gemini-3.1-flash-live vs GPT Realtime 2.1
Which one, when — curated verdict, not a benchmark table
Both are realtime audio models billed per million tokens, but gemini-3.1-flash-live is the cheaper lane: $3 audio input versus $32 (about 10.7x less) and $12 audio output versus $64, with text at $0.75/$4.5 against $4/$24 (roughly 5.3x less). It also takes image and video input alongside audio and text, carries a 131072-token context with up to 65536 output tokens, and its Live API sessions cap at 15 minutes audio-only (2 minutes with video) unless extended. Pick gpt-realtime-2.1 if you want OpenAI's audio/text stack with $0.4 cache reads, its 128000-token context and 32000 max output.
Pricing
| gemini-3.1-flash-live | GPT Realtime 2.1 | Δ | |
|---|---|---|---|
| Audio input / 1M tokens | $3 | $32 | 0.094× |
| Audio output / 1M tokens | $12 | $64 | 0.19× |
| Audio cache read / 1M tokens | — | $0.4 | — |
| Text input / 1M tokens | $0.75 | $4 | 0.19× |
| Text output / 1M tokens | $4.5 | $24 | 0.19× |
| Cache write | — | no separate charge | — |
Rates from the live catalog at build time; each model page carries the current card.
Where they sit — price per 1M audio tokens across all 6 realtime speech-to-speech models on this billing unit (log scale)
Capabilities
| gemini-3.1-flash-live | GPT Realtime 2.1 | |
|---|---|---|
| Thinking control | always on | — |
| Prompt caching | implicit + explicit | implicit (automatic) |
| Cache lifetime | not published | 5–10m, up to 1h |
| Minimum cached prefix | 4096 tokens | 1024 tokens |
Specs
| gemini-3.1-flash-live | GPT Realtime 2.1 | |
|---|---|---|
| Input modalities | text image audio video | text audio |
| Output modalities | text audio | text audio |
| Released | 2026-03-26 | 2026-07-06 |
| Knowledge cutoff | — | 2024-09 |
| Voices | Any voice from the Gemini text-to-speech voice set native-audio output models switch languages naturally during a conversation. | — |
| Session capabilities |
|
|
| Context window | 131K | 128K |
Specs are transcribed from each vendor’s documentation; a row a vendor does not publish is left out rather than inferred. Full sources: gemini-3.1-flash-live · 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=gemini-3.1-flash-live"
# 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())import WebSocket from "ws";
const ws = new WebSocket("wss://synthorai.io/v1/realtime?model=gemini-3.1-flash-live", {
// const ws = new WebSocket("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-..." },
});
ws.on("open", () => {
// configure the speech-to-speech session
ws.send(JSON.stringify({ type: "session.update", session: {
type: "realtime", output_modalities: ["audio"], audio: { output: { voice: "alloy" } },
} }));
// send input audio (base64 PCM16), then request a spoken reply
ws.send(JSON.stringify({ type: "input_audio_buffer.append", audio: pcm16Base64 }));
ws.send(JSON.stringify({ type: "input_audio_buffer.commit" }));
ws.send(JSON.stringify({ type: "response.create" }));
});
ws.on("message", (raw) => {
const ev = JSON.parse(raw.toString());
if (ev.type === "response.audio.delta") playAudio(Buffer.from(ev.delta, "base64")); // audio out
else if (ev.type === "response.done") ws.close();
});# Realtime is a WebSocket protocol — use a WS client such as websocat.
# Each line below is one OpenAI Realtime event (JSON) sent to the session.
websocat -H 'Authorization: Bearer sk-syn-...' \
'wss://synthorai.io/v1/realtime?model=gemini-3.1-flash-live' <<'EOF'
# 'wss://synthorai.io/v1/realtime?model=gpt-realtime-2.1' <<'EOF' # uncomment this line, comment the one above
{"type":"session.update","session":{"type":"realtime","output_modalities":["audio"],"audio":{"output":{"voice":"alloy"}}}}
{"type":"input_audio_buffer.append","audio":"<base64-pcm16>"}
{"type":"input_audio_buffer.commit"}
{"type":"response.create"}
EOF
# Responses stream back as response.audio.delta (base64 audio out) … response.donepackage main
import (
"net/http"
"github.com/gorilla/websocket"
)
func main() {
h := http.Header{}
h.Set("Authorization", "Bearer sk-syn-...")
// Send ONLY the Authorization header — the beta protocol is retired.
c, _, err := websocket.DefaultDialer.Dial("wss://synthorai.io/v1/realtime?model=gemini-3.1-flash-live", h)
// c, _, err := websocket.DefaultDialer.Dial("wss://synthorai.io/v1/realtime?model=gpt-realtime-2.1", h) // uncomment this line, comment the one above
if err != nil {
panic(err)
}
defer c.Close()
// configure the speech-to-speech session, send audio, request a spoken reply
c.WriteJSON(map[string]any{"type": "session.update", "session": map[string]any{
"type": "realtime", "output_modalities": []string{"audio"},
"audio": map[string]any{"output": map[string]any{"voice": "alloy"}}}})
c.WriteJSON(map[string]any{"type": "input_audio_buffer.append", "audio": pcm16B64})
c.WriteJSON(map[string]any{"type": "input_audio_buffer.commit"})
c.WriteJSON(map[string]any{"type": "response.create"})
for {
var ev struct {
Type string `json:"type"`
Delta string `json:"delta"`
}
if err := c.ReadJSON(&ev); err != nil {
return
}
if ev.Type == "response.audio.delta" {
playAudio(ev.Delta) // base64 audio out
} else if ev.Type == "response.done" {
return
}
}
}import java.net.URI;
import java.net.http.HttpClient;
import java.net.http.WebSocket;
import java.util.concurrent.CompletionStage;
// JDK built-in WebSocket — no extra dependency needed.
WebSocket ws = HttpClient.newHttpClient().newWebSocketBuilder()
.header("Authorization", "Bearer sk-syn-...")
// Send ONLY the Authorization header — the beta protocol is retired.
.buildAsync(URI.create("wss://synthorai.io/v1/realtime?model=gemini-3.1-flash-live"), new WebSocket.Listener() {
// .buildAsync(URI.create("wss://synthorai.io/v1/realtime?model=gpt-realtime-2.1"), new WebSocket.Listener() { // uncomment this line, comment the one above
public CompletionStage<?> onText(WebSocket w, CharSequence data, boolean last) {
// handle response.audio.delta (base64 audio out) / response.done here
w.request(1);
return null;
}
}).join();
// configure the session, send input audio, then request a spoken reply
ws.sendText("{\"type\":\"session.update\",\"session\":{\"type\":\"realtime\",\"output_modalities\":[\"audio\"],\"audio\":{\"output\":{\"voice\":\"alloy\"}}}}", true);
ws.sendText("{\"type\":\"input_audio_buffer.append\",\"audio\":\"<base64-pcm16>\"}", true);
ws.sendText("{\"type\":\"input_audio_buffer.commit\"}", true);
ws.sendText("{\"type\":\"response.create\"}", true);FAQ
Which is cheaper, gemini-3.1-flash-live or GPT Realtime 2.1?
gemini-3.1-flash-live is cheaper on audio input / 1m tokens ($3 vs $32, 11× apart). Other rows may point the other way — the table above carries the full card, and real cost depends on your mix.
Can I A/B test gemini-3.1-flash-live 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 model-string change, so you can route a fraction of traffic to each and compare bills directly.
Do gemini-3.1-flash-live and GPT Realtime 2.1 support prompt caching?
Cache-read pricing is listed for only one of the two on our feed; where a rate is missing, the provider does not price cached reads separately.