glm-5.3-flash

glm-5.3-flash is a budget-tier language model from GreenPT. glm-5.3-flash is a proprietary model available exclusively through GreenPT's API. The GLM family is GreenPT's model series for this capability tier.

glm-5.3-flash is priced at $0.11/1M input tokens and $0.44/1M output tokens. Output tokens are 4× more expensive than input tokens — this ratio reflects the sequential nature of autoregressive generation, which requires a separate forward pass per output token versus parallel processing of all input tokens simultaneously. At a typical usage pattern of 1,000 input tokens and 500 output tokens per call, glm-5.3-flash costs approximately $0.33 per 1,000 API calls. GreenPT does not publish a prompt caching rate for this model, so repeated long contexts are billed at the standard $0.11/1M input rate.

Its 1.0M-token context window is among the largest available — sufficient for processing entire codebases, book-length documents, or hours of transcribed audio in a single API call.

glm-5.3-flash is best suited to cost, chat, long-context. Supported capabilities include function calling / tool use for agentic workflows, streaming token output for real-time UIs. Function calling support makes it suitable for building AI agents, structured data extraction pipelines, and any workflow requiring the model to invoke external APIs or return typed JSON. When evaluating this model for a specific workload, the most important factors are: context window (does your input fit?), output price (how long are your generations?), and latency (is this interactive or batch?). The pricing table above shows how glm-5.3-flash compares to similar models across these dimensions.

glm-5.3-flash sits in the budget tier — the most cost-efficient models, best for high-volume simple tasks, classification, extraction, and applications where cost per call is the primary constraint. Unlike open-weights alternatives, glm-5.3-flash is only available via GreenPT's API — there is no self-hosted option, which simplifies deployment but creates vendor dependency. When comparing glm-5.3-flash to alternatives, use the similar models section on this page to find models at comparable price points with different capability tradeoffs. The intelligence score (N/A/100) reflects aggregate benchmark performance — a useful proxy for general capability, though real-world performance varies significantly by task type. Always test with your specific prompts and use case before committing to a model for production.