> ## Documentation Index
> Fetch the complete documentation index at: https://docs.getpatter.com/llms.txt
> Use this file to discover all available pages before exploring further.
# OpenAI Realtime
> Models, voices, transcription, and reasoning effort for the OpenAI Realtime engine.
# OpenAI Realtime
`OpenAIRealtime` is the engine wrapper for OpenAI's Realtime API — a single WebSocket session that handles speech-in, reasoning, and speech-out, with sub-500 ms typical turn latency.
For the basic `engine=OpenAIRealtime(...)` quickstart, see [Engines](/python-sdk/engines#openairealtime). This page documents the full configuration surface: every supported model, the streaming transcription options, and the new `reasoning_effort` tier.
Models
Pass any of these to `model=` on `OpenAIRealtime(...)`. Pricing is auto-resolved per model from `DEFAULT_PRICING` — no manual override is required (see [Metrics](/python-sdk/metrics)).
| Model | Audio in / out (per M tokens) | Notes |
| -------------------------------- | ----------------------------- | ---------------------------------------------------------------------------------------- |
| `"gpt-realtime-mini"` (default) | $10 / $20 | Fastest + cheapest. Production default for most voice flows. |
| `"gpt-realtime"` | $32 / $64 | GA realtime model (Aug 2025). |
| `"gpt-realtime-2"` | $32 / $64 | Most-capable. Stronger instruction following, 128K context, supports `reasoning_effort`. |
| `"gpt-4o-realtime-preview"` | $100 / $200 | Earlier preview, retained for compatibility. |
| `"gpt-4o-mini-realtime-preview"` | $10 / $20 | Earlier preview, retained for compatibility. |
The same identifiers are exposed as a `StrEnum` for editor autocomplete:
```python theme={null}
from getpatter.providers.openai_realtime import OpenAIRealtimeModel
OpenAIRealtimeModel.GPT_REALTIME_2 # "gpt-realtime-2"
```
`gpt-realtime-translate` is intentionally **not** supported by Patter's Realtime engine. It lives on a different OpenAI endpoint (`/v1/realtime/translations`), does not accept tool calls or `response.create`, and would invalidate the `Agent` contract Patter exposes. Real-time translation, if added, will land as a dedicated feature — not as a Realtime model variant.
## Reasoning effort
`gpt-realtime-2` accepts a configurable reasoning tier. Patter exposes it as the `reasoning_effort` constructor argument on the lower-level `OpenAIRealtimeAdapter`:
| Value | When to use |
| ----------- | ----------------------------------------------------------------------------------------------------- |
| `"minimal"` | Snappy turn-taking. Skips most reasoning. |
| `"low"` | **Recommended for production voice.** Good instruction following without measurable per-turn latency. |
| `"medium"` | Multi-step tool flows where the model should plan. Adds latency. |
| `"high"` | Complex reasoning. Not recommended for live phone calls. |
When set, Patter injects `session.reasoning = { effort: ... }` into the `session.update` payload. When omitted, the field is not sent and OpenAI's server default applies. The field is a no-op on models that ignore it (for example `gpt-realtime-mini`), so it's safe to leave configured across model swaps.
Higher reasoning tiers add measurable latency to every turn. Stick to `"low"` unless you've profiled the call and confirmed the model needs more.
## Streaming transcription
The Realtime session can run an inline Whisper-family model on inbound audio so you get text deltas alongside the conversation. The model is set via `input_audio_transcription_model`:
| Model | Cost | Notes |
| -------------------------- | ----------- | -------------------------------------------------------------------------------------------------------------------- |
| `"whisper-1"` (default) | \$0.006/min | Established Whisper. Slower partials. |
| `"gpt-4o-mini-transcribe"` | \$0.003/min | Cheapest. |
| `"gpt-4o-transcribe"` | \$0.006/min | Higher accuracy. |
| `"gpt-realtime-whisper"` | \$0.017/min | Streaming-optimised. Lowest-latency partials. Use when you need fast deltas in the dashboard or for live captioning. |
Same enum form:
```python theme={null}
from getpatter.providers.openai_realtime import OpenAITranscriptionModel
OpenAITranscriptionModel.GPT_REALTIME_WHISPER # "gpt-realtime-whisper"
```
## Speakerphone noise & turn detection
The same `noise_reduction` and `turn_detection` knobs documented on the [OpenAI Realtime 2 page](/python-sdk/providers/openai-realtime-2#speakerphone-noise--false-barge-in) are accepted by `OpenAIRealtime(...)` too — they reach the beta adapter, which emits `input_audio_noise_reduction` at the top level of the session (the GA adapter nests it under `session.audio.input`):
```python theme={null}
from getpatter import OpenAIRealtime, RealtimeTurnDetection
engine = OpenAIRealtime(
noise_reduction="far_field", # filter speakerphone / room noise
turn_detection=RealtimeTurnDetection(type="server_vad", threshold=0.6),
)
```
`None` / omitting either field preserves today's behaviour exactly. See the [Realtime 2 reference](/python-sdk/providers/openai-realtime-2#speakerphone-noise--false-barge-in) for the full `RealtimeTurnDetection` field table.
## Worked example — `gpt-realtime-2` with low reasoning + streaming whisper
Constructing the lower-level `OpenAIRealtimeAdapter` directly gives access to every field. This is what `OpenAIRealtime(engine=...)` builds under the hood; reach for it when you need `reasoning_effort` or a non-default transcription model.
```python Python theme={null}
import asyncio
from getpatter import Patter, Twilio
from getpatter.providers.openai_realtime import (
OpenAIRealtimeAdapter,
OpenAIRealtimeModel,
OpenAITranscriptionModel,
)
phone = Patter(carrier=Twilio(), phone_number="+15555550100") # TWILIO_* from env
adapter = OpenAIRealtimeAdapter(
api_key="", # reads OPENAI_API_KEY
model=OpenAIRealtimeModel.GPT_REALTIME_2,
voice="nova",
instructions="You are a helpful, concise voice assistant.",
input_audio_transcription_model=OpenAITranscriptionModel.GPT_REALTIME_WHISPER,
reasoning_effort="low", # OpenAI's recommended production tier
)
agent = phone.agent(
engine=adapter, # adapter passed as engine
system_prompt="You are a helpful assistant.",
first_message="Hi, how can I help today?",
)
async def main() -> None:
await phone.serve(agent)
asyncio.run(main())
```
```typescript TypeScript theme={null}
// See /typescript-sdk/providers/openai-realtime
```
Since 0.6.2 you can pass `reasoning_effort` and `input_audio_transcription_model` directly to the engine wrapper — `OpenAIRealtime(model="gpt-realtime-2", reasoning_effort="low", input_audio_transcription_model="gpt-realtime-whisper")`. Reach for the lower-level `OpenAIRealtimeAdapter` only when you need every field (custom VAD type, modalities, `silence_duration_ms`, etc.). For the GA `gpt-realtime-2` endpoint, prefer the dedicated [`OpenAIRealtime2`](/python-sdk/engines#openairealtime2) marker — it dispatches to a separate adapter that handles the GA-shape `session.update` wire format automatically.
## Backward compatibility
* Defaults are unchanged: `model="gpt-realtime-mini"`, `input_audio_transcription_model="whisper-1"`, `reasoning_effort=None`.
* All existing `OpenAIRealtime(...)` constructions keep working without code changes.
* Pricing for new models is added under `DEFAULT_PRICING["openai_realtime"].models[...]`. The earlier `Patter(pricing={"openai_realtime": DEFAULT_PRICING["openai_realtime_2"]})` workaround is no longer needed — just construct with `model="gpt-realtime-2"`.
## What's Next
All engine classes side by side.
Per-call cost breakdown and the model-aware pricing table.
Configure system prompts, tools, and first messages.
Function calling inside a Realtime session.