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Blended $/1M across tracked versions of this line.
Typical 3:1 output-to-input mix, per 1M tokens
Price as of 2026-04-28 · Source: legacy_model_catalog
Mixed text, image, audio and document workloads that benefit from one model across modalities.
GPT-4.1 Mini is a mid-sized model delivering performance competitive with GPT-4o at substantially lower latency and cost. It retains a 1 million token context window and scores 45.1% on hard...
gpt-4.1-mini is a Multimodal model from OpenAI (US). HotON.ai tracks it at $0.40 per 1M input tokens and $1.60 per 1M output tokens, with a 1048K-token context window. Its composite efficiency score is 96/100 at an estimated $0.002 per successful task.
gpt-4.1-mini is tracked at $0.40 per 1M input tokens and $1.60 per 1M output tokens. A typical 3:1 output-to-input workload blends to roughly $1.30 per 1M tokens. Figures are illustrative demo data.
Mixed text, image, audio and document workloads that benefit from one model across modalities.
gpt-4.1-mini supports up to a 1048K-token context window — large enough for long documents and extended conversations in a single request.
Within the HotON.ai tracked set, gpt-4.1-mini is cheaper than 47% of models on input price and ranks #18 of 537 by overall efficiency.
Yes — gemini-2.0-flash-lite-001 is a lower-cost option at $0.30 per 1M output tokens, while still covering similar Multimodal use cases. Compare them side by side on HotON.ai.
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HotON.ai — gpt-4.1-mini (OpenAI): $0.40/1M input, $1.60/1M output, as of 2026-04-28. https://hoton.ai/en/models/openai-gpt-4-1-miniPricing 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.