLM-4-Flash is genuinely free for API users, making it the industry standard for bulk tasks like classification or extraction where SOTA reasoning isn't required. New users get ~25M tokens on signup.
The flagship GLM-5 is priced around $1.00/1M input and $3.20/1M output (prices fluctuate slightly by region/provider). This is roughly 1/5th the cost of GPT-5. The "cost cliff" is non-existent for Flash users but steep if you accidentally route high-volume traffic to GLM-4.7-Plus or other legacy specialized models. Beware of latency costs: while dollars are low, round-trip times to Beijing can add 200-500ms overhead for US/EU requests.
Technical Verdict
The Python SDK (zhipuai) is a thin, reliable wrapper around the REST API, fully compatible with modern agent frameworks. Documentation is bilingual (Chinese/English) but English sections can lag behind. Latency is the main technical bottleneck for non-Asian users, though the new "Flash" models mitigate this with sheer inference speed. Reliability has improved significantly since the 2026 IPO, with fewer random timeouts than the 2024 era.
Quick Start
from zhipuai import ZhipuAI
client = ZhipuAI(api_key="YOUR_API_KEY")
response = client.chat.completions.create(
model="glm-4-flash",
messages=[{"role": "user", "content": "Summarize the history of AI in 20 words."}]
)
print(response.choices[0].message.content)Watch Out
- US Entity List: Added Jan 2025; strict internal compliance bans for many US firms.
- Censorship: Queries touching on sensitive Chinese political topics will trigger hard refusals or connection drops.
- Data Residency: All processing happens in mainland China; no EU/US distinct regions available.
- Hardware Constraints: Trained on Huawei Ascend chips; some niche numerical precision issues have been reported compared to Nvidia-trained models.