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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
Source: litellm
General-purpose text generation, chat, summarization and content workloads where broad capability and low cost matter most.
Z.ai GLM 4.7 is a Cerebras preview model for fast reasoning, code, and tool-use workloads.
zai-glm-4.7 is a Text model from Cerebras (US). HotON.ai tracks it at $2.25 per 1M input tokens and $2.75 per 1M output tokens, with a 131K-token context window. Its composite efficiency score is 88/100 at an estimated $0.006 per successful task.
zai-glm-4.7 is tracked at $2.25 per 1M input tokens and $2.75 per 1M output tokens. A typical 3:1 output-to-input workload blends to roughly $2.63 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.
zai-glm-4.7 supports up to a 131K-token context window — large enough for long documents and extended conversations in a single request.
Within the HotON.ai tracked set, zai-glm-4.7 is cheaper than 15% of models on input price and ranks #395 of 537 by overall efficiency.
Yes — minimax-m2 is a lower-cost option at $1.00 per 1M output tokens, while still covering similar Text use cases. Compare them side by side on HotON.ai.
Ready to paste into articles, papers or AI prompts — prices and date refresh with the live data.
HotON.ai — zai-glm-4.7 (Cerebras): $2.25/1M input, $2.75/1M output. https://hoton.ai/en/models/cerebras-zai-glm-4-7Pricing 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.