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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.
Pearl AI Gemma 4 31B Instruct is tracked as a public marketplace namespace reference so supplier catalog review can distinguish model-author rows from real provider routes.
gemma-4-31b-it is a Text model from Pearl AI (US). HotON.ai tracks it at $0.38 per 1M input tokens and $1.15 per 1M output tokens, with a 32K-token context window. Its composite efficiency score is 88/100 at an estimated $0.001 per successful task.
gemma-4-31b-it is tracked at $0.38 per 1M input tokens and $1.15 per 1M output tokens. A typical 3:1 output-to-input workload blends to roughly $0.96 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.
gemma-4-31b-it supports up to a 32K-token context window — large enough for long documents and extended conversations in a single request.
Within the HotON.ai tracked set, gemma-4-31b-it is cheaper than 49% of models on input price and ranks #303 of 535 by overall efficiency.
Yes — minimax-m2.7 is a lower-cost option at $1.20 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 — gemma-4-31b-it (Pearl AI): $0.38/1M input, $1.15/1M output. https://hoton.ai/en/models/pearl-ai-gemma-4-31b-itPricing 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.