GLM-5
Zhipu AI · GLM
Zhipu's latest GLM flagship with long context, strong coding ability, and open-weight plus API access.
Overview
Freshness note: Model capabilities, limits, and pricing can change quickly. This profile is a point-in-time snapshot last verified on March 1, 2026.
GLM-5 is Zhipu AI’s latest flagship base model and one of the most relevant Chinese frontier options to track in 2026. It is positioned as a general-purpose model for reasoning, coding, and agent workflows, with both open-weight and hosted API routes.
For teams trying to avoid single-vendor dependency while keeping strong Chinese and bilingual performance, GLM-5 is now a practical option rather than only an experimental model to watch.
Capabilities
GLM-5 is strongest on multilingual instruction following, coding, and tool-centric assistant tasks. Zhipu positions it as a model that can maintain quality across longer workflows where context retention and planning matter.
It is also designed to be adaptable across consumer and enterprise usage modes. In practice, that means it can serve as a general default for mixed workloads instead of requiring immediate model routing complexity on day one.
Technical Details
Published GLM-5 specs list a 200,000-token context window and up to 128,000 output tokens. That output headroom is unusually high and useful for long synthesis jobs, report drafting, and agent traces where shorter output ceilings become a bottleneck.
Zhipu’s official model materials also frame GLM-5 as an open-source/open-weight capable flagship line. As with most open model ecosystems, exact licensing terms can differ between checkpoints and hosting channels, so deployment teams should verify the specific artifact license before production rollout.
Pricing & Access
Official API pricing published for GLM-5 is:
- Input: $1.00 per 1M tokens
- Output: $3.20 per 1M tokens
Access paths include Zhipu’s API platform and official model release channels for open-weight workflows.
Best Use Cases
Use GLM-5 for bilingual assistants, coding copilots, and long-context planning/synthesis workloads where cost matters but quality still needs to be competitive with higher-priced frontier tiers.
It is a strong fit when your system needs Chinese-first quality and you want the option to combine hosted and self-managed deployment strategies.
Comparisons
- Qwen3.5 (Alibaba): both target high-end Chinese and multilingual workloads; Qwen3.5 benefits from Alibaba ecosystem depth, while GLM-5 is compelling on cost-performance and open deployment flexibility.
- DeepSeek-R1 (DeepSeek): DeepSeek can be cheaper for some pure reasoning routes; GLM-5 is broader as a general flagship for mixed workloads.
- Mistral Small 3.2 (Mistral AI): Mistral is a strong Western open-weight alternative for multilingual engineering workflows; GLM-5 is typically favored when Chinese-language quality is primary.