Whisper v1
Provider list prices: no platform markup, pay-as-you-go. These are official list prices. Logged-in customers may see effective prices including workspace discounts on /console/pricing.
Use Whisper v1 in 30 seconds
OpenAI-compatible: swap the base_url, keep your SDK. POST /v1/audio/transcriptions
from openai import OpenAI
client = OpenAI(
base_url="https://synthorai.io/v1",
api_key="sk-syn-...",
)
resp = client.audio.transcriptions.create(
model="whisper-1",
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: "whisper-1",
file: fs.createReadStream("meeting.mp3"),
});
console.log(resp.text);curl https://synthorai.io/v1/audio/transcriptions \
-H "Authorization: Bearer sk-syn-..." \
-F model="whisper-1" \
-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: "whisper-1",
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("whisper-1")
.file(Paths.get("meeting.mp3"))
.build()).asTranscription();
System.out.println(resp.text());About Whisper v1
Whisper v1 is OpenAI's general-purpose speech recognition model, trained on a large dataset of diverse audio.
- It is a multitask system that performs transcription, multilingual speech recognition, speech translation, and language identification, and is billed simply per minute of audio processed.
- As the long-standing workhorse of OpenAI's audio stack, it remains broadly compatible across the transcription and translation endpoints.
- Synthorai accepts Whisper jobs on its OpenAI-compatible /v1/audio/transcriptions route, so existing clients work as-is.
Specs & limits
| Modalities | audio → text |
| Audio limits | mp3/mp4/mpeg/mpga/m4a/wav/webm, up to 25MB; word- and segment-level timestamps (verbose_json), srt/vtt output; no streaming; only model supported on the translations endpoint (to English) |
| Notable | Open-source Whisper large-v2 served via API; prompt limited to 224 tokens. |
FAQ
Is the Whisper v1 API free to try?
Yes: new accounts get 10 trial calls and up to $1 in free credit, no card required. That's enough to try Whisper v1 against your real workload before adding a payment method.
What is Whisper v1 best at?
Multitask: transcription, translation, language identification, plus billed simply per minute of audio and compatible across transcription and translation endpoints. See the About section for the full picture from the vendor's own release notes.
How much does Whisper v1 cost?
Whisper v1 costs $0.006 per minute of audio transcribed on Synthorai: pay-as-you-go, no platform markup, no subscription.
Which languages does Whisper v1 support?
On Synthorai you call Whisper v1 through POST /v1/audio/transcriptions, the OpenAI transcription API shape. Official language list →
How do I get access to Whisper v1?
Point your existing OpenAI SDK at base_url="https://synthorai.io/v1", set model="whisper-1", and you're done. One API key covers every model on the gateway.