Qwen3 TTS Instruct Flash vs BytePlus Seed TTS 2.0
何时使用哪一个 — 经过整理的结论，而非基准测试表格
qwen3-tts-instruct-flash 每百万字符便宜 2.6 倍（$11.5 对 $30），两者也都接受自然语言的音色指令，但请求长度差别很大：600 个字符对 4096。seed-tts-2.0 还在描述式控制之外提供数值型语音参数，并按场景分组公布音色。短句要控成本选 qwen3-tts-instruct-flash，长段落和更细的音色控制选 seed-tts-2.0。
定价
| Qwen3 TTS Instruct Flash | BytePlus Seed TTS 2.0 | Δ | |
|---|---|---|---|
| 每 1M 字符 | $11.5 | $30 | 0.38× |
费率取自构建时的实时目录；每个模型页面均附有当前的费率卡。
它们的位置 — 以该计费单位计费的所有 7 个 文本转语音 模型的 每 1M 字符的价格（对数刻度）
能力
| Qwen3 TTS Instruct Flash | BytePlus Seed TTS 2.0 | |
|---|---|---|
| 流式传输 | 是 | 是 |
| SSML | undocumented | unsupported |
| 计费单位 | character | character |
规格
| Qwen3 TTS Instruct Flash | BytePlus Seed TTS 2.0 | |
|---|---|---|
| 输入模态 | 文本 | 文本 |
| 输出模态 | 音频 | 音频 |
| 请求限制 | 600 characters | — |
| 声音 | System voices published with one-line personas, among them Cherry (a sunny, positive, friendly and natural young woman), Serena, Ethan, Chelsie, Momo, Vivian, Moon, Maia, Kai, Nofish (a designer who cannot pronounce retroflex sounds), Bella, Eldric Sage, Mia, Mochi, Bellona, Vincent, Bunny, Neil, Elias, Arthur, Nini, Seren, Pip and Stella the Qwen-TTS voice list pairs each voice with the exact model ids that accept it. | TTS 2.0 voices carry *_uranus_bigtts speaker IDs and are listed by scenario (General, Entertainment, Education, Dubbing, AudioBook, RolePlay, CustomerService) on the Voice List page per-voice emotion via audio_params.emotion with emotion_scale 1 to 5 (default 4), speech_rate and loudness_rate in [-50, 100], and post_process.pitch in [-12, 12]. |
| 语言 | Chinese (Mandarin), English, German, Italian, Portuguese, Spanish, Japanese, Korean, French and Russian. language_type defaults to Auto for mixed-language or undetermined input, which Alibaba documents as not guaranteeing accuracy naming a single language is documented to significantly improve synthesis quality. Unlike the Qwen3-TTS-Flash series, the Instruct series lists no Chinese dialect voices (Beijing, Shanghainese, Sichuan, Nanjing, Shaanxi, Hokkien, Tianjin, Cantonese). | English, Chinese, Japanese, German, French, Mexican Spanish, Indonesian Bahasa, Brazilian Portuguese, Italian and Korean |
| 语音控制 |
| context_texts and section_id are TTS 2.0 only: a plain-language instruction steers rate, emotion, volume and style (only the first list value takes effect, and its text is not billed), and section_id links up to 30 rounds or 10 minutes of earlier synthesis as historical context. |
| 限制 | HTTP non-real-time speech synthesis API the -realtime suffix marks the WebSocket sibling. Input text capped at 600 characters, multilingual mixed input allowed. Non-streaming returns an audio file URL valid for 24 hours streaming returns Base64-encoded PCM in chunks with the URL only in the final packet, played back in the official samples as 24 kHz mono 16-bit audio. Billed by input text characters, reported as usage.characters (input_tokens and output_tokens are always 0 on the Qwen3-TTS series) output audio is free. | Integration via uni-directional streaming HTTP, uni- or bi-directional streaming WebSocket and online SDK sampling rate 24K/16K/8K on the uni-directional streaming and non-streaming interfaces, 48K/24K/16K/8K on the bi-directional interface output PCM, OGG_OPUS or MP3 (WAV is accepted but returns multiple headers when streaming) SSML is not supported |
规格转录自各供应商的文档；若供应商未发布某项数据，则直接省略该行，而非进行推断。 完整来源： Qwen3 TTS Instruct Flash · BytePlus Seed TTS 2.0
只需一行代码即可在它们之间切换
两个 ID 都包含在下方的每个选项卡中 — 高亮显示的两行是唯一的修改。相同的端点，相同的密钥，相同的请求结构。
from openai import OpenAI
client = OpenAI(
base_url="https://synthorai.io/v1",
api_key="sk-syn-...",
)
resp = client.audio.transcriptions.create(
model="qwen3-tts-instruct-flash",
# model="seed-tts-2.0", # 取消注释此行，注释上一行
file=open("meeting.mp3", "rb"),
language="en",
)
print(resp.text)import OpenAI from "openai";
import fs from "node:fs";
const client = new OpenAI({
baseURL: "https://synthorai.io/v1",
apiKey: "sk-syn-...",
});
const resp = await client.audio.transcriptions.create({
model: "qwen3-tts-instruct-flash",
// model: "seed-tts-2.0", // 取消注释此行，注释上一行
file: fs.createReadStream("meeting.mp3"),
});
console.log(resp.text);curl https://synthorai.io/v1/audio/transcriptions \
-H "Authorization: Bearer sk-syn-..." \
-F model="qwen3-tts-instruct-flash" \
# -F model="seed-tts-2.0" \ # 取消注释此行，注释上一行
-F file=@meeting.mp3package main
import (
"context"
"fmt"
"os"
"github.com/openai/openai-go/v3"
"github.com/openai/openai-go/v3/option"
)
func main() {
client := openai.NewClient(
option.WithBaseURL("https://synthorai.io/v1"),
option.WithAPIKey("sk-syn-..."),
)
f, _ := os.Open("meeting.mp3")
resp, _ := client.Audio.Transcriptions.New(context.TODO(), openai.AudioTranscriptionNewParams{
Model: "qwen3-tts-instruct-flash",
// Model: "seed-tts-2.0", // 取消注释此行，注释上一行
File: f,
})
fmt.Println(resp.Text)
}import com.openai.client.OpenAIClient;
import com.openai.client.okhttp.OpenAIOkHttpClient;
import com.openai.models.audio.transcriptions.*;
import java.nio.file.Paths;
OpenAIClient client = OpenAIOkHttpClient.builder()
.baseUrl("https://synthorai.io/v1")
.apiKey("sk-syn-...")
.build();
Transcription resp = client.audio().transcriptions().create(
TranscriptionCreateParams.builder()
.model("qwen3-tts-instruct-flash")
// .model("seed-tts-2.0") // 取消注释此行，注释上一行
.file(Paths.get("meeting.mp3"))
.build()).asTranscription();
System.out.println(resp.text());常见问题
Qwen3 TTS Instruct Flash 和 BytePlus Seed TTS 2.0 哪个更便宜？
在 每 1m 字符 方面，Qwen3 TTS Instruct Flash 更便宜（$11.5 对比 $30，相差 2.6×）。其他行可能得出相反的结论——上方表格提供了完整信息，实际成本取决于你的组合使用情况。
我可以在不进行两次集成的情况下，对 Qwen3 TTS Instruct Flash 和 BytePlus Seed TTS 2.0 进行 A/B 测试吗？
可以。两者均通过同一个兼容 OpenAI 的端点提供服务，并使用同一把 API 密钥——切换只需更改一行模型字符串，因此你可以将一部分流量路由到各个模型并直接比较账单。
文本转语音如何计费？
按输入文本的字符数计费，每次请求的字符上限如规格表所示。无论使用哪种模型，长文本都必须在多个请求中分块。