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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 2026-05-11 · Source: microsoft_reference_catalog
General-purpose text generation, chat, summarization and content workloads where broad capability and low cost matter most.
Microsoft Research Phi-4 is designed to perform well in complex reasoning tasks and can operate efficiently in situations with limited memory or where quick responses are needed. At 14 billion...
phi-4 is a Text model from Microsoft (US). HotON.ai tracks it at $0.07 per 1M input tokens and $0.14 per 1M output tokens, with a 16K-token context window. Its composite efficiency score is 88/100 at an estimated $0.000 per successful task.
phi-4 is tracked at $0.07 per 1M input tokens and $0.14 per 1M output tokens. A typical 3:1 output-to-input workload blends to roughly $0.12 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.
phi-4 supports up to a 16K-token context window — large enough for long documents and extended conversations in a single request.
Within the HotON.ai tracked set, phi-4 is cheaper than 88% of models on input price and ranks #357 of 535 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 — phi-4 (Microsoft): $0.07/1M input, $0.14/1M output, as of 2026-05-11. https://hoton.ai/en/models/microsoft-phi-4Pricing 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.