GLM-5.3-Flash is a chat model from Z AI, positioned in the GLM line's "Flash" tier for latency- and cost-sensitive workloads.
| Provider | Input / 1M | Output / 1M | Cached / 1M |
|---|---|---|---|
| $0.075 | $0.250 | $0.015 | |
| $0.075 | $0.250 | $0.015 | |
| $0.150 | $0.500 | $0.030 | |
| $0.150 | $0.500 | $0.030 | |
| $0.150 | $0.500 | $0.075 | |
| $0.150 | $0.500 | - | |
| $0.150 | $0.500 | - | |
| $0.150 | $0.500 | $0.030 | |
| $0.200 | $0.500 | $0.050 |
Prices updated daily. Last check: Sep 5, 2026
Input, output, and batch rates, plus alternatives, for one provider at a time.
Benchmarks measured Sep 2026. Scores are independent evaluations, not vendor-reported.
GLM-5.3-Flash fits workloads that send many text requests and care about per-request cost: chat assistants and support bots, summarization of tickets or documents, classification and tagging, structured data extraction, content rewriting, and drafting steps inside a larger pipeline. Its measured ~49 tokens/second output rate and just-over-one-second time to first token are adequate for streaming chat UIs where users see partial output immediately. A common pattern with Flash-tier models is tiered routing — handle the bulk of straightforward requests here and escalate harder prompts to a larger GLM 5.3 model. For tasks that hinge on deep multi-step reasoning, long-context document analysis, or verified benchmark thresholds, confirm capabilities with the provider first, since we do not track context length or task benchmarks for this entry.
Pricing depends on which provider hosts the model and on the pricing type — input tokens, output tokens, and any cached-input or batch rates are billed separately, and rates change frequently. Check the pricing table on this page for current per-provider figures rather than relying on a fixed number.
High-volume text work where cost and responsiveness matter more than maximum capability: chat assistants, summarization, classification, extraction, and drafting steps in automated pipelines. It is also a reasonable default tier in a routing setup that escalates harder prompts to a larger GLM 5.3 model.
Artificial Analysis measured roughly 49 output tokens per second with a time to first token of about 1,180 ms. Real-world numbers vary by provider, region, prompt length, and load, so compare providers if latency is a hard requirement.
Flash-tier GLM models are built for cheaper, faster serving, while the larger models in the same generation target harder reasoning and agentic tasks. If your prompts involve long multi-step reasoning or complex tool orchestration, evaluate a larger sibling alongside Flash before committing.
We do not have a confirmed context window for this model in our database. Check the documentation of the provider you plan to use, since hosted endpoints can also impose their own maximum input and output limits.