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Model comparison
GPT-Realtime-2.1 vs Eleven v3 Conversational
Compare GPT-Realtime-2.1 and Eleven v3 Conversational using the same provider-sourced voice & realtime rubric. No mystery score and no invented benchmark ranking.
Quick take
GPT-Realtime-2.1
OpenAI's realtime speech-to-speech reasoning model for tool-using voice agents that also need text and image context.
Best for
- Tool-using customer or employee voice agents
- Multimodal realtime assistants
- OpenAI-native agent stacks
Watch out for
There is no published universal latency number, and audio-token costs are hard to compare directly with minute- or character-priced competitors.
Eleven v3 Conversational
ElevenLabs' expressive realtime text-to-speech model for natural dialogue, emotional delivery, audio tags, and more than 70 languages.
Best for
- Expressive support and assistant voices
- Multilingual interactive characters
- Agent stacks that already supply reasoning and tools
Watch out for
It is not a complete speech-to-speech agent by itself. End-to-end latency also includes transcription, LLM response time, transport, and playback.
Compare the published facts
GPT-Realtime-2.1 vs Eleven v3 Conversational
Values use each provider's own published units and limits. A blank means the provider did not publish a directly comparable value in the sources reviewed.
| Voice & realtime | GPT-Realtime-2.1 | Eleven v3 Conversational |
|---|---|---|
| Price basisToken-, character-, or minute-based price for the listed access route. | Audio $32 in · $64 out / 1M tokens | $0.05 / 1K characters |
| Interaction modeSpeech-to-speech, audio-to-audio, or streamed text-to-speech behavior. | Speech-to-speech with text/image context | Realtime text-to-speech / text-to-dialogue |
| Published latencyProvider-published measurement with its stated exclusions; not a Cody test. | Not published | ~280ms, excluding app/network |
| LanguagesProvider-documented language coverage or a clear unpublished marker. | Multilingual; exact list not published here | 70+ languages |
| Tools & controlNative function calling, reasoning, or speech-control features. | Function calling and configurable reasoning | Audio tags; orchestration handled by your agent stack |
| Context or input limitDocumented token or character limit where it is meaningful. | 128K input · 32K max output | 5K-character guidance for v3 family; verify endpoint |
How to choose
Compare the job, not the hype.
Start with the job you need to complete, then validate cost, access, and policy details on your exact provider route.
GPT-Realtime-2.1
OpenAI says API content is not used for training by default. Default abuse-monitoring logs may be retained up to 30 days, with additional controls available to qualifying organizations.
Provider and API links
Eleven v3 Conversational
ElevenLabs says enterprise customer data is not used for training by default. Other users can opt out of model improvement; enterprise zero-retention and regional environments are available with plan-specific limits.
Provider and API links
Frequently asked questions
GPT-Realtime-2.1 vs Eleven v3 Conversational FAQ
What is the main difference between GPT-Realtime-2.1 and Eleven v3 Conversational?
GPT-Realtime-2.1: OpenAI's realtime speech-to-speech reasoning model for tool-using voice agents that also need text and image context. Eleven v3 Conversational: ElevenLabs' expressive realtime text-to-speech model for natural dialogue, emotional delivery, audio tags, and more than 70 languages.
Should I choose GPT-Realtime-2.1 or Eleven v3 Conversational?
Consider GPT-Realtime-2.1 when your priority is Tool-using customer or employee voice agents. Consider Eleven v3 Conversational when your priority is Expressive support and assistant voices. Test both with your own data and provider route before committing.
Is this GPT-Realtime-2.1 vs Eleven v3 Conversational comparison based on Cody benchmarks?
No. This comparison aligns provider-published facts for the Voice & realtime category. It does not claim a universal winner or combine incompatible third-party benchmark scores.