Zhipu AI's flagship LLM with 200K context, multimodal reasoning, and open weights — China's answer to GPT-5.
GLM-5 is Zhipu AI's fifth-generation large language model, released in 2026 as a direct competitor to GPT-5, Claude 4.5, and Gemini 3 Pro. What sets it apart: open weights for research, a 200K context window, native multimodal reasoning (text + image + code), and an aggressive free-tier API that makes it one of the most accessible frontier models available.
Who it's for: Developers building AI apps who need a capable model without the $20/mo per-user cost. Researchers who want open weights. Teams targeting Chinese-language users. Budget-conscious startups.
Process up to 200K tokens — roughly 150,000 words — in a single call. Summarize entire codebases, analyze long documents, and maintain context across lengthy conversations without chunking.
GLM-5 understands text, images, and code natively. Upload a screenshot and ask it to write the HTML/CSS. Feed it a chart and ask for analysis. No separate vision model needed.
The base model weights are available for research and non-commercial use. Self-host on your own GPU infrastructure for full data privacy — no tokens leave your network.
OpenAI-compatible API endpoint. Drop-in replacement for GPT-5 in most apps — just change the base URL. Includes function calling, streaming, and structured outputs.
GLM-5 excels at Chinese-language tasks — translation, cultural context, and regional compliance. Outperforms Western models on Chinese benchmarks by 12-18%.
1M tokens/month free via API. Includes access to GLM-5 with rate limits. Perfect for prototyping and small projects.
$0.50 per million input tokens, $1.50 per million output tokens. No monthly commitment. Cheaper than GPT-5 by ~70%.
OpenAI's flagship model. Best overall quality, huge ecosystem, but pricier.
Anthropic's model. Best for long-form writing and nuanced reasoning.
Alibaba's open-source LLM. Another strong Chinese option with open weights.
DeepSeek's latest reasoning model. Open weights, excellent at math and code.