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GPT-Realtime-2 benchmarks, pricing and specs

GPT-Realtime-2 is an OpenAI model released on May 7, 2026 that takes text, audio and image input and produces text and audio. It costs $4 per 1M input tokens and accepts up to 128,000 tokens of context. It scores 1079 Elo on Artificial Analysis Speech Arena, #10 of 11 current models (Artificial Analysis, measured October 13, 2026).

Per 1M input tokens
$4
Context window
128K
Artificial Analysis Speech Arena
1079 Elo · #10/11

Data verified October 13, 2026 · Dataset 2026-10-13

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Key facts

Provider
OpenAI
Model family
GPT Realtime
Release date
May 7, 2026
Status
Current
Access
API only
API model id
gpt-realtime-2
Context window
128,000 tokens
Max output
32,000 tokens
Input
text, audio, image
Output
text, audio
Task families
audio
Declared capabilities
realtime voice, reasoning

GPT-Realtime-2 pricing

It is tied for the most expensive of 10 current audio models priced per 1M input tokens.

UnitPrice (USD)TierAppliesSource
1M input tokens$4standardCurrent
1M output tokens$24standardCurrent
1M input tokens$0.40cachedCurrent
1M input tokens$32audio inputCurrent
1M output tokens$64audio outputCurrent

Independent benchmark results

Scores come from independent evaluators that ran the model themselves, pinned to a dated snapshot. Rank is among current models in the same snapshot. OpenAI's own launch figures are listed under strengths with the publisher named, because they are not measured the same way.

BenchmarkScoreRankMeasuredSource
Artificial Analysis Speech Arena1079 Elo#10 of 11October 13, 2026Artificial Analysis · 2026-10-13

Strengths, cautions and best uses

Strengths

  • OpenAI's most capable realtime voice model, with configurable reasoning for speech-to-speech agents
  • Text, audio and image input in one Realtime session, with function calling and prompt caching

Cautions

  • Available only on the Realtime endpoint, not Chat Completions, Responses or Batch
  • Audio costs $32 input and $64 output per 1M tokens, eight and four times its text rates
  • Higher reasoning effort adds latency and output tokens

Best for

  • Speech-to-speech voice agents with tool calls

Alternatives to GPT-Realtime-2

The closest current audiomodels by price. The cheapest model that scores as well or better is listed first; failing that, the cheapest one within 3% of the benchmark's scale.

Compare GPT-Realtime-2 with

Other GPT Realtime models

GPT-Realtime-2 FAQ

How much does GPT-Realtime-2 cost?

GPT-Realtime-2 costs $4 per 1M input tokens at the standard tier. It is tied for the most expensive of 10 current audio models priced per 1M input tokens. Source: OpenAI, verified October 13, 2026.

What is the context window of GPT-Realtime-2?

GPT-Realtime-2 accepts up to 128,000 tokens of context. It can return up to 32,000 tokens in one response. That ranks #4 of 8 current audio models by context length.

How does GPT-Realtime-2 score on independent benchmarks?

GPT-Realtime-2 scores 1079 Elo on Artificial Analysis Speech Arena, #10 of 11 current models (Artificial Analysis, measured October 13, 2026). These are independent evaluations, not OpenAI's own launch figures.

Is GPT-Realtime-2 open source or API only?

GPT-Realtime-2 is available through OpenAI's API only; its weights are not published.

What are the best alternatives to GPT-Realtime-2?

The closest current alternatives by price and measured performance are Gemini 3.8 Flash TTS (88% cheaper per 1M input tokens, $0.50 vs $4), Gemini 3.5 Live Translate Preview (13% cheaper per 1M input tokens, $3.50 vs $4), GPT-4o Transcribe (38% cheaper per 1M input tokens, $2.50 vs $4) and gpt-audio-1.5 (38% cheaper per 1M input tokens, $2.50 vs $4).

Sources

Cite this page

Van Data Team. "GPT-Realtime-2 Benchmarks, Pricing and Specs." AI Model Benchmark Dataset 2026-10-13. https://vandatateam.com/ai-model-benchmarks/gpt-realtime-2

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Production evaluation

Deciding whether GPT-Realtime-2 fits your workload?

Public benchmarks narrow the shortlist. We test the finalists on your own tasks, data and cost limits, then build the routing and review controls to run the winner in production.

  • Evaluation cases and acceptance thresholds tied to real work
  • Model routing, fallbacks and cost controls