GPT-4o Transcribe vs Whisper v1
Which one, when — curated verdict, not a benchmark table
These bill in different units — whisper-1 at $0.006 per audio minute, gpt-4o-transcribe at $6 per million audio input tokens plus $2.5 and $10 per million text tokens — so no single conversion between them is honest. whisper-1 is the one with word- and segment-level timestamps, srt/vtt output and the translations endpoint, but it does not stream; gpt-4o-transcribe streams, including realtime transcription sessions, and returns json or text only. Pick whisper-1 for subtitles and translation, gpt-4o-transcribe for live transcripts.
Pricing
| GPT-4o Transcribe | Whisper v1 | Δ | |
|---|---|---|---|
| Per audio minute | — | $0.006 | — |
| Audio input / 1M tokens | $6 | — | — |
| Text output / 1M tokens | $10 | — | — |
These two models bill in different units, so no Δ is shown — converting between them would require an assumption we have not measured. Each card is listed in its own unit above.
Capabilities
| GPT-4o Transcribe | Whisper v1 | |
|---|---|---|
| Speaker diarization | no | no |
| Streaming | yes | no |
| Timestamps | no | yes |
Specs
| GPT-4o Transcribe | Whisper v1 | |
|---|---|---|
| Input modalities | text audio | audio |
| Output modalities | text | text |
| Released | 2025-03-20 | 2023-03-01 |
| Knowledge cutoff | 2024-06 | — |
| Limits | mp3/mp4/mpeg/mpga/m4a/wav/webm, up to 25MB streaming transcription supported (incl. Realtime transcription sessions) json/text output only no word timestamps or diarization | 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) |
| Languages | 57 languages listed for the transcriptions endpoint (one shared list for all transcription models) ISO 639-1 / 639-3 codes accepted for GPT-4o-based models | Trained on 98 languages 57 listed as supported, the languages that met OpenAI's under-50% word-error-rate threshold across the transcriptions and translations endpoints |
| Max output | 2K | — |
Specs are transcribed from each vendor’s documentation; a row a vendor does not publish is left out rather than inferred. Full sources: GPT-4o Transcribe · Whisper v1
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.
from openai import OpenAI
client = OpenAI(
base_url="https://synthorai.io/v1",
api_key="sk-syn-...",
)
resp = client.audio.transcriptions.create(
model="gpt-4o-transcribe",
# model="whisper-1", # uncomment this line, comment the one above
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: "gpt-4o-transcribe",
// model: "whisper-1", // uncomment this line, comment the one above
file: fs.createReadStream("meeting.mp3"),
});
console.log(resp.text);curl https://synthorai.io/v1/audio/transcriptions \
-H "Authorization: Bearer sk-syn-..." \
-F model="gpt-4o-transcribe" \
# -F model="whisper-1" \ # uncomment this line, comment the one above
-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: "gpt-4o-transcribe",
// Model: "whisper-1", // uncomment this line, comment the one above
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("gpt-4o-transcribe")
// .model("whisper-1") // uncomment this line, comment the one above
.file(Paths.get("meeting.mp3"))
.build()).asTranscription();
System.out.println(resp.text());FAQ
Which is cheaper, GPT-4o Transcribe or Whisper v1?
They bill in different units, so there is no single honest number: GPT-4o Transcribe and Whisper v1 each appear in their own unit in the table above. Compare them on your own workload — the practical trade-off is described in the verdict at the top of this page.
Can I A/B test GPT-4o Transcribe against Whisper v1 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 GPT-4o Transcribe and Whisper v1 support speaker diarization?
The capability table above answers this per model, straight from each vendor’s documentation — diarization, streaming and timestamps are listed separately because models differ on all three.