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OpenAI's voice models have had one price cut in 22 months — and text output got dearer along the way

OpenAI has told developers that nine legacy voice models — the entire GPT-4o audio and realtime line, plus the first generation of GPT-Audio and GPT-Realtime — stop answering on 20 January 2027. Adding the four missing GPT-4o voice profiles to our catalogue put the whole price history of that line in one place, and it reads differently from the price history of text. When GPT-4o Audio and GPT-4o Realtime went live on 1 October 2024, an audio token cost $40 per million on the way in and $80 on the way out. In August 2025 the successors, GPT-Audio and GPT-Realtime, brought that to $32 and $64. Today's generally available replacements — gpt-audio-1.5 and gpt-realtime-2.1, the models OpenAI names in the shutdown notice — charge exactly the same $32 and $64. That is one cut, of 20%, in twenty-two months, and nothing since. Text inside the same models moved in both directions. In the realtime line, input fell from $5 to $4 per million and cached input collapsed from $2.50 to $0.40, a drop of 84%. Output went the other way: $20 in 2024, $24 today — 20% more expensive. And the ratio that matters for anyone building a voice product has not shifted at all. In October 2024 an audio input token cost eight times a text input token; in August 2026, at $32 against $4, it still costs eight times as much. What the buyer does get for the same money is room. GPT-4o Realtime remembered 32,000 tokens and answered with at most 4,096; gpt-realtime-2.1 holds 128,000 and returns up to 32,000 — four times the context and eight times the answer at an unchanged audio rate. The cheap tier tells the same story from below: GPT-4o mini Realtime, launched on 17 December 2024, had the shortest memory in the family at 16,000 tokens. One caveat: these are list prices from OpenAI's own model cards, not what any particular customer pays, and audio tokens are not directly comparable to text tokens — a second of speech consumes far more of them than a second of reading. The comparison here is strictly OpenAI against itself, one voice generation against the next.