GPT Realtime 2.1 vs GPT Realtime 2.1 Mini
GPT Realtime 2.1 目前为邀请制。下方是它的实时价格,但调用前需要先为你的工作空间开通权限;打算根据这份对比做开发的话,请先向我们申请。
GPT Realtime 2.1 Mini 目前为邀请制。下方是它的实时价格,但调用前需要先为你的工作空间开通权限;打算根据这份对比做开发的话,请先向我们申请。
什么时候选哪个
mini 档在每一行都更便宜——文本每百万 $0.6 和 $2.4 对 $4 和 $24,音频每百万输入/输出 $10 和 $20 对 $32 和 $64——即音频大约低 3 倍、文本输入约低 7 倍。两者都带 128K 会话上下文、语音到语音、工具使用和提示缓存;完整版另外写明了可配置的推理力度和打断处理。走量选 mini,需要按会话调节推理力度时选完整版。
价格
| GPT Realtime 2.1 | GPT Realtime 2.1 Mini | Δ | |
|---|---|---|---|
| 音频输入 / 1M token | $32 | $10 | 3.2× |
| 音频输出 / 1M token | $64 | $20 | 3.2× |
| 音频缓存读取 / 1M token | $0.4 | $0.3 | 1.3× |
| 文本输入 / 1M token | $4 | $0.6 | 6.7× |
| 文本输出 / 1M token | $24 | $2.4 | 10× |
| 缓存写入 | 不单独收费 | 不单独收费 | - |
价格取自构建时的实时目录,最新价格见各模型页面。
两个模型所处的位置:全部 6 个按同一单位计费的实时语音对话模型的每 1M 音频 token 价格分布(对数刻度)
能力
| GPT Realtime 2.1 | GPT Realtime 2.1 Mini | |
|---|---|---|
| 提示词缓存 | 隐式(自动) | 隐式(自动) |
| 缓存有效期 | 5-10m, up to 1h | 5-10m, up to 1h |
| 最小缓存前缀 | 1024 个 token | 1024 个 token |
规格
| GPT Realtime 2.1 | GPT Realtime 2.1 Mini | |
|---|---|---|
| 输入模态 | 文本 音频 | 文本 音频 |
| 输出模态 | 文本 音频 | 文本 音频 |
| 发布日期 | 2026-07-06 | 2026-07-06 |
| 知识截止日期 | 2024-09 | 2024-09 |
| 会话能力 |
|
|
| 上下文窗口 | 128K | 128K |
规格照录自各供应商的文档;供应商没有公布的项目,对应的行直接省略,不做推断。 完整来源: GPT Realtime 2.1 · GPT Realtime 2.1 Mini
改一行代码就能在两个模型之间切换
下方每个标签页里都有两个模型 ID,高亮的那两行是唯一要改的地方。端点不变,API key 不变,请求结构也不变。
import asyncio, base64, json, websockets
URL = "wss://synthorai.io/v1/realtime?model=gpt-realtime-2.1"
# URL = "wss://synthorai.io/v1/realtime?model=gpt-realtime-2.1-mini" # 取消注释此行,注释上一行
# 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=gpt-realtime-2.1", {
// const ws = new WebSocket("wss://synthorai.io/v1/realtime?model=gpt-realtime-2.1-mini", { // 取消注释此行,注释上一行
// 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=gpt-realtime-2.1' <<'EOF'
# 'wss://synthorai.io/v1/realtime?model=gpt-realtime-2.1-mini' <<'EOF' # 取消注释此行,注释上一行
{"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=gpt-realtime-2.1", h)
// c, _, err := websocket.DefaultDialer.Dial("wss://synthorai.io/v1/realtime?model=gpt-realtime-2.1-mini", h) // 取消注释此行,注释上一行
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=gpt-realtime-2.1"), new WebSocket.Listener() {
// .buildAsync(URI.create("wss://synthorai.io/v1/realtime?model=gpt-realtime-2.1-mini"), new WebSocket.Listener() { // 取消注释此行,注释上一行
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);常见问题
GPT Realtime 2.1 和 GPT Realtime 2.1 Mini 哪个更便宜?
按「音频输入 / 1M token」算,GPT Realtime 2.1 Mini 更便宜($10 对 $32,相差 3.2×)。其他计费项的结论可能相反,完整价格见上方表格,实际成本取决于你的用量构成。
不用分别集成两次,就能对 GPT Realtime 2.1 和 GPT Realtime 2.1 Mini 做 A/B 测试吗?
可以。两个模型走同一个 OpenAI 兼容端点,用同一个 API key,切换时只要改一行里的模型名,所以可以给两个模型各分一部分流量,直接对比账单。
GPT Realtime 2.1 和 GPT Realtime 2.1 Mini 支持提示词缓存吗?
支持。两个模型的缓存读取价都低于各自的输入价,所以前缀能反复命中缓存的负载,实际成本会比按官网价估算的低。具体的缓存读取价见上方价格表。