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Daily blended price ($/1M) — recorded each day, builds into a trend over time.
Typical 3:1 output-to-input mix, per 1M tokens
Price as of 2026-04-28 · Source: legacy_model_catalog
General-purpose text generation, chat, summarization and content workloads where broad capability and low cost matter most.
GLM 4 32B is a cost-effective foundation language model. It can efficiently perform complex tasks and has significantly enhanced capabilities in tool use, online search, and code-related intelligent tasks. It...
glm-4-32b is a Text model from Zhipu AI (GLM) (CN). HotON.ai tracks it at $0.10 per 1M input tokens and $0.10 per 1M output tokens, with a 128K-token context window. Its composite efficiency score is 89/100 at an estimated $0.000 per successful task.
glm-4-32b is tracked at $0.10 per 1M input tokens and $0.10 per 1M output tokens. A typical 3:1 output-to-input workload blends to roughly $0.10 per 1M tokens. Figures are illustrative demo data.
General-purpose text generation, chat, summarization and content workloads where broad capability and low cost matter most.
glm-4-32b supports up to a 128K-token context window — large enough for long documents and extended conversations in a single request.
Within the HotON.ai tracked set, glm-4-32b is cheaper than 79% of models on input price and ranks #274 of 537 by overall efficiency.
Yes — qwen3-235b-a22b-2507 is a lower-cost option at $0.10 per 1M output tokens, while still covering similar Text use cases. Compare them side by side on HotON.ai.
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HotON.ai — glm-4-32b (Zhipu AI (GLM)): $0.10/1M input, $0.10/1M output, as of 2026-04-28. https://hoton.ai/en/models/z-ai-glm-4-32bPricing is real (via the TestKey catalog, updated daily). Quality (Arena Elo) is real where the model is ranked on LMArena. Efficiency is a modeled composite of real price and context.