Several Chinese large models now compete with Western offerings while providing substantially lower API costs and comparable performance on many tasks.

Background and catalyst

Last January, DeepSeek surpassed ChatGPT in the U.S. App Store after training its model for $6M, against $100M+ reported for Western peers.

Export restrictions on Nvidia chips in 2022 pushed Chinese labs to optimize models on alternative hardware and extract more performance from limited resources.

Leading Chinese models

Below are several prominent models that developers have adopted for cost-sensitive or agent-heavy use cases.

• GLM-5 (Zhipu AI) — 77.8% on SWE-bench Verified; leaderboard shows MIT license, 744B parameters, activates only 40B on request; best suited for code and agent tasks.
• Kimi K2.5 (Moonshot AI) — reported 1 trillion parameters and the ability to run up to 100 parallel subagents; 74.9% on BrowseComp versus 59.2% for Claude Opus 4.5.
• Qwen 3.5 (Alibaba) — emphasises multilingual capabilities and is available under Apache 2.0, enabling broader commercial use.
• DeepSeek V4 (DeepSeek) — positioned as a low-cost option with pricing around $0.14-0.30 per 1M tokens; reportedly funded by a hedge fund investor.

Pricing comparison

Published API price ranges illustrate large differences: Claude Opus listed at $5-15/M tokens, while GPT-5.4 is $5-10/M tokens.

By contrast, Kimi K2.5 is offered at about $0.6/M tokens and DeepSeek V4 at roughly $0.4/M tokens, enabling many more calls for the same budget.

Operational caveats

Chinese models often enforce strict restrictions on politically sensitive content and typically route API calls through servers located in China unless alternative routing is used.

For tasks requiring stricter data governance, such as certain medical, financial or government workloads, these deployment and content constraints may be unsuitable.

Many of the models are available for local download and can be run on private hardware, offering further flexibility for offline or controlled environments.

Summary

Developers seeking lower-cost inference or large-agent setups have practical alternatives among Chinese offerings, albeit with trade-offs in content controls and hosting.