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GPT Realtime vs GPT Realtime 2.1

GPT Realtime is served by invitation. Its figures below are the live rates, but calls need a workspace grant first; ask us for access before you build on this comparison.

GPT Realtime 2.1 is served by invitation. Its figures below are the live rates, but calls need a workspace grant first; ask us for access before you build on this comparison.

vs

Which one, when

Text input is $4 per million on both, audio is $32 in and $64 out on both, and cache reads are $0.4 on both; gpt-realtime-2.1 charges more only on text output, $24 against $16, and quadruples the session context to 128K from 32K. It also adds configurable reasoning effort and interruption handling to the older model's function calling. Pick gpt-realtime only to hold an existing integration - on everything but text output the newer model costs the same.

Benchmarks

GPT Realtime 2.1: the vendor has not published benchmark scores.

GPT Realtime: 8 published, but no benchmark it shares with enough other models to compare.

GPT Realtime GPT Realtime 2.1 other models measured peer average ★ no peer scored higher
AMI near+far field (WER)
35.9%
N/A
Big Bench Audio
82.8%
N/A
BFCL v3 (single-turn, python only)
80.4%
N/A

Vendor-published: Amazon OpenAI

Pricing

GPT Realtime GPT Realtime 2.1 Δ
Audio input / 1M tokens $32 $32 =
Audio output / 1M tokens $64 $64 =
Audio cache read / 1M tokens $0.4 $0.4 =
Text input / 1M tokens $4 $4 =
Text output / 1M tokens $16 $24 0.67×
Cache write no separate charge no separate charge -

Rates from the live catalogue at build time; each model page carries the current rate card.

Where they sit · price per 1M audio tokens across all 6 realtime speech-to-speech models on this billing unit (log scale)

Capabilities

GPT Realtime GPT Realtime 2.1
Prompt caching implicit (automatic) implicit (automatic)
Cache lifetime 5-10m, up to 1h 5-10m, up to 1h
Minimum cached prefix 1024 tokens 1024 tokens

Specs

GPT Realtime GPT Realtime 2.1
Input modalities text audio text audio
Output modalities text audio text audio
Released 2025-08-28 2026-07-06
Knowledge cutoff 2023-10 2024-09
Session capabilities
  • Native speech-to-speech over WebSocket
  • function calling
  • 32K context
  • Speech-to-speech over WebSocket
  • configurable reasoning effort
  • tool use
  • interruption handling
  • 128K context
Context window 32K 128K

Specs are transcribed from each vendor’s documentation; a row a vendor does not publish is left out rather than inferred. Full sources: GPT Realtime · GPT Realtime 2.1

Switch between them with one line

Both ids are in every tab below; the highlighted pair of lines is the only edit. Same endpoint, same key, same request shape.

import asyncio, base64, json, websockets

URL = "wss://synthorai.io/v1/realtime?model=gpt-realtime"
# URL = "wss://synthorai.io/v1/realtime?model=gpt-realtime-2.1"  # uncomment this line, comment the one above
# Send ONLY the Authorization header - the beta protocol is retired.
HEADERS = {"Authorization": "Bearer sk-syn-..."}

async def main():
    async with websockets.connect(URL, additional_headers=HEADERS) as ws:
        # 1) configure the speech-to-speech session
        await ws.send(json.dumps({
            "type": "session.update",
            "session": {
                "type": "realtime",
                "output_modalities": ["audio"],
                "audio": {"output": {"voice": "alloy"}},
            },
        }))
        # 2) send input audio (base64 PCM16), then request a spoken reply
        await ws.send(json.dumps({"type": "input_audio_buffer.append", "audio": pcm16_b64}))
        await ws.send(json.dumps({"type": "input_audio_buffer.commit"}))
        await ws.send(json.dumps({"type": "response.create"}))
        # 3) stream the model's audio (and text) back
        async for raw in ws:
            ev = json.loads(raw)
            if ev["type"] == "response.audio.delta":
                play(base64.b64decode(ev["delta"]))   # audio out
            elif ev["type"] == "response.done":
                break

asyncio.run(main())

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FAQ

Which is cheaper, GPT Realtime or GPT Realtime 2.1?

They list the same price on the "Audio input / 1M tokens" row ($32), so price does not decide this one. See the specs and capabilities below.

Can I A/B test GPT Realtime against GPT Realtime 2.1 without two integrations?

Yes. Both are served through the same OpenAI-compatible endpoint with one API key. Switching is a one-line change to the model id, so you can route a fraction of traffic to each and compare bills directly.

Do GPT Realtime and GPT Realtime 2.1 support prompt caching?

Yes. Both bill cache reads below their input rate, so warm-prefix workloads cost less than the list rates suggest. The exact cache-read rows are in the pricing table above.

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