Amazon Transcribe = $1.44/hr and an S3 Bucket
Amazon Transcribe charges $0.024/minute ($1.44/hr) on tier 1 and makes you upload files to S3 before each job. SpeakEasy is $0.20/hr, file goes directly to the API, done in one call.
Feature-by-feature comparison
AWS pricing plus AWS operational overhead, or a flat rate with zero AWS footprint.
| Feature | SpeakEasy | Amazon Transcribe |
|---|---|---|
| STT Price per Hour | $0.20 | $1.44 (tier 1, 0-250k min) |
| Medical/Call Analytics tier | Standard rate | $4.80+/hr |
| Monthly Plan | $10/mo (50 hrs included) | Pay-as-you-go |
| Free Tier | $1 first month | 60 min/month × 12 months |
| Languages | 99+ | 40+ |
| Speaker Diarization | Yes (included) | Yes |
| Word-level Timestamps | Yes | Yes |
| File ingestion | Direct multipart upload | S3 pre-upload required |
| API Model | Sync single call | Async job + polling |
| OpenAI SDK Compatible | Yes | No (AWS SDK) |
| Setup required | API key only | AWS account + IAM + S3 bucket |
| Pricing Model | Simple flat rate | Volume-tiered + add-ons |
Pricing breakdown
7x the price and a stack of AWS services, or one API call.
SpeakEasy
- ✓STT at $0.20/hour (50 hrs included)
- ✓One API call — no S3, no IAM, no jobs
- ✓99+ languages vs 40+
- ✓Standard OpenAI SDK
- ✓Includes TTS for voice agents
Amazon Transcribe
- ✕S3 upload required before every job
- ✕Async job + polling loop
- ✕AWS account + IAM role needed
- ✕Custom AWS SDK (boto3) only
- ✓60 min/month free for 12 months
Save 86% per hour — plus an S3 bucket you do not need
100 hrs/month: Amazon Transcribe tier 1 = $144. SpeakEasy = $22.50. And you skip the S3 lifecycle rules, IAM role, and polling code.
Skip S3
Amazon Transcribe requires you to upload to S3 first, then submit a job, then poll, then parse the result. SpeakEasy accepts the file directly.
# Amazon Transcribe — requires AWS creds, S3 upload, async job
import boto3, time
s3 = boto3.client("s3")
s3.upload_file("meeting.mp3", "my-bucket", "meeting.mp3")
transcribe = boto3.client("transcribe", region_name="us-east-1")
transcribe.start_transcription_job(
TranscriptionJobName="job-" + str(int(time.time())),
Media={"MediaFileUri": "s3://my-bucket/meeting.mp3"},
MediaFormat="mp3",
LanguageCode="en-US",
)
# then poll get_transcription_job(...) until status == COMPLETED
# then fetch TranscriptFileUri, parse JSON, extract text# SpeakEasy — one call, file goes directly, OpenAI SDK
from openai import OpenAI
client = OpenAI(
api_key="YOUR_SPEAKEASY_KEY",
base_url="https://www.tryspeakeasy.io/api/v1"
)
transcript = client.audio.transcriptions.create(
model="whisper-large-v3",
file=open("meeting.mp3", "rb")
)
print(transcript.text)The verdict
Amazon Transcribe is priced for the AWS-native enterprise. $1.44/hr at tier 1, higher for Medical or Call Analytics specializations, and a deployment flow that assumes you already run half your stack on AWS.
If your audio already lives in S3 and your compliance team has blessed AWS, Transcribe's integration is reasonable. Otherwise, you're paying AWS prices and doing AWS plumbing to ingest a file you already had on disk.
SpeakEasy takes a multipart upload in one call, returns the transcript synchronously, and runs at $0.20/hr. No S3, no IAM, no polling. If you are not already locked into AWS, this comparison is not close.
$1 for your first month. Full 50 hours included.
Also compare SpeakEasy with:
$1. 50 hours. Both STT and TTS.
Your current speech API provider is charging you too much. Switch in one line of code.